bike-share-case-study-capstone-project (3).ipynb

{"metadata":{"kernelspec":{"name":"ir","display_name":"R","language":"R"},"language_info":{"name":"R","codemirror_mode":"r","pygments_lexer":"r","mimetype":"text/x-r-source","file_extension":".r","version":"4.0.5"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"#  **Case Study: How Does a Bike-Share Navigate Speedy Success?**\n","metadata":{}},{"cell_type":"markdown","source":"![Bike Image](https://images.unsplash.com/photo-1541623498-e0ae057f4cf8?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MTcxfHxiaWtlJTIwcGljeXVyZXN8ZW58MHx8MHx8&auto=format&fit=crop&w=500&q=60)","metadata":{}},{"cell_type":"markdown","source":"# **Introduction**\n\nThis case study is a Capstone Project for the Google Data Analytics Professional Certificate. The data for this case study has been made available by Motivate International Inc. under this [license](https://ride.divvybikes.com/data-license-agreement). The dataset is composed of first party data collected by Lyft Bike's and Scooters, LLC (\"Bikeshare\") and the City of Chicago's (\"Divvy\") bike sharing service. \n\nFor the purposes of this project, the data is recognized to be collected by Cyclistic, a fictional bike-share company situated in Chicago. The Dataset consists of bike trips for 12 months from November 2021 - October 2022 [dataset](https://divvy-tripdata.s3.amazonaws.com/index.html)","metadata":{}},{"cell_type":"markdown","source":"# **Scenario**\n\n\nYou are a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The director\nof marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore,\nyour team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights,\nyour team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclistic executives\nmust approve your recommendations, so they must be backed up with compelling data insights and professional data\nvisualizations","metadata":{}},{"cell_type":"markdown","source":"# **About the Company**\n\nIn 2016, Cyclistic launched a successful bike-share offering. Since then, the program has grown to a fleet of 5,824 bicycles that\nare geotracked and locked into a network of 692 stations across Chicago. The bikes can be unlocked from one station and\nreturned to any other station in the system anytime.\nUntil now, Cyclistic’s marketing strategy relied on building general awareness and appealing to broad consumer segments.\nOne approach that helped make these things possible was the flexibility of its pricing plans: single-ride passes, full-day passes,\nand annual memberships. Customers who purchase single-ride or full-day passes are referred to as casual riders. Customers\nwho purchase annual memberships are Cyclistic members.\nCyclistic’s finance analysts have concluded that annual members are much more profitable than casual riders. Although the\npricing flexibility helps Cyclistic attract more customers, Moreno believes that maximizing the number of annual members will\nbe key to future growth. Rather than creating a marketing campaign that targets all-new customers, Moreno believes there is a\nvery good chance to convert casual riders into members. She notes that casual riders are already aware of the Cyclistic\nprogram and have chosen Cyclistic for their mobility needs.\nMoreno has set a clear goal: Design marketing strategies aimed at converting casual riders into annual members. In order to\ndo that, however, the marketing analyst team needs to better understand how annual members and casual riders differ, why\ncasual riders would buy a membership, and how digital media could affect their marketing tactics. Moreno and her team are\ninterested in analyzing the Cyclistic historical bike trip data to identify trends.","metadata":{}},{"cell_type":"markdown","source":"# **Data Analysis Process**\n\n## - **Ask Phase**\n\n* How do annual members and casual riders use Cyclistic bikes differently?\n* Why would casual riders buy Cyclistic annual memberships?\n* How can Cyclistic use digital media to influence casual riders to become members?\n\n### Objective \nAs a member of the marketing analyst team, i have been assigned the first question, \"How do annual members and casual riders use Cyclistic bikes differently?\" and to create a concise report with the following deliverables:\n\n\n* A clear statement of the business task\n* A description of all data sources used\n* Documentation of any cleaning or manipulation of data\n* A summary of your analysis\n* Supporting visualizations and key findings\n* Your top three recommendations based on your analysis","metadata":{}},{"cell_type":"markdown","source":"#### Business Task and Stakeholders\n\nFinance analysts believe that annual members are more profitable to the company than casual riders. Thus, the marketing analytics team is tasked with the responsibility to identify the difference between annual members and casual riders in using Cyclistic bikes and provide recommendations to convert casual riders into annual members.\n\n##### Key Stakeholders\n\n* Lily Moreno: The director of marketing and your manager\n\n* Cyclistic marketing analytics team: A team of data analysts who are responsible for collecting, analyzing, and reporting data that helps guide the Cyclistic marketing strategy\n\n* Cyclistic executive team: The notoriously detail-oriented executive team that will decide whether to approve the recommended marketing program","metadata":{}},{"cell_type":"markdown","source":"***Preparing my work environment***","metadata":{}},{"cell_type":"code","source":"# Loading the required libraries for thorough analysis\n\nlibrary(tidyverse)\nlibrary(ggplot2)\nlibrary(lubridate)\nlibrary(dplyr)\nlibrary(readr)\nlibrary(janitor)\nlibrary(data.table)\nlibrary(tidyr)\nlibrary(geosphere)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:18:17.825271Z","iopub.execute_input":"2022-10-21T04:18:17.826977Z","iopub.status.idle":"2022-10-21T04:18:17.852658Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"markdown","source":"### ***Prepare***\n\n***Data Source***\n\nPrevious 12 months of Cyclistic trip data from November 2021 to October 2022. The data is public and has been made available by Motivate International Inc.\n\n***Data Security***\n\nRiders’ personally identifiable information is protected through encryption.\nA copy of the downloaded files is backed up.\n\n***Data Limitations***\n\nAs riders’ personally identifiable information is prohibited, no pass purchases will be able to connect to credit card numbers to determine if casual riders live in the Cyclistic service area or have purchased multiple single passes\n\n***Data Integrity***\n\nThe data was collected by first party, the fictional company and therefore from a trusted source. The data is free from bias and reflects overall population.\n\nThe data is consistent, provided in comma separated format (CSV) and organized in rows and columns. ","metadata":{}},{"cell_type":"code","source":"# loading the datasets \n\ntrip1 <- read_csv(\"../input/bike-share-dataset/Dec_Trip_Data.csv\")\ntrip2 <- read_csv(\"../input/bike-share-dataset/Nov_Trip_Data.csv\")\ntrip3 <- read_csv(\"../input/bike-share-dataset/Jan_Trip_Data.csv\")\ntrip4 <- read_csv(\"../input/bike-share-dataset/Feb_Trip_Data.csv\")\ntrip5 <- read_csv(\"../input/bike-share-dataset/Mar_Trip_Data.csv\")\ntrip6 <- read_csv(\"../input/bike-share-dataset/Apr_Trip_Data.csv\")\ntrip7 <- read_csv(\"../input/bike-share-dataset/May_Trip_Data.csv\")\ntrip8 <- read_csv(\"../input/bike-share-dataset/Jun_Trip_Data.csv\")\ntrip9 <- read_csv(\"../input/bike-share-dataset/Jul_Trip_Data.csv\")\ntrip10 <- read_csv(\"../input/bike-share-dataset/Aug_Trip_Data.csv\")\ntrip11 <- read_csv(\"../input/bike-share-dataset/Sep_Trip_Data.csv\")\ntrip12 <- read_csv(\"../input/bike-share-dataset/Oct_Trip_Data.csv\")","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:18:17.948708Z","iopub.execute_input":"2022-10-21T04:18:17.950272Z","iopub.status.idle":"2022-10-21T04:18:49.485571Z"},"trusted":true},"execution_count":7,"outputs":[{"name":"stderr","text":"\u001b[1mRows: \u001b[22m\u001b[34m359978\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m631226\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m247540\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m103770\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m115609\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m284042\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m371249\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m634858\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m769204\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m823488\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m785932\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\u001b[1mRows: \u001b[22m\u001b[34m701339\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m13\u001b[39m\n\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n\u001b[1mDelimiter:\u001b[22m \",\"\n\u001b[31mchr\u001b[39m  (7): ride_id, rideable_type, start_station_name, start_station_id, end_...\n\u001b[32mdbl\u001b[39m  (4): start_lat, start_lng, end_lat, end_lng\n\u001b[34mdttm\u001b[39m (2): started_at, ended_at\n\n\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n","output_type":"stream"}]},{"cell_type":"code","source":"# merging the datasets into a single dataframe since they all have the same column names and dataframe structure\n\ndf <- \nrbind(trip1,\n     trip2,\n     trip3,\n     trip4,\n     trip5,\n     trip6,\n     trip7,\n     trip8,\n     trip9,\n     trip10,\n     trip11,\n     trip12)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:18:49.487638Z","iopub.execute_input":"2022-10-21T04:18:49.488855Z","iopub.status.idle":"2022-10-21T04:19:02.764743Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"### **Process**\n\nI have opted for the use of R programming language for the analysis of this case study due to the dataset being enormous. \n\nI will procedd to clean and manipulate my dataset for further analysis","metadata":{}},{"cell_type":"code","source":"# identify how the dataset is organized using functions to preview the dataset\n\nhead(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.767091Z","iopub.execute_input":"2022-10-21T04:19:02.768425Z","iopub.status.idle":"2022-10-21T04:19:02.799626Z"},"trusted":true},"execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 13</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>member_casual</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>7C00A93E10556E47</td><td>electric_bike</td><td>2021-11-27 13:27:38</td><td>2021-11-27 13:46:38</td><td>NA                   </td><td>NA   </td><td>NA</td><td>NA</td><td>41.93000</td><td>-87.72000</td><td>41.96</td><td>-87.73</td><td>casual</td></tr>\n\t<tr><td>90854840DFD508BA</td><td>electric_bike</td><td>2021-11-27 13:38:25</td><td>2021-11-27 13:56:10</td><td>NA                   </td><td>NA   </td><td>NA</td><td>NA</td><td>41.96000</td><td>-87.70000</td><td>41.92</td><td>-87.70</td><td>casual</td></tr>\n\t<tr><td>0A7D10CDD144061C</td><td>electric_bike</td><td>2021-11-26 22:03:34</td><td>2021-11-26 22:05:56</td><td>NA                   </td><td>NA   </td><td>NA</td><td>NA</td><td>41.96000</td><td>-87.70000</td><td>41.96</td><td>-87.70</td><td>casual</td></tr>\n\t<tr><td>2F3BE33085BCFF02</td><td>electric_bike</td><td>2021-11-27 09:56:49</td><td>2021-11-27 10:01:50</td><td>NA                   </td><td>NA   </td><td>NA</td><td>NA</td><td>41.94000</td><td>-87.79000</td><td>41.93</td><td>-87.79</td><td>casual</td></tr>\n\t<tr><td>D67B4781A19928D4</td><td>electric_bike</td><td>2021-11-26 19:09:28</td><td>2021-11-26 19:30:41</td><td>NA                   </td><td>NA   </td><td>NA</td><td>NA</td><td>41.90000</td><td>-87.63000</td><td>41.88</td><td>-87.62</td><td>casual</td></tr>\n\t<tr><td>02F85C2C3C5F7D46</td><td>electric_bike</td><td>2021-11-26 18:34:07</td><td>2021-11-26 18:52:49</td><td>Michigan Ave &amp; Oak St</td><td>13042</td><td>NA</td><td>NA</td><td>41.90086</td><td>-87.62379</td><td>41.90</td><td>-87.63</td><td>casual</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 13\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | member_casual &lt;chr&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| 7C00A93E10556E47 | electric_bike | 2021-11-27 13:27:38 | 2021-11-27 13:46:38 | NA                    | NA    | NA | NA | 41.93000 | -87.72000 | 41.96 | -87.73 | casual |\n| 90854840DFD508BA | electric_bike | 2021-11-27 13:38:25 | 2021-11-27 13:56:10 | NA                    | NA    | NA | NA | 41.96000 | -87.70000 | 41.92 | -87.70 | casual |\n| 0A7D10CDD144061C | electric_bike | 2021-11-26 22:03:34 | 2021-11-26 22:05:56 | NA                    | NA    | NA | NA | 41.96000 | -87.70000 | 41.96 | -87.70 | casual |\n| 2F3BE33085BCFF02 | electric_bike | 2021-11-27 09:56:49 | 2021-11-27 10:01:50 | NA                    | NA    | NA | NA | 41.94000 | -87.79000 | 41.93 | -87.79 | casual |\n| D67B4781A19928D4 | electric_bike | 2021-11-26 19:09:28 | 2021-11-26 19:30:41 | NA                    | NA    | NA | NA | 41.90000 | -87.63000 | 41.88 | -87.62 | casual |\n| 02F85C2C3C5F7D46 | electric_bike | 2021-11-26 18:34:07 | 2021-11-26 18:52:49 | Michigan Ave &amp; Oak St | 13042 | NA | NA | 41.90086 | -87.62379 | 41.90 | -87.63 | casual |\n\n","text/latex":"A tibble: 6 × 13\n\\begin{tabular}{lllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & member\\_casual\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr>\\\\\n\\hline\n\t 7C00A93E10556E47 & electric\\_bike & 2021-11-27 13:27:38 & 2021-11-27 13:46:38 & NA                    & NA    & NA & NA & 41.93000 & -87.72000 & 41.96 & -87.73 & casual\\\\\n\t 90854840DFD508BA & electric\\_bike & 2021-11-27 13:38:25 & 2021-11-27 13:56:10 & NA                    & NA    & NA & NA & 41.96000 & -87.70000 & 41.92 & -87.70 & casual\\\\\n\t 0A7D10CDD144061C & electric\\_bike & 2021-11-26 22:03:34 & 2021-11-26 22:05:56 & NA                    & NA    & NA & NA & 41.96000 & -87.70000 & 41.96 & -87.70 & casual\\\\\n\t 2F3BE33085BCFF02 & electric\\_bike & 2021-11-27 09:56:49 & 2021-11-27 10:01:50 & NA                    & NA    & NA & NA & 41.94000 & -87.79000 & 41.93 & -87.79 & casual\\\\\n\t D67B4781A19928D4 & electric\\_bike & 2021-11-26 19:09:28 & 2021-11-26 19:30:41 & NA                    & NA    & NA & NA & 41.90000 & -87.63000 & 41.88 & -87.62 & casual\\\\\n\t 02F85C2C3C5F7D46 & electric\\_bike & 2021-11-26 18:34:07 & 2021-11-26 18:52:49 & Michigan Ave \\& Oak St & 13042 & NA & NA & 41.90086 & -87.62379 & 41.90 & -87.63 & casual\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 7C00A93E10556E47 electric_bike 2021-11-27 13:27:38 2021-11-27 13:46:38\n2 90854840DFD508BA electric_bike 2021-11-27 13:38:25 2021-11-27 13:56:10\n3 0A7D10CDD144061C electric_bike 2021-11-26 22:03:34 2021-11-26 22:05:56\n4 2F3BE33085BCFF02 electric_bike 2021-11-27 09:56:49 2021-11-27 10:01:50\n5 D67B4781A19928D4 electric_bike 2021-11-26 19:09:28 2021-11-26 19:30:41\n6 02F85C2C3C5F7D46 electric_bike 2021-11-26 18:34:07 2021-11-26 18:52:49\n  start_station_name    start_station_id end_station_name end_station_id\n1 NA                    NA               NA               NA            \n2 NA                    NA               NA               NA            \n3 NA                    NA               NA               NA            \n4 NA                    NA               NA               NA            \n5 NA                    NA               NA               NA            \n6 Michigan Ave & Oak St 13042            NA               NA            \n  start_lat start_lng end_lat end_lng member_casual\n1 41.93000  -87.72000 41.96   -87.73  casual       \n2 41.96000  -87.70000 41.92   -87.70  casual       \n3 41.96000  -87.70000 41.96   -87.70  casual       \n4 41.94000  -87.79000 41.93   -87.79  casual       \n5 41.90000  -87.63000 41.88   -87.62  casual       \n6 41.90086  -87.62379 41.90   -87.63  casual       "},"metadata":{}}]},{"cell_type":"code","source":"tail(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.801812Z","iopub.execute_input":"2022-10-21T04:19:02.803039Z","iopub.status.idle":"2022-10-21T04:19:02.829370Z"},"trusted":true},"execution_count":10,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 13</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>member_casual</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>DC8318F0C749314B</td><td>classic_bike </td><td>2022-09-21 16:16:14</td><td>2022-09-21 16:25:40</td><td><span style=white-space:pre-wrap>Wells St &amp; Hubbard St  </span></td><td>TA1307000151</td><td><span style=white-space:pre-wrap>Wabash Ave &amp; Adams St                              </span></td><td>KA1503000015</td><td>41.88991</td><td>-87.63427</td><td>41.87947</td><td>-87.62569</td><td>member</td></tr>\n\t<tr><td>32ECA2B32C4B6F85</td><td>classic_bike </td><td>2022-09-05 17:59:21</td><td>2022-09-05 18:19:07</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97491</td><td>-87.69250</td><td>41.96522</td><td>-87.65814</td><td>member</td></tr>\n\t<tr><td>14801F713026AEAE</td><td>classic_bike </td><td>2022-09-30 17:20:54</td><td>2022-09-30 17:34:40</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98404</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td></tr>\n\t<tr><td>7CCAF5D6E88E45C0</td><td>electric_bike</td><td>2022-09-04 11:39:37</td><td>2022-09-04 11:50:55</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98411</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td></tr>\n\t<tr><td>AF9A129D9AFAA40B</td><td>electric_bike</td><td>2022-09-28 13:42:45</td><td>2022-09-28 13:52:59</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97492</td><td>-87.69273</td><td>41.96522</td><td>-87.65814</td><td>member</td></tr>\n\t<tr><td>60B56F4897429FCE</td><td>electric_bike</td><td>2022-09-01 20:07:04</td><td>2022-09-01 20:18:01</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97490</td><td>-87.69265</td><td>41.96522</td><td>-87.65814</td><td>member</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 13\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | member_casual &lt;chr&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| DC8318F0C749314B | classic_bike  | 2022-09-21 16:16:14 | 2022-09-21 16:25:40 | Wells St &amp; Hubbard St   | TA1307000151 | Wabash Ave &amp; Adams St                               | KA1503000015 | 41.88991 | -87.63427 | 41.87947 | -87.62569 | member |\n| 32ECA2B32C4B6F85 | classic_bike  | 2022-09-05 17:59:21 | 2022-09-05 18:19:07 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97491 | -87.69250 | 41.96522 | -87.65814 | member |\n| 14801F713026AEAE | classic_bike  | 2022-09-30 17:20:54 | 2022-09-30 17:34:40 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98404 | -87.66027 | 41.96522 | -87.65814 | member |\n| 7CCAF5D6E88E45C0 | electric_bike | 2022-09-04 11:39:37 | 2022-09-04 11:50:55 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98411 | -87.66027 | 41.96522 | -87.65814 | member |\n| AF9A129D9AFAA40B | electric_bike | 2022-09-28 13:42:45 | 2022-09-28 13:52:59 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97492 | -87.69273 | 41.96522 | -87.65814 | member |\n| 60B56F4897429FCE | electric_bike | 2022-09-01 20:07:04 | 2022-09-01 20:18:01 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97490 | -87.69265 | 41.96522 | -87.65814 | member |\n\n","text/latex":"A tibble: 6 × 13\n\\begin{tabular}{lllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & member\\_casual\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr>\\\\\n\\hline\n\t DC8318F0C749314B & classic\\_bike  & 2022-09-21 16:16:14 & 2022-09-21 16:25:40 & Wells St \\& Hubbard St   & TA1307000151 & Wabash Ave \\& Adams St                               & KA1503000015 & 41.88991 & -87.63427 & 41.87947 & -87.62569 & member\\\\\n\t 32ECA2B32C4B6F85 & classic\\_bike  & 2022-09-05 17:59:21 & 2022-09-05 18:19:07 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97491 & -87.69250 & 41.96522 & -87.65814 & member\\\\\n\t 14801F713026AEAE & classic\\_bike  & 2022-09-30 17:20:54 & 2022-09-30 17:34:40 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98404 & -87.66027 & 41.96522 & -87.65814 & member\\\\\n\t 7CCAF5D6E88E45C0 & electric\\_bike & 2022-09-04 11:39:37 & 2022-09-04 11:50:55 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98411 & -87.66027 & 41.96522 & -87.65814 & member\\\\\n\t AF9A129D9AFAA40B & electric\\_bike & 2022-09-28 13:42:45 & 2022-09-28 13:52:59 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97492 & -87.69273 & 41.96522 & -87.65814 & member\\\\\n\t 60B56F4897429FCE & electric\\_bike & 2022-09-01 20:07:04 & 2022-09-01 20:18:01 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97490 & -87.69265 & 41.96522 & -87.65814 & member\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 DC8318F0C749314B classic_bike  2022-09-21 16:16:14 2022-09-21 16:25:40\n2 32ECA2B32C4B6F85 classic_bike  2022-09-05 17:59:21 2022-09-05 18:19:07\n3 14801F713026AEAE classic_bike  2022-09-30 17:20:54 2022-09-30 17:34:40\n4 7CCAF5D6E88E45C0 electric_bike 2022-09-04 11:39:37 2022-09-04 11:50:55\n5 AF9A129D9AFAA40B electric_bike 2022-09-28 13:42:45 2022-09-28 13:52:59\n6 60B56F4897429FCE electric_bike 2022-09-01 20:07:04 2022-09-01 20:18:01\n  start_station_name      start_station_id\n1 Wells St & Hubbard St   TA1307000151    \n2 Lincoln Ave & Winona St KA1504000078    \n3 Broadway & Ridge Ave    15578           \n4 Broadway & Ridge Ave    15578           \n5 Lincoln Ave & Winona St KA1504000078    \n6 Lincoln Ave & Winona St KA1504000078    \n  end_station_name                                    end_station_id start_lat\n1 Wabash Ave & Adams St                               KA1503000015   41.88991 \n2 Broadway & Wilson - Truman College Vaccination Site 13074          41.97491 \n3 Broadway & Wilson - Truman College Vaccination Site 13074          41.98404 \n4 Broadway & Wilson - Truman College Vaccination Site 13074          41.98411 \n5 Broadway & Wilson - Truman College Vaccination Site 13074          41.97492 \n6 Broadway & Wilson - Truman College Vaccination Site 13074          41.97490 \n  start_lng end_lat  end_lng   member_casual\n1 -87.63427 41.87947 -87.62569 member       \n2 -87.69250 41.96522 -87.65814 member       \n3 -87.66027 41.96522 -87.65814 member       \n4 -87.66027 41.96522 -87.65814 member       \n5 -87.69273 41.96522 -87.65814 member       \n6 -87.69265 41.96522 -87.65814 member       "},"metadata":{}}]},{"cell_type":"markdown","source":"It is good practice to know more about our dataframe structure before carrying on with our analysis ","metadata":{}},{"cell_type":"code","source":"glimpse(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.831668Z","iopub.execute_input":"2022-10-21T04:19:02.832934Z","iopub.status.idle":"2022-10-21T04:19:02.860189Z"},"trusted":true},"execution_count":11,"outputs":[{"name":"stdout","text":"Rows: 5,828,235\nColumns: 13\n$ ride_id            \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"7C00A93E10556E47\", \"90854840DFD508BA\", \"0A7D10CDD1…\n$ rideable_type      \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"electric_bike\", \"electric_bike\", \"electric_bike\", …\n$ started_at         \u001b[3m\u001b[90m<dttm>\u001b[39m\u001b[23m 2021-11-27 13:27:38, 2021-11-27 13:38:25, 2021-11-…\n$ ended_at           \u001b[3m\u001b[90m<dttm>\u001b[39m\u001b[23m 2021-11-27 13:46:38, 2021-11-27 13:56:10, 2021-11-…\n$ start_station_name \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m NA, NA, NA, NA, NA, \"Michigan Ave & Oak St\", NA, NA…\n$ start_station_id   \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m NA, NA, NA, NA, NA, \"13042\", NA, NA, NA, NA, NA, NA…\n$ end_station_name   \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…\n$ end_station_id     \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…\n$ start_lat          \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m 41.93000, 41.96000, 41.96000, 41.94000, 41.90000, 4…\n$ start_lng          \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m -87.72000, -87.70000, -87.70000, -87.79000, -87.630…\n$ end_lat            \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m 41.96, 41.92, 41.96, 41.93, 41.88, 41.90, 41.80, 41…\n$ end_lng            \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m -87.73, -87.70, -87.70, -87.79, -87.62, -87.63, -87…\n$ member_casual      \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"casual\", \"casual\", \"casual\", \"casual\", \"casual\", \"…\n","output_type":"stream"}]},{"cell_type":"code","source":"colnames(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.862483Z","iopub.execute_input":"2022-10-21T04:19:02.863772Z","iopub.status.idle":"2022-10-21T04:19:02.882311Z"},"trusted":true},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/html":"<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>'ride_id'</li><li>'rideable_type'</li><li>'started_at'</li><li>'ended_at'</li><li>'start_station_name'</li><li>'start_station_id'</li><li>'end_station_name'</li><li>'end_station_id'</li><li>'start_lat'</li><li>'start_lng'</li><li>'end_lat'</li><li>'end_lng'</li><li>'member_casual'</li></ol>\n","text/markdown":"1. 'ride_id'\n2. 'rideable_type'\n3. 'started_at'\n4. 'ended_at'\n5. 'start_station_name'\n6. 'start_station_id'\n7. 'end_station_name'\n8. 'end_station_id'\n9. 'start_lat'\n10. 'start_lng'\n11. 'end_lat'\n12. 'end_lng'\n13. 'member_casual'\n\n\n","text/latex":"\\begin{enumerate*}\n\\item 'ride\\_id'\n\\item 'rideable\\_type'\n\\item 'started\\_at'\n\\item 'ended\\_at'\n\\item 'start\\_station\\_name'\n\\item 'start\\_station\\_id'\n\\item 'end\\_station\\_name'\n\\item 'end\\_station\\_id'\n\\item 'start\\_lat'\n\\item 'start\\_lng'\n\\item 'end\\_lat'\n\\item 'end\\_lng'\n\\item 'member\\_casual'\n\\end{enumerate*}\n","text/plain":" [1] \"ride_id\"            \"rideable_type\"      \"started_at\"        \n [4] \"ended_at\"           \"start_station_name\" \"start_station_id\"  \n [7] \"end_station_name\"   \"end_station_id\"     \"start_lat\"         \n[10] \"start_lng\"          \"end_lat\"            \"end_lng\"           \n[13] \"member_casual\"     "},"metadata":{}}]},{"cell_type":"code","source":"nrow(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.884662Z","iopub.execute_input":"2022-10-21T04:19:02.886059Z","iopub.status.idle":"2022-10-21T04:19:02.900959Z"},"trusted":true},"execution_count":13,"outputs":[{"output_type":"display_data","data":{"text/html":"5828235","text/markdown":"5828235","text/latex":"5828235","text/plain":"[1] 5828235"},"metadata":{}}]},{"cell_type":"code","source":"dim(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.903449Z","iopub.execute_input":"2022-10-21T04:19:02.904874Z","iopub.status.idle":"2022-10-21T04:19:02.920246Z"},"trusted":true},"execution_count":14,"outputs":[{"output_type":"display_data","data":{"text/html":"<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>5828235</li><li>13</li></ol>\n","text/markdown":"1. 5828235\n2. 13\n\n\n","text/latex":"\\begin{enumerate*}\n\\item 5828235\n\\item 13\n\\end{enumerate*}\n","text/plain":"[1] 5828235      13"},"metadata":{}}]},{"cell_type":"code","source":"summary(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:02.922709Z","iopub.execute_input":"2022-10-21T04:19:02.924148Z","iopub.status.idle":"2022-10-21T04:19:06.210988Z"},"trusted":true},"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/plain":"   ride_id          rideable_type        started_at                 \n Length:5828235     Length:5828235     Min.   :2021-10-01 00:00:09  \n Class :character   Class :character   1st Qu.:2022-02-28 19:21:08  \n Mode  :character   Mode  :character   Median :2022-06-08 06:41:28  \n                                       Mean   :2022-05-06 21:39:18  \n                                       3rd Qu.:2022-08-02 11:26:01  \n                                       Max.   :2022-09-30 23:59:56  \n                                                                    \n    ended_at                   start_station_name start_station_id  \n Min.   :2021-10-01 00:03:11   Length:5828235     Length:5828235    \n 1st Qu.:2022-02-28 19:34:02   Class :character   Class :character  \n Median :2022-06-08 06:55:07   Mode  :character   Mode  :character  \n Mean   :2022-05-06 21:58:54                                        \n 3rd Qu.:2022-08-02 11:46:26                                        \n Max.   :2022-10-05 19:53:11                                        \n                                                                    \n end_station_name   end_station_id       start_lat       start_lng     \n Length:5828235     Length:5828235     Min.   :41.64   Min.   :-87.84  \n Class :character   Class :character   1st Qu.:41.88   1st Qu.:-87.66  \n Mode  :character   Mode  :character   Median :41.90   Median :-87.64  \n                                       Mean   :41.90   Mean   :-87.65  \n                                       3rd Qu.:41.93   3rd Qu.:-87.63  \n                                       Max.   :45.64   Max.   :-73.80  \n                                                                       \n    end_lat         end_lng       member_casual     \n Min.   :41.39   Min.   :-88.97   Length:5828235    \n 1st Qu.:41.88   1st Qu.:-87.66   Class :character  \n Median :41.90   Median :-87.64   Mode  :character  \n Mean   :41.90   Mean   :-87.65                     \n 3rd Qu.:41.93   3rd Qu.:-87.63                     \n Max.   :42.37   Max.   :-87.30                     \n NA's   :5844    NA's   :5844                       "},"metadata":{}}]},{"cell_type":"code","source":"str(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:06.213213Z","iopub.execute_input":"2022-10-21T04:19:06.214467Z","iopub.status.idle":"2022-10-21T04:19:06.254337Z"},"trusted":true},"execution_count":16,"outputs":[{"name":"stdout","text":"spec_tbl_df [5,828,235 × 13] (S3: spec_tbl_df/tbl_df/tbl/data.frame)\n $ ride_id           : chr [1:5828235] \"7C00A93E10556E47\" \"90854840DFD508BA\" \"0A7D10CDD144061C\" \"2F3BE33085BCFF02\" ...\n $ rideable_type     : chr [1:5828235] \"electric_bike\" \"electric_bike\" \"electric_bike\" \"electric_bike\" ...\n $ started_at        : POSIXct[1:5828235], format: \"2021-11-27 13:27:38\" \"2021-11-27 13:38:25\" ...\n $ ended_at          : POSIXct[1:5828235], format: \"2021-11-27 13:46:38\" \"2021-11-27 13:56:10\" ...\n $ start_station_name: chr [1:5828235] NA NA NA NA ...\n $ start_station_id  : chr [1:5828235] NA NA NA NA ...\n $ end_station_name  : chr [1:5828235] NA NA NA NA ...\n $ end_station_id    : chr [1:5828235] NA NA NA NA ...\n $ start_lat         : num [1:5828235] 41.9 42 42 41.9 41.9 ...\n $ start_lng         : num [1:5828235] -87.7 -87.7 -87.7 -87.8 -87.6 ...\n $ end_lat           : num [1:5828235] 42 41.9 42 41.9 41.9 ...\n $ end_lng           : num [1:5828235] -87.7 -87.7 -87.7 -87.8 -87.6 ...\n $ member_casual     : chr [1:5828235] \"casual\" \"casual\" \"casual\" \"casual\" ...\n - attr(*, \"spec\")=\n  .. cols(\n  ..   ride_id = \u001b[31mcol_character()\u001b[39m,\n  ..   rideable_type = \u001b[31mcol_character()\u001b[39m,\n  ..   started_at = \u001b[34mcol_datetime(format = \"\")\u001b[39m,\n  ..   ended_at = \u001b[34mcol_datetime(format = \"\")\u001b[39m,\n  ..   start_station_name = \u001b[31mcol_character()\u001b[39m,\n  ..   start_station_id = \u001b[31mcol_character()\u001b[39m,\n  ..   end_station_name = \u001b[31mcol_character()\u001b[39m,\n  ..   end_station_id = \u001b[31mcol_character()\u001b[39m,\n  ..   start_lat = \u001b[32mcol_double()\u001b[39m,\n  ..   start_lng = \u001b[32mcol_double()\u001b[39m,\n  ..   end_lat = \u001b[32mcol_double()\u001b[39m,\n  ..   end_lng = \u001b[32mcol_double()\u001b[39m,\n  ..   member_casual = \u001b[31mcol_character()\u001b[39m\n  .. )\n - attr(*, \"problems\")=<externalptr> \n","output_type":"stream"}]},{"cell_type":"markdown","source":"#### Data Cleaning\n\nOur dataset appears to have null values which will sorted and filtered","metadata":{}},{"cell_type":"code","source":"is.na(df)\ncolSums(is.na(df))","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:06.256532Z","iopub.execute_input":"2022-10-21T04:19:06.257985Z","iopub.status.idle":"2022-10-21T04:19:10.214768Z"},"trusted":true},"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A matrix: 5828235 × 13 of type lgl</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>member_casual</th></tr>\n</thead>\n<tbody>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>TRUE</td><td>TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA matrix: 5828235 × 13 of type lgl\n\n| ride_id | rideable_type | started_at | ended_at | start_station_name | start_station_id | end_station_name | end_station_id | start_lat | start_lng | end_lat | end_lng | member_casual |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE |  TRUE |  TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n\n","text/latex":"A matrix: 5828235 × 13 of type lgl\n\\begin{tabular}{lllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & member\\_casual\\\\\n\\hline\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & TRUE & TRUE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE &  TRUE &  TRUE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\\end{tabular}\n","text/plain":"      ride_id rideable_type started_at ended_at start_station_name\n [1,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [2,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [3,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [4,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [5,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [6,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [7,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [8,] FALSE   FALSE         FALSE      FALSE     TRUE             \n [9,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[10,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[11,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[12,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[13,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[14,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[15,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[16,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[17,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[18,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[19,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[20,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[21,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[22,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[23,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[24,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[25,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[26,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[27,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[28,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[29,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[30,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[31,] ⋮       ⋮             ⋮          ⋮        ⋮                 \n[32,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[33,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[34,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[35,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[36,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[37,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[38,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[39,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[40,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[41,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[42,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[43,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[44,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[45,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[46,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[47,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[48,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[49,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[50,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[51,] FALSE   FALSE         FALSE      FALSE     TRUE             \n[52,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[53,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[54,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[55,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[56,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[57,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[58,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[59,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[60,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[61,] FALSE   FALSE         FALSE      FALSE    FALSE             \n      start_station_id end_station_name end_station_id start_lat start_lng\n [1,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [2,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [3,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [4,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [5,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [6,] FALSE            TRUE             TRUE           FALSE     FALSE    \n [7,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [8,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n [9,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[10,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[11,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[12,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[13,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[14,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[15,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[16,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[17,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[18,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[19,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[20,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[21,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[22,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[23,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[24,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[25,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[26,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[27,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[28,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[29,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[30,]  TRUE            TRUE             TRUE           FALSE     FALSE    \n[31,] ⋮                ⋮                ⋮              ⋮         ⋮        \n[32,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[33,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[34,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[35,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[36,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[37,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[38,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[39,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[40,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[41,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[42,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[43,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[44,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[45,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[46,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[47,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[48,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[49,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[50,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[51,]  TRUE            FALSE            FALSE          FALSE     FALSE    \n[52,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[53,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[54,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[55,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[56,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[57,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[58,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[59,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[60,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[61,] FALSE            FALSE            FALSE          FALSE     FALSE    \n      end_lat end_lng member_casual\n [1,] FALSE   FALSE   FALSE        \n [2,] FALSE   FALSE   FALSE        \n [3,] FALSE   FALSE   FALSE        \n [4,] FALSE   FALSE   FALSE        \n [5,] FALSE   FALSE   FALSE        \n [6,] FALSE   FALSE   FALSE        \n [7,] FALSE   FALSE   FALSE        \n [8,] FALSE   FALSE   FALSE        \n [9,] FALSE   FALSE   FALSE        \n[10,] FALSE   FALSE   FALSE        \n[11,] FALSE   FALSE   FALSE        \n[12,] FALSE   FALSE   FALSE        \n[13,] FALSE   FALSE   FALSE        \n[14,] FALSE   FALSE   FALSE        \n[15,] FALSE   FALSE   FALSE        \n[16,] FALSE   FALSE   FALSE        \n[17,] FALSE   FALSE   FALSE        \n[18,] FALSE   FALSE   FALSE        \n[19,] FALSE   FALSE   FALSE        \n[20,] FALSE   FALSE   FALSE        \n[21,] FALSE   FALSE   FALSE        \n[22,] FALSE   FALSE   FALSE        \n[23,] FALSE   FALSE   FALSE        \n[24,] FALSE   FALSE   FALSE        \n[25,] FALSE   FALSE   FALSE        \n[26,] FALSE   FALSE   FALSE        \n[27,] FALSE   FALSE   FALSE        \n[28,] FALSE   FALSE   FALSE        \n[29,] FALSE   FALSE   FALSE        \n[30,] FALSE   FALSE   FALSE        \n[31,] ⋮       ⋮       ⋮            \n[32,] FALSE   FALSE   FALSE        \n[33,] FALSE   FALSE   FALSE        \n[34,] FALSE   FALSE   FALSE        \n[35,] FALSE   FALSE   FALSE        \n[36,] FALSE   FALSE   FALSE        \n[37,] FALSE   FALSE   FALSE        \n[38,] FALSE   FALSE   FALSE        \n[39,] FALSE   FALSE   FALSE        \n[40,] FALSE   FALSE   FALSE        \n[41,] FALSE   FALSE   FALSE        \n[42,] FALSE   FALSE   FALSE        \n[43,] FALSE   FALSE   FALSE        \n[44,] FALSE   FALSE   FALSE        \n[45,] FALSE   FALSE   FALSE        \n[46,] FALSE   FALSE   FALSE        \n[47,] FALSE   FALSE   FALSE        \n[48,] FALSE   FALSE   FALSE        \n[49,] FALSE   FALSE   FALSE        \n[50,] FALSE   FALSE   FALSE        \n[51,] FALSE   FALSE   FALSE        \n[52,] FALSE   FALSE   FALSE        \n[53,] FALSE   FALSE   FALSE        \n[54,] FALSE   FALSE   FALSE        \n[55,] FALSE   FALSE   FALSE        \n[56,] FALSE   FALSE   FALSE        \n[57,] FALSE   FALSE   FALSE        \n[58,] FALSE   FALSE   FALSE        \n[59,] FALSE   FALSE   FALSE        \n[60,] FALSE   FALSE   FALSE        \n[61,] FALSE   FALSE   FALSE        "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<style>\n.dl-inline {width: auto; margin:0; padding: 0}\n.dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n.dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n.dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n</style><dl class=dl-inline><dt>ride_id</dt><dd>0</dd><dt>rideable_type</dt><dd>0</dd><dt>started_at</dt><dd>0</dd><dt>ended_at</dt><dd>0</dd><dt>start_station_name</dt><dd>895032</dd><dt>start_station_id</dt><dd>895032</dd><dt>end_station_name</dt><dd>958227</dd><dt>end_station_id</dt><dd>958227</dd><dt>start_lat</dt><dd>0</dd><dt>start_lng</dt><dd>0</dd><dt>end_lat</dt><dd>5844</dd><dt>end_lng</dt><dd>5844</dd><dt>member_casual</dt><dd>0</dd></dl>\n","text/markdown":"ride_id\n:   0rideable_type\n:   0started_at\n:   0ended_at\n:   0start_station_name\n:   895032start_station_id\n:   895032end_station_name\n:   958227end_station_id\n:   958227start_lat\n:   0start_lng\n:   0end_lat\n:   5844end_lng\n:   5844member_casual\n:   0\n\n","text/latex":"\\begin{description*}\n\\item[ride\\textbackslash{}\\_id] 0\n\\item[rideable\\textbackslash{}\\_type] 0\n\\item[started\\textbackslash{}\\_at] 0\n\\item[ended\\textbackslash{}\\_at] 0\n\\item[start\\textbackslash{}\\_station\\textbackslash{}\\_name] 895032\n\\item[start\\textbackslash{}\\_station\\textbackslash{}\\_id] 895032\n\\item[end\\textbackslash{}\\_station\\textbackslash{}\\_name] 958227\n\\item[end\\textbackslash{}\\_station\\textbackslash{}\\_id] 958227\n\\item[start\\textbackslash{}\\_lat] 0\n\\item[start\\textbackslash{}\\_lng] 0\n\\item[end\\textbackslash{}\\_lat] 5844\n\\item[end\\textbackslash{}\\_lng] 5844\n\\item[member\\textbackslash{}\\_casual] 0\n\\end{description*}\n","text/plain":"           ride_id      rideable_type         started_at           ended_at \n                 0                  0                  0                  0 \nstart_station_name   start_station_id   end_station_name     end_station_id \n            895032             895032             958227             958227 \n         start_lat          start_lng            end_lat            end_lng \n                 0                  0               5844               5844 \n     member_casual \n                 0 "},"metadata":{}}]},{"cell_type":"code","source":"df <- df[rowSums(is.na(df)) == 0, ]","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:10.218095Z","iopub.execute_input":"2022-10-21T04:19:10.219599Z","iopub.status.idle":"2022-10-21T04:19:12.281319Z"},"trusted":true},"execution_count":18,"outputs":[]},{"cell_type":"code","source":"is.na(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:12.283565Z","iopub.execute_input":"2022-10-21T04:19:12.284862Z","iopub.status.idle":"2022-10-21T04:19:15.283160Z"},"trusted":true},"execution_count":19,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A matrix: 4474141 × 13 of type lgl</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>member_casual</th></tr>\n</thead>\n<tbody>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n\t<tr><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>FALSE</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA matrix: 4474141 × 13 of type lgl\n\n| ride_id | rideable_type | started_at | ended_at | start_station_name | start_station_id | end_station_name | end_station_id | start_lat | start_lng | end_lat | end_lng | member_casual |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n| FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE |\n\n","text/latex":"A matrix: 4474141 × 13 of type lgl\n\\begin{tabular}{lllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & member\\_casual\\\\\n\\hline\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\t FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE & FALSE\\\\\n\\end{tabular}\n","text/plain":"      ride_id rideable_type started_at ended_at start_station_name\n [1,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [2,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [3,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [4,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [5,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [6,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [7,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [8,] FALSE   FALSE         FALSE      FALSE    FALSE             \n [9,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[10,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[11,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[12,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[13,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[14,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[15,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[16,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[17,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[18,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[19,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[20,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[21,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[22,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[23,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[24,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[25,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[26,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[27,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[28,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[29,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[30,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[31,] ⋮       ⋮             ⋮          ⋮        ⋮                 \n[32,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[33,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[34,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[35,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[36,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[37,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[38,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[39,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[40,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[41,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[42,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[43,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[44,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[45,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[46,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[47,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[48,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[49,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[50,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[51,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[52,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[53,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[54,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[55,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[56,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[57,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[58,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[59,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[60,] FALSE   FALSE         FALSE      FALSE    FALSE             \n[61,] FALSE   FALSE         FALSE      FALSE    FALSE             \n      start_station_id end_station_name end_station_id start_lat start_lng\n [1,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [2,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [3,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [4,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [5,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [6,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [7,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [8,] FALSE            FALSE            FALSE          FALSE     FALSE    \n [9,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[10,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[11,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[12,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[13,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[14,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[15,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[16,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[17,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[18,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[19,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[20,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[21,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[22,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[23,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[24,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[25,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[26,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[27,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[28,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[29,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[30,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[31,] ⋮                ⋮                ⋮              ⋮         ⋮        \n[32,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[33,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[34,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[35,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[36,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[37,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[38,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[39,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[40,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[41,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[42,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[43,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[44,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[45,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[46,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[47,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[48,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[49,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[50,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[51,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[52,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[53,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[54,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[55,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[56,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[57,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[58,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[59,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[60,] FALSE            FALSE            FALSE          FALSE     FALSE    \n[61,] FALSE            FALSE            FALSE          FALSE     FALSE    \n      end_lat end_lng member_casual\n [1,] FALSE   FALSE   FALSE        \n [2,] FALSE   FALSE   FALSE        \n [3,] FALSE   FALSE   FALSE        \n [4,] FALSE   FALSE   FALSE        \n [5,] FALSE   FALSE   FALSE        \n [6,] FALSE   FALSE   FALSE        \n [7,] FALSE   FALSE   FALSE        \n [8,] FALSE   FALSE   FALSE        \n [9,] FALSE   FALSE   FALSE        \n[10,] FALSE   FALSE   FALSE        \n[11,] FALSE   FALSE   FALSE        \n[12,] FALSE   FALSE   FALSE        \n[13,] FALSE   FALSE   FALSE        \n[14,] FALSE   FALSE   FALSE        \n[15,] FALSE   FALSE   FALSE        \n[16,] FALSE   FALSE   FALSE        \n[17,] FALSE   FALSE   FALSE        \n[18,] FALSE   FALSE   FALSE        \n[19,] FALSE   FALSE   FALSE        \n[20,] FALSE   FALSE   FALSE        \n[21,] FALSE   FALSE   FALSE        \n[22,] FALSE   FALSE   FALSE        \n[23,] FALSE   FALSE   FALSE        \n[24,] FALSE   FALSE   FALSE        \n[25,] FALSE   FALSE   FALSE        \n[26,] FALSE   FALSE   FALSE        \n[27,] FALSE   FALSE   FALSE        \n[28,] FALSE   FALSE   FALSE        \n[29,] FALSE   FALSE   FALSE        \n[30,] FALSE   FALSE   FALSE        \n[31,] ⋮       ⋮       ⋮            \n[32,] FALSE   FALSE   FALSE        \n[33,] FALSE   FALSE   FALSE        \n[34,] FALSE   FALSE   FALSE        \n[35,] FALSE   FALSE   FALSE        \n[36,] FALSE   FALSE   FALSE        \n[37,] FALSE   FALSE   FALSE        \n[38,] FALSE   FALSE   FALSE        \n[39,] FALSE   FALSE   FALSE        \n[40,] FALSE   FALSE   FALSE        \n[41,] FALSE   FALSE   FALSE        \n[42,] FALSE   FALSE   FALSE        \n[43,] FALSE   FALSE   FALSE        \n[44,] FALSE   FALSE   FALSE        \n[45,] FALSE   FALSE   FALSE        \n[46,] FALSE   FALSE   FALSE        \n[47,] FALSE   FALSE   FALSE        \n[48,] FALSE   FALSE   FALSE        \n[49,] FALSE   FALSE   FALSE        \n[50,] FALSE   FALSE   FALSE        \n[51,] FALSE   FALSE   FALSE        \n[52,] FALSE   FALSE   FALSE        \n[53,] FALSE   FALSE   FALSE        \n[54,] FALSE   FALSE   FALSE        \n[55,] FALSE   FALSE   FALSE        \n[56,] FALSE   FALSE   FALSE        \n[57,] FALSE   FALSE   FALSE        \n[58,] FALSE   FALSE   FALSE        \n[59,] FALSE   FALSE   FALSE        \n[60,] FALSE   FALSE   FALSE        \n[61,] FALSE   FALSE   FALSE        "},"metadata":{}}]},{"cell_type":"code","source":"glimpse(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:15.286753Z","iopub.execute_input":"2022-10-21T04:19:15.288251Z","iopub.status.idle":"2022-10-21T04:19:15.308694Z"},"trusted":true},"execution_count":20,"outputs":[{"name":"stdout","text":"Rows: 4,474,141\nColumns: 13\n$ ride_id            \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"4CA9676997DAFFF6\", \"F3E84A230AF2D676\", \"A1F2C92308…\n$ rideable_type      \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"classic_bike\", \"classic_bike\", \"electric_bike\", \"c…\n$ started_at         \u001b[3m\u001b[90m<dttm>\u001b[39m\u001b[23m 2021-11-26 10:27:28, 2021-11-15 09:35:03, 2021-11-…\n$ ended_at           \u001b[3m\u001b[90m<dttm>\u001b[39m\u001b[23m 2021-11-26 11:22:13, 2021-11-15 09:42:08, 2021-11-…\n$ start_station_name \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"Michigan Ave & Oak St\", \"Clark St & Grace St\", \"Le…\n$ start_station_id   \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"13042\", \"TA1307000127\", \"307\", \"TA1306000003\", \"TA…\n$ end_station_name   \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"Michigan Ave & Oak St\", \"Clark St & Leland Ave\", \"…\n$ end_station_id     \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"13042\", \"TA1309000014\", \"307\", \"TA1306000003\", \"13…\n$ start_lat          \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m 41.90096, 41.95078, 41.91000, 41.88872, 41.91808, 4…\n$ start_lng          \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m -87.62378, -87.65917, -87.75000, -87.64445, -87.643…\n$ end_lat            \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m 41.90096, 41.96710, 41.91000, 41.88872, 41.90096, 4…\n$ end_lng            \u001b[3m\u001b[90m<dbl>\u001b[39m\u001b[23m -87.62378, -87.66743, -87.75000, -87.64445, -87.623…\n$ member_casual      \u001b[3m\u001b[90m<chr>\u001b[39m\u001b[23m \"casual\", \"casual\", \"casual\", \"casual\", \"casual\", \"…\n","output_type":"stream"}]},{"cell_type":"markdown","source":"Null values have been excommunicated and will thus proceed to Data Manipulation for ease of analysis","metadata":{}},{"cell_type":"markdown","source":"#### Data Manipulation\n\n","metadata":{}},{"cell_type":"code","source":"# create new column \"ride_distance\" which calculates the ride distances\ndf <- df %>% \nmutate(ride_distance = distHaversine(cbind(start_lng, start_lat), cbind(end_lng, end_lat)))\nhead(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:15.310903Z","iopub.execute_input":"2022-10-21T04:19:15.312184Z","iopub.status.idle":"2022-10-21T04:19:18.265129Z"},"trusted":true},"execution_count":21,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 14</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>member_casual</th><th scope=col>ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>4CA9676997DAFFF6</td><td>classic_bike </td><td>2021-11-26 10:27:28</td><td>2021-11-26 11:22:13</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90096</td><td>-87.62378</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St       </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave     </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.64307</td></tr>\n\t<tr><td>A1F2C92308007968</td><td>electric_bike</td><td>2021-11-10 16:27:02</td><td>2021-11-10 17:04:28</td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>41.91000</td><td>-87.75000</td><td>41.91000</td><td>-87.75000</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>9B871C3B14E9BEC4</td><td>classic_bike </td><td>2021-11-09 19:51:36</td><td>2021-11-09 20:11:17</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>41.88872</td><td>-87.64445</td><td>41.88872</td><td>-87.64445</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave</td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.13085</td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.67405</span></td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 14\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | member_casual &lt;chr&gt; | ride_distance &lt;dbl&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| 4CA9676997DAFFF6 | classic_bike  | 2021-11-26 10:27:28 | 2021-11-26 11:22:13 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90096 | -87.62378 | 41.90096 | -87.62378 | casual |    0.00000 |\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St        | TA1307000127 | Clark St &amp; Leland Ave      | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.64307 |\n| A1F2C92308007968 | electric_bike | 2021-11-10 16:27:02 | 2021-11-10 17:04:28 | Leamington Ave &amp; Hirsch St | 307          | Leamington Ave &amp; Hirsch St | 307          | 41.91000 | -87.75000 | 41.91000 | -87.75000 | casual |    0.00000 |\n| 9B871C3B14E9BEC4 | classic_bike  | 2021-11-09 19:51:36 | 2021-11-09 20:11:17 | Desplaines St &amp; Kinzie St  | TA1306000003 | Desplaines St &amp; Kinzie St  | TA1306000003 | 41.88872 | -87.64445 | 41.88872 | -87.64445 | casual |    0.00000 |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave | TA1309000006 | Michigan Ave &amp; Oak St      | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.13085 |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.67405 |\n\n","text/latex":"A tibble: 6 × 14\n\\begin{tabular}{llllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & member\\_casual & ride\\_distance\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl>\\\\\n\\hline\n\t 4CA9676997DAFFF6 & classic\\_bike  & 2021-11-26 10:27:28 & 2021-11-26 11:22:13 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90096 & -87.62378 & 41.90096 & -87.62378 & casual &    0.00000\\\\\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St        & TA1307000127 & Clark St \\& Leland Ave      & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.64307\\\\\n\t A1F2C92308007968 & electric\\_bike & 2021-11-10 16:27:02 & 2021-11-10 17:04:28 & Leamington Ave \\& Hirsch St & 307          & Leamington Ave \\& Hirsch St & 307          & 41.91000 & -87.75000 & 41.91000 & -87.75000 & casual &    0.00000\\\\\n\t 9B871C3B14E9BEC4 & classic\\_bike  & 2021-11-09 19:51:36 & 2021-11-09 20:11:17 & Desplaines St \\& Kinzie St  & TA1306000003 & Desplaines St \\& Kinzie St  & TA1306000003 & 41.88872 & -87.64445 & 41.88872 & -87.64445 & casual &    0.00000\\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave & TA1309000006 & Michigan Ave \\& Oak St      & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.13085\\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.67405\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 4CA9676997DAFFF6 classic_bike  2021-11-26 10:27:28 2021-11-26 11:22:13\n2 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n3 A1F2C92308007968 electric_bike 2021-11-10 16:27:02 2021-11-10 17:04:28\n4 9B871C3B14E9BEC4 classic_bike  2021-11-09 19:51:36 2021-11-09 20:11:17\n5 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n6 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n  start_station_name         start_station_id end_station_name          \n1 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n2 Clark St & Grace St        TA1307000127     Clark St & Leland Ave     \n3 Leamington Ave & Hirsch St 307              Leamington Ave & Hirsch St\n4 Desplaines St & Kinzie St  TA1306000003     Desplaines St & Kinzie St \n5 Larrabee St & Armitage Ave TA1309000006     Michigan Ave & Oak St     \n6 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n  end_station_id start_lat start_lng end_lat  end_lng   member_casual\n1 13042          41.90096  -87.62378 41.90096 -87.62378 casual       \n2 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual       \n3 307            41.91000  -87.75000 41.91000 -87.75000 casual       \n4 TA1306000003   41.88872  -87.64445 41.88872 -87.64445 casual       \n5 13042          41.91808  -87.64375 41.90096 -87.62378 casual       \n6 13042          41.90114  -87.62353 41.90100 -87.62375 casual       \n  ride_distance\n1    0.00000   \n2 1940.64307   \n3    0.00000   \n4    0.00000   \n5 2524.13085   \n6   23.67405   "},"metadata":{}}]},{"cell_type":"code","source":"# Change column names from \"member_casual\" to \"usertype\"\n\ndf <- df %>% \nrename(usertype = member_casual)\ncolnames(df)\ntable(df$usertype)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:18.267378Z","iopub.execute_input":"2022-10-21T04:19:18.268621Z","iopub.status.idle":"2022-10-21T04:19:18.654515Z"},"trusted":true},"execution_count":22,"outputs":[{"output_type":"display_data","data":{"text/html":"<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>'ride_id'</li><li>'rideable_type'</li><li>'started_at'</li><li>'ended_at'</li><li>'start_station_name'</li><li>'start_station_id'</li><li>'end_station_name'</li><li>'end_station_id'</li><li>'start_lat'</li><li>'start_lng'</li><li>'end_lat'</li><li>'end_lng'</li><li>'usertype'</li><li>'ride_distance'</li></ol>\n","text/markdown":"1. 'ride_id'\n2. 'rideable_type'\n3. 'started_at'\n4. 'ended_at'\n5. 'start_station_name'\n6. 'start_station_id'\n7. 'end_station_name'\n8. 'end_station_id'\n9. 'start_lat'\n10. 'start_lng'\n11. 'end_lat'\n12. 'end_lng'\n13. 'usertype'\n14. 'ride_distance'\n\n\n","text/latex":"\\begin{enumerate*}\n\\item 'ride\\_id'\n\\item 'rideable\\_type'\n\\item 'started\\_at'\n\\item 'ended\\_at'\n\\item 'start\\_station\\_name'\n\\item 'start\\_station\\_id'\n\\item 'end\\_station\\_name'\n\\item 'end\\_station\\_id'\n\\item 'start\\_lat'\n\\item 'start\\_lng'\n\\item 'end\\_lat'\n\\item 'end\\_lng'\n\\item 'usertype'\n\\item 'ride\\_distance'\n\\end{enumerate*}\n","text/plain":" [1] \"ride_id\"            \"rideable_type\"      \"started_at\"        \n [4] \"ended_at\"           \"start_station_name\" \"start_station_id\"  \n [7] \"end_station_name\"   \"end_station_id\"     \"start_lat\"         \n[10] \"start_lng\"          \"end_lat\"            \"end_lng\"           \n[13] \"usertype\"           \"ride_distance\"     "},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n casual  member \n1805975 2668166 "},"metadata":{}}]},{"cell_type":"code","source":"head(df)\ntail(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:18.656800Z","iopub.execute_input":"2022-10-21T04:19:18.658106Z","iopub.status.idle":"2022-10-21T04:19:18.704185Z"},"trusted":true},"execution_count":23,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 14</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>4CA9676997DAFFF6</td><td>classic_bike </td><td>2021-11-26 10:27:28</td><td>2021-11-26 11:22:13</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90096</td><td>-87.62378</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St       </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave     </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.64307</td></tr>\n\t<tr><td>A1F2C92308007968</td><td>electric_bike</td><td>2021-11-10 16:27:02</td><td>2021-11-10 17:04:28</td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>41.91000</td><td>-87.75000</td><td>41.91000</td><td>-87.75000</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>9B871C3B14E9BEC4</td><td>classic_bike </td><td>2021-11-09 19:51:36</td><td>2021-11-09 20:11:17</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>41.88872</td><td>-87.64445</td><td>41.88872</td><td>-87.64445</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave</td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.13085</td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.67405</span></td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 14\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| 4CA9676997DAFFF6 | classic_bike  | 2021-11-26 10:27:28 | 2021-11-26 11:22:13 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90096 | -87.62378 | 41.90096 | -87.62378 | casual |    0.00000 |\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St        | TA1307000127 | Clark St &amp; Leland Ave      | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.64307 |\n| A1F2C92308007968 | electric_bike | 2021-11-10 16:27:02 | 2021-11-10 17:04:28 | Leamington Ave &amp; Hirsch St | 307          | Leamington Ave &amp; Hirsch St | 307          | 41.91000 | -87.75000 | 41.91000 | -87.75000 | casual |    0.00000 |\n| 9B871C3B14E9BEC4 | classic_bike  | 2021-11-09 19:51:36 | 2021-11-09 20:11:17 | Desplaines St &amp; Kinzie St  | TA1306000003 | Desplaines St &amp; Kinzie St  | TA1306000003 | 41.88872 | -87.64445 | 41.88872 | -87.64445 | casual |    0.00000 |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave | TA1309000006 | Michigan Ave &amp; Oak St      | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.13085 |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.67405 |\n\n","text/latex":"A tibble: 6 × 14\n\\begin{tabular}{llllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl>\\\\\n\\hline\n\t 4CA9676997DAFFF6 & classic\\_bike  & 2021-11-26 10:27:28 & 2021-11-26 11:22:13 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90096 & -87.62378 & 41.90096 & -87.62378 & casual &    0.00000\\\\\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St        & TA1307000127 & Clark St \\& Leland Ave      & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.64307\\\\\n\t A1F2C92308007968 & electric\\_bike & 2021-11-10 16:27:02 & 2021-11-10 17:04:28 & Leamington Ave \\& Hirsch St & 307          & Leamington Ave \\& Hirsch St & 307          & 41.91000 & -87.75000 & 41.91000 & -87.75000 & casual &    0.00000\\\\\n\t 9B871C3B14E9BEC4 & classic\\_bike  & 2021-11-09 19:51:36 & 2021-11-09 20:11:17 & Desplaines St \\& Kinzie St  & TA1306000003 & Desplaines St \\& Kinzie St  & TA1306000003 & 41.88872 & -87.64445 & 41.88872 & -87.64445 & casual &    0.00000\\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave & TA1309000006 & Michigan Ave \\& Oak St      & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.13085\\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.67405\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 4CA9676997DAFFF6 classic_bike  2021-11-26 10:27:28 2021-11-26 11:22:13\n2 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n3 A1F2C92308007968 electric_bike 2021-11-10 16:27:02 2021-11-10 17:04:28\n4 9B871C3B14E9BEC4 classic_bike  2021-11-09 19:51:36 2021-11-09 20:11:17\n5 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n6 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n  start_station_name         start_station_id end_station_name          \n1 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n2 Clark St & Grace St        TA1307000127     Clark St & Leland Ave     \n3 Leamington Ave & Hirsch St 307              Leamington Ave & Hirsch St\n4 Desplaines St & Kinzie St  TA1306000003     Desplaines St & Kinzie St \n5 Larrabee St & Armitage Ave TA1309000006     Michigan Ave & Oak St     \n6 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n  end_station_id start_lat start_lng end_lat  end_lng   usertype ride_distance\n1 13042          41.90096  -87.62378 41.90096 -87.62378 casual      0.00000   \n2 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual   1940.64307   \n3 307            41.91000  -87.75000 41.91000 -87.75000 casual      0.00000   \n4 TA1306000003   41.88872  -87.64445 41.88872 -87.64445 casual      0.00000   \n5 13042          41.91808  -87.64375 41.90096 -87.62378 casual   2524.13085   \n6 13042          41.90114  -87.62353 41.90100 -87.62375 casual     23.67405   "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 14</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>DC8318F0C749314B</td><td>classic_bike </td><td>2022-09-21 16:16:14</td><td>2022-09-21 16:25:40</td><td><span style=white-space:pre-wrap>Wells St &amp; Hubbard St  </span></td><td>TA1307000151</td><td><span style=white-space:pre-wrap>Wabash Ave &amp; Adams St                              </span></td><td>KA1503000015</td><td>41.88991</td><td>-87.63427</td><td>41.87947</td><td>-87.62569</td><td>member</td><td>1361.739</td></tr>\n\t<tr><td>32ECA2B32C4B6F85</td><td>classic_bike </td><td>2022-09-05 17:59:21</td><td>2022-09-05 18:19:07</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97491</td><td>-87.69250</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3041.812</td></tr>\n\t<tr><td>14801F713026AEAE</td><td>classic_bike </td><td>2022-09-30 17:20:54</td><td>2022-09-30 17:34:40</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98404</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>2102.870</td></tr>\n\t<tr><td>7CCAF5D6E88E45C0</td><td>electric_bike</td><td>2022-09-04 11:39:37</td><td>2022-09-04 11:50:55</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98411</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>2110.338</td></tr>\n\t<tr><td>AF9A129D9AFAA40B</td><td>electric_bike</td><td>2022-09-28 13:42:45</td><td>2022-09-28 13:52:59</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97492</td><td>-87.69273</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3060.162</td></tr>\n\t<tr><td>60B56F4897429FCE</td><td>electric_bike</td><td>2022-09-01 20:07:04</td><td>2022-09-01 20:18:01</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97490</td><td>-87.69265</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3052.878</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 14\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| DC8318F0C749314B | classic_bike  | 2022-09-21 16:16:14 | 2022-09-21 16:25:40 | Wells St &amp; Hubbard St   | TA1307000151 | Wabash Ave &amp; Adams St                               | KA1503000015 | 41.88991 | -87.63427 | 41.87947 | -87.62569 | member | 1361.739 |\n| 32ECA2B32C4B6F85 | classic_bike  | 2022-09-05 17:59:21 | 2022-09-05 18:19:07 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97491 | -87.69250 | 41.96522 | -87.65814 | member | 3041.812 |\n| 14801F713026AEAE | classic_bike  | 2022-09-30 17:20:54 | 2022-09-30 17:34:40 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98404 | -87.66027 | 41.96522 | -87.65814 | member | 2102.870 |\n| 7CCAF5D6E88E45C0 | electric_bike | 2022-09-04 11:39:37 | 2022-09-04 11:50:55 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98411 | -87.66027 | 41.96522 | -87.65814 | member | 2110.338 |\n| AF9A129D9AFAA40B | electric_bike | 2022-09-28 13:42:45 | 2022-09-28 13:52:59 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97492 | -87.69273 | 41.96522 | -87.65814 | member | 3060.162 |\n| 60B56F4897429FCE | electric_bike | 2022-09-01 20:07:04 | 2022-09-01 20:18:01 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97490 | -87.69265 | 41.96522 | -87.65814 | member | 3052.878 |\n\n","text/latex":"A tibble: 6 × 14\n\\begin{tabular}{llllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl>\\\\\n\\hline\n\t DC8318F0C749314B & classic\\_bike  & 2022-09-21 16:16:14 & 2022-09-21 16:25:40 & Wells St \\& Hubbard St   & TA1307000151 & Wabash Ave \\& Adams St                               & KA1503000015 & 41.88991 & -87.63427 & 41.87947 & -87.62569 & member & 1361.739\\\\\n\t 32ECA2B32C4B6F85 & classic\\_bike  & 2022-09-05 17:59:21 & 2022-09-05 18:19:07 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97491 & -87.69250 & 41.96522 & -87.65814 & member & 3041.812\\\\\n\t 14801F713026AEAE & classic\\_bike  & 2022-09-30 17:20:54 & 2022-09-30 17:34:40 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98404 & -87.66027 & 41.96522 & -87.65814 & member & 2102.870\\\\\n\t 7CCAF5D6E88E45C0 & electric\\_bike & 2022-09-04 11:39:37 & 2022-09-04 11:50:55 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98411 & -87.66027 & 41.96522 & -87.65814 & member & 2110.338\\\\\n\t AF9A129D9AFAA40B & electric\\_bike & 2022-09-28 13:42:45 & 2022-09-28 13:52:59 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97492 & -87.69273 & 41.96522 & -87.65814 & member & 3060.162\\\\\n\t 60B56F4897429FCE & electric\\_bike & 2022-09-01 20:07:04 & 2022-09-01 20:18:01 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97490 & -87.69265 & 41.96522 & -87.65814 & member & 3052.878\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 DC8318F0C749314B classic_bike  2022-09-21 16:16:14 2022-09-21 16:25:40\n2 32ECA2B32C4B6F85 classic_bike  2022-09-05 17:59:21 2022-09-05 18:19:07\n3 14801F713026AEAE classic_bike  2022-09-30 17:20:54 2022-09-30 17:34:40\n4 7CCAF5D6E88E45C0 electric_bike 2022-09-04 11:39:37 2022-09-04 11:50:55\n5 AF9A129D9AFAA40B electric_bike 2022-09-28 13:42:45 2022-09-28 13:52:59\n6 60B56F4897429FCE electric_bike 2022-09-01 20:07:04 2022-09-01 20:18:01\n  start_station_name      start_station_id\n1 Wells St & Hubbard St   TA1307000151    \n2 Lincoln Ave & Winona St KA1504000078    \n3 Broadway & Ridge Ave    15578           \n4 Broadway & Ridge Ave    15578           \n5 Lincoln Ave & Winona St KA1504000078    \n6 Lincoln Ave & Winona St KA1504000078    \n  end_station_name                                    end_station_id start_lat\n1 Wabash Ave & Adams St                               KA1503000015   41.88991 \n2 Broadway & Wilson - Truman College Vaccination Site 13074          41.97491 \n3 Broadway & Wilson - Truman College Vaccination Site 13074          41.98404 \n4 Broadway & Wilson - Truman College Vaccination Site 13074          41.98411 \n5 Broadway & Wilson - Truman College Vaccination Site 13074          41.97492 \n6 Broadway & Wilson - Truman College Vaccination Site 13074          41.97490 \n  start_lng end_lat  end_lng   usertype ride_distance\n1 -87.63427 41.87947 -87.62569 member   1361.739     \n2 -87.69250 41.96522 -87.65814 member   3041.812     \n3 -87.66027 41.96522 -87.65814 member   2102.870     \n4 -87.66027 41.96522 -87.65814 member   2110.338     \n5 -87.69273 41.96522 -87.65814 member   3060.162     \n6 -87.69265 41.96522 -87.65814 member   3052.878     "},"metadata":{}}]},{"cell_type":"code","source":"dim(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:18.707527Z","iopub.execute_input":"2022-10-21T04:19:18.708957Z","iopub.status.idle":"2022-10-21T04:19:18.725113Z"},"trusted":true},"execution_count":24,"outputs":[{"output_type":"display_data","data":{"text/html":"<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>4474141</li><li>14</li></ol>\n","text/markdown":"1. 4474141\n2. 14\n\n\n","text/latex":"\\begin{enumerate*}\n\\item 4474141\n\\item 14\n\\end{enumerate*}\n","text/plain":"[1] 4474141      14"},"metadata":{}}]},{"cell_type":"code","source":"# aggregate ride data for each month, day, or year and create new column \"day_of_week\"\ndf$date <- as.Date(df$started_at)\ndf$month <- format(as.Date(df$date), \"%m\")\ndf$day <- format(as.Date(df$date), \"%d\")\ndf$year <- format(as.Date(df$date), \"%Y\")\ndf$day_of_week <- format(as.Date(df$date), \"%A\")\nhead(df)\ntail(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:18.728422Z","iopub.execute_input":"2022-10-21T04:19:18.729798Z","iopub.status.idle":"2022-10-21T04:19:26.123116Z"},"trusted":true},"execution_count":25,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 19</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th><th scope=col>date</th><th scope=col>month</th><th scope=col>day</th><th scope=col>year</th><th scope=col>day_of_week</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;date&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>4CA9676997DAFFF6</td><td>classic_bike </td><td>2021-11-26 10:27:28</td><td>2021-11-26 11:22:13</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90096</td><td>-87.62378</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-26</td><td>11</td><td>26</td><td>2021</td><td><span style=white-space:pre-wrap>Friday   </span></td></tr>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St       </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave     </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.64307</td><td>2021-11-15</td><td>11</td><td>15</td><td>2021</td><td><span style=white-space:pre-wrap>Monday   </span></td></tr>\n\t<tr><td>A1F2C92308007968</td><td>electric_bike</td><td>2021-11-10 16:27:02</td><td>2021-11-10 17:04:28</td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>41.91000</td><td>-87.75000</td><td>41.91000</td><td>-87.75000</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-10</td><td>11</td><td>10</td><td>2021</td><td>Wednesday</td></tr>\n\t<tr><td>9B871C3B14E9BEC4</td><td>classic_bike </td><td>2021-11-09 19:51:36</td><td>2021-11-09 20:11:17</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>41.88872</td><td>-87.64445</td><td>41.88872</td><td>-87.64445</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-09</td><td>11</td><td>09</td><td>2021</td><td><span style=white-space:pre-wrap>Tuesday  </span></td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave</td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.13085</td><td>2021-11-06</td><td>11</td><td>06</td><td>2021</td><td>Saturday </td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.67405</span></td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday </td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 19\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; | date &lt;date&gt; | month &lt;chr&gt; | day &lt;chr&gt; | year &lt;chr&gt; | day_of_week &lt;chr&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| 4CA9676997DAFFF6 | classic_bike  | 2021-11-26 10:27:28 | 2021-11-26 11:22:13 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90096 | -87.62378 | 41.90096 | -87.62378 | casual |    0.00000 | 2021-11-26 | 11 | 26 | 2021 | Friday    |\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St        | TA1307000127 | Clark St &amp; Leland Ave      | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.64307 | 2021-11-15 | 11 | 15 | 2021 | Monday    |\n| A1F2C92308007968 | electric_bike | 2021-11-10 16:27:02 | 2021-11-10 17:04:28 | Leamington Ave &amp; Hirsch St | 307          | Leamington Ave &amp; Hirsch St | 307          | 41.91000 | -87.75000 | 41.91000 | -87.75000 | casual |    0.00000 | 2021-11-10 | 11 | 10 | 2021 | Wednesday |\n| 9B871C3B14E9BEC4 | classic_bike  | 2021-11-09 19:51:36 | 2021-11-09 20:11:17 | Desplaines St &amp; Kinzie St  | TA1306000003 | Desplaines St &amp; Kinzie St  | TA1306000003 | 41.88872 | -87.64445 | 41.88872 | -87.64445 | casual |    0.00000 | 2021-11-09 | 11 | 09 | 2021 | Tuesday   |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave | TA1309000006 | Michigan Ave &amp; Oak St      | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.13085 | 2021-11-06 | 11 | 06 | 2021 | Saturday  |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.67405 | 2021-11-18 | 11 | 18 | 2021 | Thursday  |\n\n","text/latex":"A tibble: 6 × 19\n\\begin{tabular}{lllllllllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance & date & month & day & year & day\\_of\\_week\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl> & <date> & <chr> & <chr> & <chr> & <chr>\\\\\n\\hline\n\t 4CA9676997DAFFF6 & classic\\_bike  & 2021-11-26 10:27:28 & 2021-11-26 11:22:13 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90096 & -87.62378 & 41.90096 & -87.62378 & casual &    0.00000 & 2021-11-26 & 11 & 26 & 2021 & Friday   \\\\\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St        & TA1307000127 & Clark St \\& Leland Ave      & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.64307 & 2021-11-15 & 11 & 15 & 2021 & Monday   \\\\\n\t A1F2C92308007968 & electric\\_bike & 2021-11-10 16:27:02 & 2021-11-10 17:04:28 & Leamington Ave \\& Hirsch St & 307          & Leamington Ave \\& Hirsch St & 307          & 41.91000 & -87.75000 & 41.91000 & -87.75000 & casual &    0.00000 & 2021-11-10 & 11 & 10 & 2021 & Wednesday\\\\\n\t 9B871C3B14E9BEC4 & classic\\_bike  & 2021-11-09 19:51:36 & 2021-11-09 20:11:17 & Desplaines St \\& Kinzie St  & TA1306000003 & Desplaines St \\& Kinzie St  & TA1306000003 & 41.88872 & -87.64445 & 41.88872 & -87.64445 & casual &    0.00000 & 2021-11-09 & 11 & 09 & 2021 & Tuesday  \\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave & TA1309000006 & Michigan Ave \\& Oak St      & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.13085 & 2021-11-06 & 11 & 06 & 2021 & Saturday \\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.67405 & 2021-11-18 & 11 & 18 & 2021 & Thursday \\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 4CA9676997DAFFF6 classic_bike  2021-11-26 10:27:28 2021-11-26 11:22:13\n2 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n3 A1F2C92308007968 electric_bike 2021-11-10 16:27:02 2021-11-10 17:04:28\n4 9B871C3B14E9BEC4 classic_bike  2021-11-09 19:51:36 2021-11-09 20:11:17\n5 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n6 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n  start_station_name         start_station_id end_station_name          \n1 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n2 Clark St & Grace St        TA1307000127     Clark St & Leland Ave     \n3 Leamington Ave & Hirsch St 307              Leamington Ave & Hirsch St\n4 Desplaines St & Kinzie St  TA1306000003     Desplaines St & Kinzie St \n5 Larrabee St & Armitage Ave TA1309000006     Michigan Ave & Oak St     \n6 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n  end_station_id start_lat start_lng end_lat  end_lng   usertype ride_distance\n1 13042          41.90096  -87.62378 41.90096 -87.62378 casual      0.00000   \n2 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual   1940.64307   \n3 307            41.91000  -87.75000 41.91000 -87.75000 casual      0.00000   \n4 TA1306000003   41.88872  -87.64445 41.88872 -87.64445 casual      0.00000   \n5 13042          41.91808  -87.64375 41.90096 -87.62378 casual   2524.13085   \n6 13042          41.90114  -87.62353 41.90100 -87.62375 casual     23.67405   \n  date       month day year day_of_week\n1 2021-11-26 11    26  2021 Friday     \n2 2021-11-15 11    15  2021 Monday     \n3 2021-11-10 11    10  2021 Wednesday  \n4 2021-11-09 11    09  2021 Tuesday    \n5 2021-11-06 11    06  2021 Saturday   \n6 2021-11-18 11    18  2021 Thursday   "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 19</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th><th scope=col>date</th><th scope=col>month</th><th scope=col>day</th><th scope=col>year</th><th scope=col>day_of_week</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;date&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>DC8318F0C749314B</td><td>classic_bike </td><td>2022-09-21 16:16:14</td><td>2022-09-21 16:25:40</td><td><span style=white-space:pre-wrap>Wells St &amp; Hubbard St  </span></td><td>TA1307000151</td><td><span style=white-space:pre-wrap>Wabash Ave &amp; Adams St                              </span></td><td>KA1503000015</td><td>41.88991</td><td>-87.63427</td><td>41.87947</td><td>-87.62569</td><td>member</td><td>1361.739</td><td>2022-09-21</td><td>09</td><td>21</td><td>2022</td><td>Wednesday</td></tr>\n\t<tr><td>32ECA2B32C4B6F85</td><td>classic_bike </td><td>2022-09-05 17:59:21</td><td>2022-09-05 18:19:07</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97491</td><td>-87.69250</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3041.812</td><td>2022-09-05</td><td>09</td><td>05</td><td>2022</td><td><span style=white-space:pre-wrap>Monday   </span></td></tr>\n\t<tr><td>14801F713026AEAE</td><td>classic_bike </td><td>2022-09-30 17:20:54</td><td>2022-09-30 17:34:40</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98404</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>2102.870</td><td>2022-09-30</td><td>09</td><td>30</td><td>2022</td><td><span style=white-space:pre-wrap>Friday   </span></td></tr>\n\t<tr><td>7CCAF5D6E88E45C0</td><td>electric_bike</td><td>2022-09-04 11:39:37</td><td>2022-09-04 11:50:55</td><td><span style=white-space:pre-wrap>Broadway &amp; Ridge Ave   </span></td><td><span style=white-space:pre-wrap>15578       </span></td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.98411</td><td>-87.66027</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>2110.338</td><td>2022-09-04</td><td>09</td><td>04</td><td>2022</td><td><span style=white-space:pre-wrap>Sunday   </span></td></tr>\n\t<tr><td>AF9A129D9AFAA40B</td><td>electric_bike</td><td>2022-09-28 13:42:45</td><td>2022-09-28 13:52:59</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97492</td><td>-87.69273</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3060.162</td><td>2022-09-28</td><td>09</td><td>28</td><td>2022</td><td>Wednesday</td></tr>\n\t<tr><td>60B56F4897429FCE</td><td>electric_bike</td><td>2022-09-01 20:07:04</td><td>2022-09-01 20:18:01</td><td>Lincoln Ave &amp; Winona St</td><td>KA1504000078</td><td>Broadway &amp; Wilson - Truman College Vaccination Site</td><td><span style=white-space:pre-wrap>13074       </span></td><td>41.97490</td><td>-87.69265</td><td>41.96522</td><td>-87.65814</td><td>member</td><td>3052.878</td><td>2022-09-01</td><td>09</td><td>01</td><td>2022</td><td>Thursday </td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 19\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; | date &lt;date&gt; | month &lt;chr&gt; | day &lt;chr&gt; | year &lt;chr&gt; | day_of_week &lt;chr&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| DC8318F0C749314B | classic_bike  | 2022-09-21 16:16:14 | 2022-09-21 16:25:40 | Wells St &amp; Hubbard St   | TA1307000151 | Wabash Ave &amp; Adams St                               | KA1503000015 | 41.88991 | -87.63427 | 41.87947 | -87.62569 | member | 1361.739 | 2022-09-21 | 09 | 21 | 2022 | Wednesday |\n| 32ECA2B32C4B6F85 | classic_bike  | 2022-09-05 17:59:21 | 2022-09-05 18:19:07 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97491 | -87.69250 | 41.96522 | -87.65814 | member | 3041.812 | 2022-09-05 | 09 | 05 | 2022 | Monday    |\n| 14801F713026AEAE | classic_bike  | 2022-09-30 17:20:54 | 2022-09-30 17:34:40 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98404 | -87.66027 | 41.96522 | -87.65814 | member | 2102.870 | 2022-09-30 | 09 | 30 | 2022 | Friday    |\n| 7CCAF5D6E88E45C0 | electric_bike | 2022-09-04 11:39:37 | 2022-09-04 11:50:55 | Broadway &amp; Ridge Ave    | 15578        | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.98411 | -87.66027 | 41.96522 | -87.65814 | member | 2110.338 | 2022-09-04 | 09 | 04 | 2022 | Sunday    |\n| AF9A129D9AFAA40B | electric_bike | 2022-09-28 13:42:45 | 2022-09-28 13:52:59 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97492 | -87.69273 | 41.96522 | -87.65814 | member | 3060.162 | 2022-09-28 | 09 | 28 | 2022 | Wednesday |\n| 60B56F4897429FCE | electric_bike | 2022-09-01 20:07:04 | 2022-09-01 20:18:01 | Lincoln Ave &amp; Winona St | KA1504000078 | Broadway &amp; Wilson - Truman College Vaccination Site | 13074        | 41.97490 | -87.69265 | 41.96522 | -87.65814 | member | 3052.878 | 2022-09-01 | 09 | 01 | 2022 | Thursday  |\n\n","text/latex":"A tibble: 6 × 19\n\\begin{tabular}{lllllllllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance & date & month & day & year & day\\_of\\_week\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl> & <date> & <chr> & <chr> & <chr> & <chr>\\\\\n\\hline\n\t DC8318F0C749314B & classic\\_bike  & 2022-09-21 16:16:14 & 2022-09-21 16:25:40 & Wells St \\& Hubbard St   & TA1307000151 & Wabash Ave \\& Adams St                               & KA1503000015 & 41.88991 & -87.63427 & 41.87947 & -87.62569 & member & 1361.739 & 2022-09-21 & 09 & 21 & 2022 & Wednesday\\\\\n\t 32ECA2B32C4B6F85 & classic\\_bike  & 2022-09-05 17:59:21 & 2022-09-05 18:19:07 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97491 & -87.69250 & 41.96522 & -87.65814 & member & 3041.812 & 2022-09-05 & 09 & 05 & 2022 & Monday   \\\\\n\t 14801F713026AEAE & classic\\_bike  & 2022-09-30 17:20:54 & 2022-09-30 17:34:40 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98404 & -87.66027 & 41.96522 & -87.65814 & member & 2102.870 & 2022-09-30 & 09 & 30 & 2022 & Friday   \\\\\n\t 7CCAF5D6E88E45C0 & electric\\_bike & 2022-09-04 11:39:37 & 2022-09-04 11:50:55 & Broadway \\& Ridge Ave    & 15578        & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.98411 & -87.66027 & 41.96522 & -87.65814 & member & 2110.338 & 2022-09-04 & 09 & 04 & 2022 & Sunday   \\\\\n\t AF9A129D9AFAA40B & electric\\_bike & 2022-09-28 13:42:45 & 2022-09-28 13:52:59 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97492 & -87.69273 & 41.96522 & -87.65814 & member & 3060.162 & 2022-09-28 & 09 & 28 & 2022 & Wednesday\\\\\n\t 60B56F4897429FCE & electric\\_bike & 2022-09-01 20:07:04 & 2022-09-01 20:18:01 & Lincoln Ave \\& Winona St & KA1504000078 & Broadway \\& Wilson - Truman College Vaccination Site & 13074        & 41.97490 & -87.69265 & 41.96522 & -87.65814 & member & 3052.878 & 2022-09-01 & 09 & 01 & 2022 & Thursday \\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 DC8318F0C749314B classic_bike  2022-09-21 16:16:14 2022-09-21 16:25:40\n2 32ECA2B32C4B6F85 classic_bike  2022-09-05 17:59:21 2022-09-05 18:19:07\n3 14801F713026AEAE classic_bike  2022-09-30 17:20:54 2022-09-30 17:34:40\n4 7CCAF5D6E88E45C0 electric_bike 2022-09-04 11:39:37 2022-09-04 11:50:55\n5 AF9A129D9AFAA40B electric_bike 2022-09-28 13:42:45 2022-09-28 13:52:59\n6 60B56F4897429FCE electric_bike 2022-09-01 20:07:04 2022-09-01 20:18:01\n  start_station_name      start_station_id\n1 Wells St & Hubbard St   TA1307000151    \n2 Lincoln Ave & Winona St KA1504000078    \n3 Broadway & Ridge Ave    15578           \n4 Broadway & Ridge Ave    15578           \n5 Lincoln Ave & Winona St KA1504000078    \n6 Lincoln Ave & Winona St KA1504000078    \n  end_station_name                                    end_station_id start_lat\n1 Wabash Ave & Adams St                               KA1503000015   41.88991 \n2 Broadway & Wilson - Truman College Vaccination Site 13074          41.97491 \n3 Broadway & Wilson - Truman College Vaccination Site 13074          41.98404 \n4 Broadway & Wilson - Truman College Vaccination Site 13074          41.98411 \n5 Broadway & Wilson - Truman College Vaccination Site 13074          41.97492 \n6 Broadway & Wilson - Truman College Vaccination Site 13074          41.97490 \n  start_lng end_lat  end_lng   usertype ride_distance date       month day year\n1 -87.63427 41.87947 -87.62569 member   1361.739      2022-09-21 09    21  2022\n2 -87.69250 41.96522 -87.65814 member   3041.812      2022-09-05 09    05  2022\n3 -87.66027 41.96522 -87.65814 member   2102.870      2022-09-30 09    30  2022\n4 -87.66027 41.96522 -87.65814 member   2110.338      2022-09-04 09    04  2022\n5 -87.69273 41.96522 -87.65814 member   3060.162      2022-09-28 09    28  2022\n6 -87.69265 41.96522 -87.65814 member   3052.878      2022-09-01 09    01  2022\n  day_of_week\n1 Wednesday  \n2 Monday     \n3 Friday     \n4 Sunday     \n5 Wednesday  \n6 Thursday   "},"metadata":{}}]},{"cell_type":"code","source":"str(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:26.125529Z","iopub.execute_input":"2022-10-21T04:19:26.126799Z","iopub.status.idle":"2022-10-21T04:19:26.171208Z"},"trusted":true},"execution_count":26,"outputs":[{"name":"stdout","text":"tibble [4,474,141 × 19] (S3: tbl_df/tbl/data.frame)\n $ ride_id           : chr [1:4474141] \"4CA9676997DAFFF6\" \"F3E84A230AF2D676\" \"A1F2C92308007968\" \"9B871C3B14E9BEC4\" ...\n $ rideable_type     : chr [1:4474141] \"classic_bike\" \"classic_bike\" \"electric_bike\" \"classic_bike\" ...\n $ started_at        : POSIXct[1:4474141], format: \"2021-11-26 10:27:28\" \"2021-11-15 09:35:03\" ...\n $ ended_at          : POSIXct[1:4474141], format: \"2021-11-26 11:22:13\" \"2021-11-15 09:42:08\" ...\n $ start_station_name: chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Grace St\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ start_station_id  : chr [1:4474141] \"13042\" \"TA1307000127\" \"307\" \"TA1306000003\" ...\n $ end_station_name  : chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Leland Ave\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ end_station_id    : chr [1:4474141] \"13042\" \"TA1309000014\" \"307\" \"TA1306000003\" ...\n $ start_lat         : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ start_lng         : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ end_lat           : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ end_lng           : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ usertype          : chr [1:4474141] \"casual\" \"casual\" \"casual\" \"casual\" ...\n $ ride_distance     : num [1:4474141] 0 1941 0 0 2524 ...\n $ date              : Date[1:4474141], format: \"2021-11-26\" \"2021-11-15\" ...\n $ month             : chr [1:4474141] \"11\" \"11\" \"11\" \"11\" ...\n $ day               : chr [1:4474141] \"26\" \"15\" \"10\" \"09\" ...\n $ year              : chr [1:4474141] \"2021\" \"2021\" \"2021\" \"2021\" ...\n $ day_of_week       : chr [1:4474141] \"Friday\" \"Monday\" \"Wednesday\" \"Tuesday\" ...\n","output_type":"stream"}]},{"cell_type":"code","source":"# Calculate trip duration in seconds and store as \"ride_length\"\n\ndf$ride_length <- difftime(df$ended_at,df$started_at)\nhead(df)\nstr(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:26.173485Z","iopub.execute_input":"2022-10-21T04:19:26.174772Z","iopub.status.idle":"2022-10-21T04:19:26.275920Z"},"trusted":true},"execution_count":27,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 20</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th><th scope=col>date</th><th scope=col>month</th><th scope=col>day</th><th scope=col>year</th><th scope=col>day_of_week</th><th scope=col>ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;date&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;drtn&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>4CA9676997DAFFF6</td><td>classic_bike </td><td>2021-11-26 10:27:28</td><td>2021-11-26 11:22:13</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90096</td><td>-87.62378</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-26</td><td>11</td><td>26</td><td>2021</td><td><span style=white-space:pre-wrap>Friday   </span></td><td>3285 secs</td></tr>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St       </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave     </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.64307</td><td>2021-11-15</td><td>11</td><td>15</td><td>2021</td><td><span style=white-space:pre-wrap>Monday   </span></td><td> 425 secs</td></tr>\n\t<tr><td>A1F2C92308007968</td><td>electric_bike</td><td>2021-11-10 16:27:02</td><td>2021-11-10 17:04:28</td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>Leamington Ave &amp; Hirsch St</td><td><span style=white-space:pre-wrap>307         </span></td><td>41.91000</td><td>-87.75000</td><td>41.91000</td><td>-87.75000</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-10</td><td>11</td><td>10</td><td>2021</td><td>Wednesday</td><td>2246 secs</td></tr>\n\t<tr><td>9B871C3B14E9BEC4</td><td>classic_bike </td><td>2021-11-09 19:51:36</td><td>2021-11-09 20:11:17</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>Desplaines St &amp; Kinzie St </td><td>TA1306000003</td><td>41.88872</td><td>-87.64445</td><td>41.88872</td><td>-87.64445</td><td>casual</td><td><span style=white-space:pre-wrap>   0.00000</span></td><td>2021-11-09</td><td>11</td><td>09</td><td>2021</td><td><span style=white-space:pre-wrap>Tuesday  </span></td><td>1181 secs</td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave</td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.13085</td><td>2021-11-06</td><td>11</td><td>06</td><td>2021</td><td>Saturday </td><td>1149 secs</td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St     </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.67405</span></td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday </td><td> 611 secs</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 20\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; | date &lt;date&gt; | month &lt;chr&gt; | day &lt;chr&gt; | year &lt;chr&gt; | day_of_week &lt;chr&gt; | ride_length &lt;drtn&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| 4CA9676997DAFFF6 | classic_bike  | 2021-11-26 10:27:28 | 2021-11-26 11:22:13 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90096 | -87.62378 | 41.90096 | -87.62378 | casual |    0.00000 | 2021-11-26 | 11 | 26 | 2021 | Friday    | 3285 secs |\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St        | TA1307000127 | Clark St &amp; Leland Ave      | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.64307 | 2021-11-15 | 11 | 15 | 2021 | Monday    |  425 secs |\n| A1F2C92308007968 | electric_bike | 2021-11-10 16:27:02 | 2021-11-10 17:04:28 | Leamington Ave &amp; Hirsch St | 307          | Leamington Ave &amp; Hirsch St | 307          | 41.91000 | -87.75000 | 41.91000 | -87.75000 | casual |    0.00000 | 2021-11-10 | 11 | 10 | 2021 | Wednesday | 2246 secs |\n| 9B871C3B14E9BEC4 | classic_bike  | 2021-11-09 19:51:36 | 2021-11-09 20:11:17 | Desplaines St &amp; Kinzie St  | TA1306000003 | Desplaines St &amp; Kinzie St  | TA1306000003 | 41.88872 | -87.64445 | 41.88872 | -87.64445 | casual |    0.00000 | 2021-11-09 | 11 | 09 | 2021 | Tuesday   | 1181 secs |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave | TA1309000006 | Michigan Ave &amp; Oak St      | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.13085 | 2021-11-06 | 11 | 06 | 2021 | Saturday  | 1149 secs |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St      | 13042        | Michigan Ave &amp; Oak St      | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.67405 | 2021-11-18 | 11 | 18 | 2021 | Thursday  |  611 secs |\n\n","text/latex":"A tibble: 6 × 20\n\\begin{tabular}{llllllllllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance & date & month & day & year & day\\_of\\_week & ride\\_length\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl> & <date> & <chr> & <chr> & <chr> & <chr> & <drtn>\\\\\n\\hline\n\t 4CA9676997DAFFF6 & classic\\_bike  & 2021-11-26 10:27:28 & 2021-11-26 11:22:13 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90096 & -87.62378 & 41.90096 & -87.62378 & casual &    0.00000 & 2021-11-26 & 11 & 26 & 2021 & Friday    & 3285 secs\\\\\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St        & TA1307000127 & Clark St \\& Leland Ave      & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.64307 & 2021-11-15 & 11 & 15 & 2021 & Monday    &  425 secs\\\\\n\t A1F2C92308007968 & electric\\_bike & 2021-11-10 16:27:02 & 2021-11-10 17:04:28 & Leamington Ave \\& Hirsch St & 307          & Leamington Ave \\& Hirsch St & 307          & 41.91000 & -87.75000 & 41.91000 & -87.75000 & casual &    0.00000 & 2021-11-10 & 11 & 10 & 2021 & Wednesday & 2246 secs\\\\\n\t 9B871C3B14E9BEC4 & classic\\_bike  & 2021-11-09 19:51:36 & 2021-11-09 20:11:17 & Desplaines St \\& Kinzie St  & TA1306000003 & Desplaines St \\& Kinzie St  & TA1306000003 & 41.88872 & -87.64445 & 41.88872 & -87.64445 & casual &    0.00000 & 2021-11-09 & 11 & 09 & 2021 & Tuesday   & 1181 secs\\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave & TA1309000006 & Michigan Ave \\& Oak St      & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.13085 & 2021-11-06 & 11 & 06 & 2021 & Saturday  & 1149 secs\\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St      & 13042        & Michigan Ave \\& Oak St      & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.67405 & 2021-11-18 & 11 & 18 & 2021 & Thursday  &  611 secs\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 4CA9676997DAFFF6 classic_bike  2021-11-26 10:27:28 2021-11-26 11:22:13\n2 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n3 A1F2C92308007968 electric_bike 2021-11-10 16:27:02 2021-11-10 17:04:28\n4 9B871C3B14E9BEC4 classic_bike  2021-11-09 19:51:36 2021-11-09 20:11:17\n5 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n6 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n  start_station_name         start_station_id end_station_name          \n1 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n2 Clark St & Grace St        TA1307000127     Clark St & Leland Ave     \n3 Leamington Ave & Hirsch St 307              Leamington Ave & Hirsch St\n4 Desplaines St & Kinzie St  TA1306000003     Desplaines St & Kinzie St \n5 Larrabee St & Armitage Ave TA1309000006     Michigan Ave & Oak St     \n6 Michigan Ave & Oak St      13042            Michigan Ave & Oak St     \n  end_station_id start_lat start_lng end_lat  end_lng   usertype ride_distance\n1 13042          41.90096  -87.62378 41.90096 -87.62378 casual      0.00000   \n2 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual   1940.64307   \n3 307            41.91000  -87.75000 41.91000 -87.75000 casual      0.00000   \n4 TA1306000003   41.88872  -87.64445 41.88872 -87.64445 casual      0.00000   \n5 13042          41.91808  -87.64375 41.90096 -87.62378 casual   2524.13085   \n6 13042          41.90114  -87.62353 41.90100 -87.62375 casual     23.67405   \n  date       month day year day_of_week ride_length\n1 2021-11-26 11    26  2021 Friday      3285 secs  \n2 2021-11-15 11    15  2021 Monday       425 secs  \n3 2021-11-10 11    10  2021 Wednesday   2246 secs  \n4 2021-11-09 11    09  2021 Tuesday     1181 secs  \n5 2021-11-06 11    06  2021 Saturday    1149 secs  \n6 2021-11-18 11    18  2021 Thursday     611 secs  "},"metadata":{}},{"name":"stdout","text":"tibble [4,474,141 × 20] (S3: tbl_df/tbl/data.frame)\n $ ride_id           : chr [1:4474141] \"4CA9676997DAFFF6\" \"F3E84A230AF2D676\" \"A1F2C92308007968\" \"9B871C3B14E9BEC4\" ...\n $ rideable_type     : chr [1:4474141] \"classic_bike\" \"classic_bike\" \"electric_bike\" \"classic_bike\" ...\n $ started_at        : POSIXct[1:4474141], format: \"2021-11-26 10:27:28\" \"2021-11-15 09:35:03\" ...\n $ ended_at          : POSIXct[1:4474141], format: \"2021-11-26 11:22:13\" \"2021-11-15 09:42:08\" ...\n $ start_station_name: chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Grace St\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ start_station_id  : chr [1:4474141] \"13042\" \"TA1307000127\" \"307\" \"TA1306000003\" ...\n $ end_station_name  : chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Leland Ave\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ end_station_id    : chr [1:4474141] \"13042\" \"TA1309000014\" \"307\" \"TA1306000003\" ...\n $ start_lat         : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ start_lng         : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ end_lat           : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ end_lng           : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ usertype          : chr [1:4474141] \"casual\" \"casual\" \"casual\" \"casual\" ...\n $ ride_distance     : num [1:4474141] 0 1941 0 0 2524 ...\n $ date              : Date[1:4474141], format: \"2021-11-26\" \"2021-11-15\" ...\n $ month             : chr [1:4474141] \"11\" \"11\" \"11\" \"11\" ...\n $ day               : chr [1:4474141] \"26\" \"15\" \"10\" \"09\" ...\n $ year              : chr [1:4474141] \"2021\" \"2021\" \"2021\" \"2021\" ...\n $ day_of_week       : chr [1:4474141] \"Friday\" \"Monday\" \"Wednesday\" \"Tuesday\" ...\n $ ride_length       : 'difftime' num [1:4474141] 3285 425 2246 1181 ...\n  ..- attr(*, \"units\")= chr \"secs\"\n","output_type":"stream"}]},{"cell_type":"code","source":"# Convert \"ride_length\" from difftime to numeric so we can run calculations on the data\n\nis.difftime(df$ride_length)\ndf$ride_length <- as.numeric(as.difftime(df$ride_length))\nis.numeric(df$ride_length)\nstr(df)\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:26.278220Z","iopub.execute_input":"2022-10-21T04:19:26.279551Z","iopub.status.idle":"2022-10-21T04:19:26.345789Z"},"trusted":true},"execution_count":28,"outputs":[{"output_type":"display_data","data":{"text/html":"TRUE","text/markdown":"TRUE","text/latex":"TRUE","text/plain":"[1] TRUE"},"metadata":{}},{"output_type":"display_data","data":{"text/html":"TRUE","text/markdown":"TRUE","text/latex":"TRUE","text/plain":"[1] TRUE"},"metadata":{}},{"name":"stdout","text":"tibble [4,474,141 × 20] (S3: tbl_df/tbl/data.frame)\n $ ride_id           : chr [1:4474141] \"4CA9676997DAFFF6\" \"F3E84A230AF2D676\" \"A1F2C92308007968\" \"9B871C3B14E9BEC4\" ...\n $ rideable_type     : chr [1:4474141] \"classic_bike\" \"classic_bike\" \"electric_bike\" \"classic_bike\" ...\n $ started_at        : POSIXct[1:4474141], format: \"2021-11-26 10:27:28\" \"2021-11-15 09:35:03\" ...\n $ ended_at          : POSIXct[1:4474141], format: \"2021-11-26 11:22:13\" \"2021-11-15 09:42:08\" ...\n $ start_station_name: chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Grace St\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ start_station_id  : chr [1:4474141] \"13042\" \"TA1307000127\" \"307\" \"TA1306000003\" ...\n $ end_station_name  : chr [1:4474141] \"Michigan Ave & Oak St\" \"Clark St & Leland Ave\" \"Leamington Ave & Hirsch St\" \"Desplaines St & Kinzie St\" ...\n $ end_station_id    : chr [1:4474141] \"13042\" \"TA1309000014\" \"307\" \"TA1306000003\" ...\n $ start_lat         : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ start_lng         : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ end_lat           : num [1:4474141] 41.9 42 41.9 41.9 41.9 ...\n $ end_lng           : num [1:4474141] -87.6 -87.7 -87.8 -87.6 -87.6 ...\n $ usertype          : chr [1:4474141] \"casual\" \"casual\" \"casual\" \"casual\" ...\n $ ride_distance     : num [1:4474141] 0 1941 0 0 2524 ...\n $ date              : Date[1:4474141], format: \"2021-11-26\" \"2021-11-15\" ...\n $ month             : chr [1:4474141] \"11\" \"11\" \"11\" \"11\" ...\n $ day               : chr [1:4474141] \"26\" \"15\" \"10\" \"09\" ...\n $ year              : chr [1:4474141] \"2021\" \"2021\" \"2021\" \"2021\" ...\n $ day_of_week       : chr [1:4474141] \"Friday\" \"Monday\" \"Wednesday\" \"Tuesday\" ...\n $ ride_length       : num [1:4474141] 3285 425 2246 1181 1149 ...\n","output_type":"stream"}]},{"cell_type":"code","source":"# removal of rides that are lesser than 0 seconds and 0 meters\ndf <- df %>% \nfilter(ride_length > 0) %>%\nfilter(ride_distance > 0)\nhead(df)\ndim(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:26.349515Z","iopub.execute_input":"2022-10-21T04:19:26.351054Z","iopub.status.idle":"2022-10-21T04:19:31.059901Z"},"trusted":true},"execution_count":29,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 20</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th><th scope=col>date</th><th scope=col>month</th><th scope=col>day</th><th scope=col>year</th><th scope=col>day_of_week</th><th scope=col>ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;date&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St        </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave      </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.643071</td><td>2021-11-15</td><td>11</td><td>15</td><td>2021</td><td><span style=white-space:pre-wrap>Monday  </span></td><td> 425</td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave </td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.130848</td><td>2021-11-06</td><td>11</td><td>06</td><td>2021</td><td>Saturday</td><td>1149</td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.674046</span></td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday</td><td> 611</td></tr>\n\t<tr><td>C79A70DFD07E75D9</td><td>electric_bike</td><td>2021-11-23 22:14:11</td><td>2021-11-23 22:44:01</td><td>Sheridan Rd &amp; Noyes St (NU)</td><td><span style=white-space:pre-wrap>604         </span></td><td>Sheridan Rd &amp; Noyes St (NU)</td><td><span style=white-space:pre-wrap>604         </span></td><td>42.05820</td><td>-87.67755</td><td>42.05825</td><td>-87.67752</td><td>casual</td><td><span style=white-space:pre-wrap>   6.625242</span></td><td>2021-11-23</td><td>11</td><td>23</td><td>2021</td><td>Tuesday </td><td>1790</td></tr>\n\t<tr><td>41E7F8FB5640B521</td><td>electric_bike</td><td>2021-11-05 16:48:10</td><td>2021-11-05 16:53:18</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St        </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave      </span></td><td>TA1309000014</td><td>41.95086</td><td>-87.65913</td><td>41.96707</td><td>-87.66745</td><td>member</td><td>1931.724227</td><td>2021-11-05</td><td>11</td><td>05</td><td>2021</td><td><span style=white-space:pre-wrap>Friday  </span></td><td> 308</td></tr>\n\t<tr><td>3DEAAA1701BBD1D3</td><td>electric_bike</td><td>2021-11-18 08:40:38</td><td>2021-11-18 08:48:56</td><td><span style=white-space:pre-wrap>Desplaines St &amp; Kinzie St  </span></td><td>TA1306000003</td><td><span style=white-space:pre-wrap>Dearborn St &amp; Monroe St    </span></td><td>TA1305000006</td><td>41.88863</td><td>-87.64437</td><td>41.88160</td><td>-87.63013</td><td>member</td><td>1415.569490</td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday</td><td> 498</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 20\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; | date &lt;date&gt; | month &lt;chr&gt; | day &lt;chr&gt; | year &lt;chr&gt; | day_of_week &lt;chr&gt; | ride_length &lt;dbl&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St         | TA1307000127 | Clark St &amp; Leland Ave       | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.643071 | 2021-11-15 | 11 | 15 | 2021 | Monday   |  425 |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave  | TA1309000006 | Michigan Ave &amp; Oak St       | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.130848 | 2021-11-06 | 11 | 06 | 2021 | Saturday | 1149 |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St       | 13042        | Michigan Ave &amp; Oak St       | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.674046 | 2021-11-18 | 11 | 18 | 2021 | Thursday |  611 |\n| C79A70DFD07E75D9 | electric_bike | 2021-11-23 22:14:11 | 2021-11-23 22:44:01 | Sheridan Rd &amp; Noyes St (NU) | 604          | Sheridan Rd &amp; Noyes St (NU) | 604          | 42.05820 | -87.67755 | 42.05825 | -87.67752 | casual |    6.625242 | 2021-11-23 | 11 | 23 | 2021 | Tuesday  | 1790 |\n| 41E7F8FB5640B521 | electric_bike | 2021-11-05 16:48:10 | 2021-11-05 16:53:18 | Clark St &amp; Grace St         | TA1307000127 | Clark St &amp; Leland Ave       | TA1309000014 | 41.95086 | -87.65913 | 41.96707 | -87.66745 | member | 1931.724227 | 2021-11-05 | 11 | 05 | 2021 | Friday   |  308 |\n| 3DEAAA1701BBD1D3 | electric_bike | 2021-11-18 08:40:38 | 2021-11-18 08:48:56 | Desplaines St &amp; Kinzie St   | TA1306000003 | Dearborn St &amp; Monroe St     | TA1305000006 | 41.88863 | -87.64437 | 41.88160 | -87.63013 | member | 1415.569490 | 2021-11-18 | 11 | 18 | 2021 | Thursday |  498 |\n\n","text/latex":"A tibble: 6 × 20\n\\begin{tabular}{llllllllllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance & date & month & day & year & day\\_of\\_week & ride\\_length\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl> & <date> & <chr> & <chr> & <chr> & <chr> & <dbl>\\\\\n\\hline\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St         & TA1307000127 & Clark St \\& Leland Ave       & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.643071 & 2021-11-15 & 11 & 15 & 2021 & Monday   &  425\\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave  & TA1309000006 & Michigan Ave \\& Oak St       & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.130848 & 2021-11-06 & 11 & 06 & 2021 & Saturday & 1149\\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St       & 13042        & Michigan Ave \\& Oak St       & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.674046 & 2021-11-18 & 11 & 18 & 2021 & Thursday &  611\\\\\n\t C79A70DFD07E75D9 & electric\\_bike & 2021-11-23 22:14:11 & 2021-11-23 22:44:01 & Sheridan Rd \\& Noyes St (NU) & 604          & Sheridan Rd \\& Noyes St (NU) & 604          & 42.05820 & -87.67755 & 42.05825 & -87.67752 & casual &    6.625242 & 2021-11-23 & 11 & 23 & 2021 & Tuesday  & 1790\\\\\n\t 41E7F8FB5640B521 & electric\\_bike & 2021-11-05 16:48:10 & 2021-11-05 16:53:18 & Clark St \\& Grace St         & TA1307000127 & Clark St \\& Leland Ave       & TA1309000014 & 41.95086 & -87.65913 & 41.96707 & -87.66745 & member & 1931.724227 & 2021-11-05 & 11 & 05 & 2021 & Friday   &  308\\\\\n\t 3DEAAA1701BBD1D3 & electric\\_bike & 2021-11-18 08:40:38 & 2021-11-18 08:48:56 & Desplaines St \\& Kinzie St   & TA1306000003 & Dearborn St \\& Monroe St     & TA1305000006 & 41.88863 & -87.64437 & 41.88160 & -87.63013 & member & 1415.569490 & 2021-11-18 & 11 & 18 & 2021 & Thursday &  498\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n2 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n3 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n4 C79A70DFD07E75D9 electric_bike 2021-11-23 22:14:11 2021-11-23 22:44:01\n5 41E7F8FB5640B521 electric_bike 2021-11-05 16:48:10 2021-11-05 16:53:18\n6 3DEAAA1701BBD1D3 electric_bike 2021-11-18 08:40:38 2021-11-18 08:48:56\n  start_station_name          start_station_id end_station_name           \n1 Clark St & Grace St         TA1307000127     Clark St & Leland Ave      \n2 Larrabee St & Armitage Ave  TA1309000006     Michigan Ave & Oak St      \n3 Michigan Ave & Oak St       13042            Michigan Ave & Oak St      \n4 Sheridan Rd & Noyes St (NU) 604              Sheridan Rd & Noyes St (NU)\n5 Clark St & Grace St         TA1307000127     Clark St & Leland Ave      \n6 Desplaines St & Kinzie St   TA1306000003     Dearborn St & Monroe St    \n  end_station_id start_lat start_lng end_lat  end_lng   usertype ride_distance\n1 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual   1940.643071  \n2 13042          41.91808  -87.64375 41.90096 -87.62378 casual   2524.130848  \n3 13042          41.90114  -87.62353 41.90100 -87.62375 casual     23.674046  \n4 604            42.05820  -87.67755 42.05825 -87.67752 casual      6.625242  \n5 TA1309000014   41.95086  -87.65913 41.96707 -87.66745 member   1931.724227  \n6 TA1305000006   41.88863  -87.64437 41.88160 -87.63013 member   1415.569490  \n  date       month day year day_of_week ride_length\n1 2021-11-15 11    15  2021 Monday       425       \n2 2021-11-06 11    06  2021 Saturday    1149       \n3 2021-11-18 11    18  2021 Thursday     611       \n4 2021-11-23 11    23  2021 Tuesday     1790       \n5 2021-11-05 11    05  2021 Friday       308       \n6 2021-11-18 11    18  2021 Thursday     498       "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>4264911</li><li>20</li></ol>\n","text/markdown":"1. 4264911\n2. 20\n\n\n","text/latex":"\\begin{enumerate*}\n\\item 4264911\n\\item 20\n\\end{enumerate*}\n","text/plain":"[1] 4264911      20"},"metadata":{}}]},{"cell_type":"markdown","source":"### Analyze \n\n#### *Key Tasks*\n\n* Perform calculations.\n* Identify trends and relationships.\n* Conduct descriptive analysis.","metadata":{}},{"cell_type":"code","source":"# desciptive analysis on ride length (in seconds)\n\nsummary(df$ride_length)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:31.062838Z","iopub.execute_input":"2022-10-21T04:19:31.064379Z","iopub.status.idle":"2022-10-21T04:19:31.381987Z"},"trusted":true},"execution_count":30,"outputs":[{"output_type":"display_data","data":{"text/plain":"   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n      1     376     643    1007    1125 2442301 "},"metadata":{}}]},{"cell_type":"code","source":"# compare ride_length of casual riders vs member usertype using summary statistics \n\naggregate(df$ride_length ~ df$usertype, FUN = mean)\naggregate(df$ride_length ~ df$usertype, FUN = median)\naggregate(df$ride_length ~ df$usertype, FUN = max)\naggregate(df$ride_length ~ df$usertype, FUN = min)\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:31.384121Z","iopub.execute_input":"2022-10-21T04:19:31.385427Z","iopub.status.idle":"2022-10-21T04:19:43.391449Z"},"trusted":true},"execution_count":31,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>1413.5592</td></tr>\n\t<tr><td>member</td><td> 742.9806</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|\n| casual | 1413.5592 |\n| member |  742.9806 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_length\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 1413.5592\\\\\n\t member &  742.9806\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_length\n1 casual      1413.5592     \n2 member       742.9806     "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>839</td></tr>\n\t<tr><td>member</td><td>544</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|\n| casual | 839 |\n| member | 544 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_length\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 839\\\\\n\t member & 544\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_length\n1 casual      839           \n2 member      544           "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>2442301</td></tr>\n\t<tr><td>member</td><td>  89575</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|\n| casual | 2442301 |\n| member |   89575 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_length\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 2442301\\\\\n\t member &   89575\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_length\n1 casual      2442301       \n2 member        89575       "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>1</td></tr>\n\t<tr><td>member</td><td>1</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|\n| casual | 1 |\n| member | 1 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_length\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 1\\\\\n\t member & 1\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_length\n1 casual      1             \n2 member      1             "},"metadata":{}}]},{"cell_type":"code","source":"# compare ride_distance of casual riders vs member usertype using summary statistics \naggregate(df$ride_distance ~ df$usertype, FUN = mean)\naggregate(df$ride_distance ~ df$usertype, FUN = median)\naggregate(df$ride_distance ~ df$usertype, FUN = max)\naggregate(df$ride_distance ~ df$usertype, FUN = min)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:43.393587Z","iopub.execute_input":"2022-10-21T04:19:43.394840Z","iopub.status.idle":"2022-10-21T04:19:52.893777Z"},"trusted":true},"execution_count":32,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>2337.208</td></tr>\n\t<tr><td>member</td><td>2113.497</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|\n| casual | 2337.208 |\n| member | 2113.497 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_distance\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 2337.208\\\\\n\t member & 2113.497\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_distance\n1 casual      2337.208        \n2 member      2113.497        "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>1796.973</td></tr>\n\t<tr><td>member</td><td>1553.776</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|\n| casual | 1796.973 |\n| member | 1553.776 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_distance\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 1796.973\\\\\n\t member & 1553.776\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_distance\n1 casual      1796.973        \n2 member      1553.776        "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>1190854.54</td></tr>\n\t<tr><td>member</td><td>  27518.42</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|\n| casual | 1190854.54 |\n| member |   27518.42 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_distance\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 1190854.54\\\\\n\t member &   27518.42\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_distance\n1 casual      1190854.54      \n2 member        27518.42      "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 2 × 2</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>0.03321865</td></tr>\n\t<tr><td>member</td><td>0.02016286</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 2 × 2\n\n| df$usertype &lt;chr&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|\n| casual | 0.03321865 |\n| member | 0.02016286 |\n\n","text/latex":"A data.frame: 2 × 2\n\\begin{tabular}{ll}\n df\\$usertype & df\\$ride\\_distance\\\\\n <chr> & <dbl>\\\\\n\\hline\n\t casual & 0.03321865\\\\\n\t member & 0.02016286\\\\\n\\end{tabular}\n","text/plain":"  df$usertype df$ride_distance\n1 casual      0.03321865      \n2 member      0.02016286      "},"metadata":{}}]},{"cell_type":"code","source":"# Average ride length by day_of_week for members vs casual users\naggregate(df$ride_length ~ df$usertype + df$day_of_week, FUN = mean)\n\n# Average ride distance by day_of_week for members vs casual users\naggregate(df$ride_distance ~ df$usertype + df$day_of_week, FUN = mean)\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:52.895946Z","iopub.execute_input":"2022-10-21T04:19:52.897162Z","iopub.status.idle":"2022-10-21T04:19:59.412301Z"},"trusted":true},"execution_count":33,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 14 × 3</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$day_of_week</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>Friday   </td><td>1322.3779</td></tr>\n\t<tr><td>member</td><td>Friday   </td><td> 727.5950</td></tr>\n\t<tr><td>casual</td><td>Monday   </td><td>1437.8708</td></tr>\n\t<tr><td>member</td><td>Monday   </td><td> 714.5053</td></tr>\n\t<tr><td>casual</td><td>Saturday </td><td>1588.4810</td></tr>\n\t<tr><td>member</td><td>Saturday </td><td> 839.8172</td></tr>\n\t<tr><td>casual</td><td>Sunday   </td><td>1614.8434</td></tr>\n\t<tr><td>member</td><td>Sunday   </td><td> 830.5445</td></tr>\n\t<tr><td>casual</td><td>Thursday </td><td>1251.6093</td></tr>\n\t<tr><td>member</td><td>Thursday </td><td> 716.1125</td></tr>\n\t<tr><td>casual</td><td>Tuesday  </td><td>1252.5735</td></tr>\n\t<tr><td>member</td><td>Tuesday  </td><td> 702.8027</td></tr>\n\t<tr><td>casual</td><td>Wednesday</td><td>1213.9254</td></tr>\n\t<tr><td>member</td><td>Wednesday</td><td> 707.0913</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 14 × 3\n\n| df$usertype &lt;chr&gt; | df$day_of_week &lt;chr&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|---|\n| casual | Friday    | 1322.3779 |\n| member | Friday    |  727.5950 |\n| casual | Monday    | 1437.8708 |\n| member | Monday    |  714.5053 |\n| casual | Saturday  | 1588.4810 |\n| member | Saturday  |  839.8172 |\n| casual | Sunday    | 1614.8434 |\n| member | Sunday    |  830.5445 |\n| casual | Thursday  | 1251.6093 |\n| member | Thursday  |  716.1125 |\n| casual | Tuesday   | 1252.5735 |\n| member | Tuesday   |  702.8027 |\n| casual | Wednesday | 1213.9254 |\n| member | Wednesday |  707.0913 |\n\n","text/latex":"A data.frame: 14 × 3\n\\begin{tabular}{lll}\n df\\$usertype & df\\$day\\_of\\_week & df\\$ride\\_length\\\\\n <chr> & <chr> & <dbl>\\\\\n\\hline\n\t casual & Friday    & 1322.3779\\\\\n\t member & Friday    &  727.5950\\\\\n\t casual & Monday    & 1437.8708\\\\\n\t member & Monday    &  714.5053\\\\\n\t casual & Saturday  & 1588.4810\\\\\n\t member & Saturday  &  839.8172\\\\\n\t casual & Sunday    & 1614.8434\\\\\n\t member & Sunday    &  830.5445\\\\\n\t casual & Thursday  & 1251.6093\\\\\n\t member & Thursday  &  716.1125\\\\\n\t casual & Tuesday   & 1252.5735\\\\\n\t member & Tuesday   &  702.8027\\\\\n\t casual & Wednesday & 1213.9254\\\\\n\t member & Wednesday &  707.0913\\\\\n\\end{tabular}\n","text/plain":"   df$usertype df$day_of_week df$ride_length\n1  casual      Friday         1322.3779     \n2  member      Friday          727.5950     \n3  casual      Monday         1437.8708     \n4  member      Monday          714.5053     \n5  casual      Saturday       1588.4810     \n6  member      Saturday        839.8172     \n7  casual      Sunday         1614.8434     \n8  member      Sunday          830.5445     \n9  casual      Thursday       1251.6093     \n10 member      Thursday        716.1125     \n11 casual      Tuesday        1252.5735     \n12 member      Tuesday         702.8027     \n13 casual      Wednesday      1213.9254     \n14 member      Wednesday       707.0913     "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 14 × 3</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$day_of_week</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>Friday   </td><td>2284.771</td></tr>\n\t<tr><td>member</td><td>Friday   </td><td>2069.064</td></tr>\n\t<tr><td>casual</td><td>Monday   </td><td>2270.612</td></tr>\n\t<tr><td>member</td><td>Monday   </td><td>2072.956</td></tr>\n\t<tr><td>casual</td><td>Saturday </td><td>2473.236</td></tr>\n\t<tr><td>member</td><td>Saturday </td><td>2226.435</td></tr>\n\t<tr><td>casual</td><td>Sunday   </td><td>2433.727</td></tr>\n\t<tr><td>member</td><td>Sunday   </td><td>2186.421</td></tr>\n\t<tr><td>casual</td><td>Thursday </td><td>2268.423</td></tr>\n\t<tr><td>member</td><td>Thursday </td><td>2094.768</td></tr>\n\t<tr><td>casual</td><td>Tuesday  </td><td>2242.841</td></tr>\n\t<tr><td>member</td><td>Tuesday  </td><td>2080.827</td></tr>\n\t<tr><td>casual</td><td>Wednesday</td><td>2240.750</td></tr>\n\t<tr><td>member</td><td>Wednesday</td><td>2095.610</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 14 × 3\n\n| df$usertype &lt;chr&gt; | df$day_of_week &lt;chr&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|---|\n| casual | Friday    | 2284.771 |\n| member | Friday    | 2069.064 |\n| casual | Monday    | 2270.612 |\n| member | Monday    | 2072.956 |\n| casual | Saturday  | 2473.236 |\n| member | Saturday  | 2226.435 |\n| casual | Sunday    | 2433.727 |\n| member | Sunday    | 2186.421 |\n| casual | Thursday  | 2268.423 |\n| member | Thursday  | 2094.768 |\n| casual | Tuesday   | 2242.841 |\n| member | Tuesday   | 2080.827 |\n| casual | Wednesday | 2240.750 |\n| member | Wednesday | 2095.610 |\n\n","text/latex":"A data.frame: 14 × 3\n\\begin{tabular}{lll}\n df\\$usertype & df\\$day\\_of\\_week & df\\$ride\\_distance\\\\\n <chr> & <chr> & <dbl>\\\\\n\\hline\n\t casual & Friday    & 2284.771\\\\\n\t member & Friday    & 2069.064\\\\\n\t casual & Monday    & 2270.612\\\\\n\t member & Monday    & 2072.956\\\\\n\t casual & Saturday  & 2473.236\\\\\n\t member & Saturday  & 2226.435\\\\\n\t casual & Sunday    & 2433.727\\\\\n\t member & Sunday    & 2186.421\\\\\n\t casual & Thursday  & 2268.423\\\\\n\t member & Thursday  & 2094.768\\\\\n\t casual & Tuesday   & 2242.841\\\\\n\t member & Tuesday   & 2080.827\\\\\n\t casual & Wednesday & 2240.750\\\\\n\t member & Wednesday & 2095.610\\\\\n\\end{tabular}\n","text/plain":"   df$usertype df$day_of_week df$ride_distance\n1  casual      Friday         2284.771        \n2  member      Friday         2069.064        \n3  casual      Monday         2270.612        \n4  member      Monday         2072.956        \n5  casual      Saturday       2473.236        \n6  member      Saturday       2226.435        \n7  casual      Sunday         2433.727        \n8  member      Sunday         2186.421        \n9  casual      Thursday       2268.423        \n10 member      Thursday       2094.768        \n11 casual      Tuesday        2242.841        \n12 member      Tuesday        2080.827        \n13 casual      Wednesday      2240.750        \n14 member      Wednesday      2095.610        "},"metadata":{}}]},{"cell_type":"code","source":"# Notice that the days of the week are out of order. Let's fix that.\ndf$day_of_week <- ordered(df$day_of_week, levels=c(\"Sunday\", \"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\", \"Saturday\"))\n\n\n# Now, let's run the average ride length by day of week for members vs casual users\n\naggregate(df$ride_length ~ df$usertype + df$day_of_week, FUN = mean)\n\n# Average ride distance by day_of_week for members vs casual users\naggregate(df$ride_distance ~ df$usertype + df$day_of_week, FUN = mean)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:19:59.415635Z","iopub.execute_input":"2022-10-21T04:19:59.417051Z","iopub.status.idle":"2022-10-21T04:20:05.186714Z"},"trusted":true},"execution_count":34,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 14 × 3</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$day_of_week</th><th scope=col>df$ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;ord&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>Sunday   </td><td>1614.8434</td></tr>\n\t<tr><td>member</td><td>Sunday   </td><td> 830.5445</td></tr>\n\t<tr><td>casual</td><td>Monday   </td><td>1437.8708</td></tr>\n\t<tr><td>member</td><td>Monday   </td><td> 714.5053</td></tr>\n\t<tr><td>casual</td><td>Tuesday  </td><td>1252.5735</td></tr>\n\t<tr><td>member</td><td>Tuesday  </td><td> 702.8027</td></tr>\n\t<tr><td>casual</td><td>Wednesday</td><td>1213.9254</td></tr>\n\t<tr><td>member</td><td>Wednesday</td><td> 707.0913</td></tr>\n\t<tr><td>casual</td><td>Thursday </td><td>1251.6093</td></tr>\n\t<tr><td>member</td><td>Thursday </td><td> 716.1125</td></tr>\n\t<tr><td>casual</td><td>Friday   </td><td>1322.3779</td></tr>\n\t<tr><td>member</td><td>Friday   </td><td> 727.5950</td></tr>\n\t<tr><td>casual</td><td>Saturday </td><td>1588.4810</td></tr>\n\t<tr><td>member</td><td>Saturday </td><td> 839.8172</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 14 × 3\n\n| df$usertype &lt;chr&gt; | df$day_of_week &lt;ord&gt; | df$ride_length &lt;dbl&gt; |\n|---|---|---|\n| casual | Sunday    | 1614.8434 |\n| member | Sunday    |  830.5445 |\n| casual | Monday    | 1437.8708 |\n| member | Monday    |  714.5053 |\n| casual | Tuesday   | 1252.5735 |\n| member | Tuesday   |  702.8027 |\n| casual | Wednesday | 1213.9254 |\n| member | Wednesday |  707.0913 |\n| casual | Thursday  | 1251.6093 |\n| member | Thursday  |  716.1125 |\n| casual | Friday    | 1322.3779 |\n| member | Friday    |  727.5950 |\n| casual | Saturday  | 1588.4810 |\n| member | Saturday  |  839.8172 |\n\n","text/latex":"A data.frame: 14 × 3\n\\begin{tabular}{lll}\n df\\$usertype & df\\$day\\_of\\_week & df\\$ride\\_length\\\\\n <chr> & <ord> & <dbl>\\\\\n\\hline\n\t casual & Sunday    & 1614.8434\\\\\n\t member & Sunday    &  830.5445\\\\\n\t casual & Monday    & 1437.8708\\\\\n\t member & Monday    &  714.5053\\\\\n\t casual & Tuesday   & 1252.5735\\\\\n\t member & Tuesday   &  702.8027\\\\\n\t casual & Wednesday & 1213.9254\\\\\n\t member & Wednesday &  707.0913\\\\\n\t casual & Thursday  & 1251.6093\\\\\n\t member & Thursday  &  716.1125\\\\\n\t casual & Friday    & 1322.3779\\\\\n\t member & Friday    &  727.5950\\\\\n\t casual & Saturday  & 1588.4810\\\\\n\t member & Saturday  &  839.8172\\\\\n\\end{tabular}\n","text/plain":"   df$usertype df$day_of_week df$ride_length\n1  casual      Sunday         1614.8434     \n2  member      Sunday          830.5445     \n3  casual      Monday         1437.8708     \n4  member      Monday          714.5053     \n5  casual      Tuesday        1252.5735     \n6  member      Tuesday         702.8027     \n7  casual      Wednesday      1213.9254     \n8  member      Wednesday       707.0913     \n9  casual      Thursday       1251.6093     \n10 member      Thursday        716.1125     \n11 casual      Friday         1322.3779     \n12 member      Friday          727.5950     \n13 casual      Saturday       1588.4810     \n14 member      Saturday        839.8172     "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A data.frame: 14 × 3</caption>\n<thead>\n\t<tr><th scope=col>df$usertype</th><th scope=col>df$day_of_week</th><th scope=col>df$ride_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;ord&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>Sunday   </td><td>2433.727</td></tr>\n\t<tr><td>member</td><td>Sunday   </td><td>2186.421</td></tr>\n\t<tr><td>casual</td><td>Monday   </td><td>2270.612</td></tr>\n\t<tr><td>member</td><td>Monday   </td><td>2072.956</td></tr>\n\t<tr><td>casual</td><td>Tuesday  </td><td>2242.841</td></tr>\n\t<tr><td>member</td><td>Tuesday  </td><td>2080.827</td></tr>\n\t<tr><td>casual</td><td>Wednesday</td><td>2240.750</td></tr>\n\t<tr><td>member</td><td>Wednesday</td><td>2095.610</td></tr>\n\t<tr><td>casual</td><td>Thursday </td><td>2268.423</td></tr>\n\t<tr><td>member</td><td>Thursday </td><td>2094.768</td></tr>\n\t<tr><td>casual</td><td>Friday   </td><td>2284.771</td></tr>\n\t<tr><td>member</td><td>Friday   </td><td>2069.064</td></tr>\n\t<tr><td>casual</td><td>Saturday </td><td>2473.236</td></tr>\n\t<tr><td>member</td><td>Saturday </td><td>2226.435</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 14 × 3\n\n| df$usertype &lt;chr&gt; | df$day_of_week &lt;ord&gt; | df$ride_distance &lt;dbl&gt; |\n|---|---|---|\n| casual | Sunday    | 2433.727 |\n| member | Sunday    | 2186.421 |\n| casual | Monday    | 2270.612 |\n| member | Monday    | 2072.956 |\n| casual | Tuesday   | 2242.841 |\n| member | Tuesday   | 2080.827 |\n| casual | Wednesday | 2240.750 |\n| member | Wednesday | 2095.610 |\n| casual | Thursday  | 2268.423 |\n| member | Thursday  | 2094.768 |\n| casual | Friday    | 2284.771 |\n| member | Friday    | 2069.064 |\n| casual | Saturday  | 2473.236 |\n| member | Saturday  | 2226.435 |\n\n","text/latex":"A data.frame: 14 × 3\n\\begin{tabular}{lll}\n df\\$usertype & df\\$day\\_of\\_week & df\\$ride\\_distance\\\\\n <chr> & <ord> & <dbl>\\\\\n\\hline\n\t casual & Sunday    & 2433.727\\\\\n\t member & Sunday    & 2186.421\\\\\n\t casual & Monday    & 2270.612\\\\\n\t member & Monday    & 2072.956\\\\\n\t casual & Tuesday   & 2242.841\\\\\n\t member & Tuesday   & 2080.827\\\\\n\t casual & Wednesday & 2240.750\\\\\n\t member & Wednesday & 2095.610\\\\\n\t casual & Thursday  & 2268.423\\\\\n\t member & Thursday  & 2094.768\\\\\n\t casual & Friday    & 2284.771\\\\\n\t member & Friday    & 2069.064\\\\\n\t casual & Saturday  & 2473.236\\\\\n\t member & Saturday  & 2226.435\\\\\n\\end{tabular}\n","text/plain":"   df$usertype df$day_of_week df$ride_distance\n1  casual      Sunday         2433.727        \n2  member      Sunday         2186.421        \n3  casual      Monday         2270.612        \n4  member      Monday         2072.956        \n5  casual      Tuesday        2242.841        \n6  member      Tuesday        2080.827        \n7  casual      Wednesday      2240.750        \n8  member      Wednesday      2095.610        \n9  casual      Thursday       2268.423        \n10 member      Thursday       2094.768        \n11 casual      Friday         2284.771        \n12 member      Friday         2069.064        \n13 casual      Saturday       2473.236        \n14 member      Saturday       2226.435        "},"metadata":{}}]},{"cell_type":"code","source":"head(df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:20:05.189990Z","iopub.execute_input":"2022-10-21T04:20:05.191419Z","iopub.status.idle":"2022-10-21T04:20:05.222096Z"},"trusted":true},"execution_count":35,"outputs":[{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 6 × 20</caption>\n<thead>\n\t<tr><th scope=col>ride_id</th><th scope=col>rideable_type</th><th scope=col>started_at</th><th scope=col>ended_at</th><th scope=col>start_station_name</th><th scope=col>start_station_id</th><th scope=col>end_station_name</th><th scope=col>end_station_id</th><th scope=col>start_lat</th><th scope=col>start_lng</th><th scope=col>end_lat</th><th scope=col>end_lng</th><th scope=col>usertype</th><th scope=col>ride_distance</th><th scope=col>date</th><th scope=col>month</th><th scope=col>day</th><th scope=col>year</th><th scope=col>day_of_week</th><th scope=col>ride_length</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;date&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;ord&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>F3E84A230AF2D676</td><td>classic_bike </td><td>2021-11-15 09:35:03</td><td>2021-11-15 09:42:08</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St        </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave      </span></td><td>TA1309000014</td><td>41.95078</td><td>-87.65917</td><td>41.96710</td><td>-87.66743</td><td>casual</td><td>1940.643071</td><td>2021-11-15</td><td>11</td><td>15</td><td>2021</td><td><span style=white-space:pre-wrap>Monday  </span></td><td> 425</td></tr>\n\t<tr><td>2A81E957DD24A3DC</td><td>classic_bike </td><td>2021-11-06 19:14:10</td><td>2021-11-06 19:33:19</td><td>Larrabee St &amp; Armitage Ave </td><td>TA1309000006</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.91808</td><td>-87.64375</td><td>41.90096</td><td>-87.62378</td><td>casual</td><td>2524.130848</td><td>2021-11-06</td><td>11</td><td>06</td><td>2021</td><td>Saturday</td><td>1149</td></tr>\n\t<tr><td>A57F8F504A01004E</td><td>electric_bike</td><td>2021-11-18 11:58:24</td><td>2021-11-18 12:08:35</td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td><span style=white-space:pre-wrap>Michigan Ave &amp; Oak St      </span></td><td><span style=white-space:pre-wrap>13042       </span></td><td>41.90114</td><td>-87.62353</td><td>41.90100</td><td>-87.62375</td><td>casual</td><td><span style=white-space:pre-wrap>  23.674046</span></td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday</td><td> 611</td></tr>\n\t<tr><td>C79A70DFD07E75D9</td><td>electric_bike</td><td>2021-11-23 22:14:11</td><td>2021-11-23 22:44:01</td><td>Sheridan Rd &amp; Noyes St (NU)</td><td><span style=white-space:pre-wrap>604         </span></td><td>Sheridan Rd &amp; Noyes St (NU)</td><td><span style=white-space:pre-wrap>604         </span></td><td>42.05820</td><td>-87.67755</td><td>42.05825</td><td>-87.67752</td><td>casual</td><td><span style=white-space:pre-wrap>   6.625242</span></td><td>2021-11-23</td><td>11</td><td>23</td><td>2021</td><td>Tuesday </td><td>1790</td></tr>\n\t<tr><td>41E7F8FB5640B521</td><td>electric_bike</td><td>2021-11-05 16:48:10</td><td>2021-11-05 16:53:18</td><td><span style=white-space:pre-wrap>Clark St &amp; Grace St        </span></td><td>TA1307000127</td><td><span style=white-space:pre-wrap>Clark St &amp; Leland Ave      </span></td><td>TA1309000014</td><td>41.95086</td><td>-87.65913</td><td>41.96707</td><td>-87.66745</td><td>member</td><td>1931.724227</td><td>2021-11-05</td><td>11</td><td>05</td><td>2021</td><td><span style=white-space:pre-wrap>Friday  </span></td><td> 308</td></tr>\n\t<tr><td>3DEAAA1701BBD1D3</td><td>electric_bike</td><td>2021-11-18 08:40:38</td><td>2021-11-18 08:48:56</td><td><span style=white-space:pre-wrap>Desplaines St &amp; Kinzie St  </span></td><td>TA1306000003</td><td><span style=white-space:pre-wrap>Dearborn St &amp; Monroe St    </span></td><td>TA1305000006</td><td>41.88863</td><td>-87.64437</td><td>41.88160</td><td>-87.63013</td><td>member</td><td>1415.569490</td><td>2021-11-18</td><td>11</td><td>18</td><td>2021</td><td>Thursday</td><td> 498</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 6 × 20\n\n| ride_id &lt;chr&gt; | rideable_type &lt;chr&gt; | started_at &lt;dttm&gt; | ended_at &lt;dttm&gt; | start_station_name &lt;chr&gt; | start_station_id &lt;chr&gt; | end_station_name &lt;chr&gt; | end_station_id &lt;chr&gt; | start_lat &lt;dbl&gt; | start_lng &lt;dbl&gt; | end_lat &lt;dbl&gt; | end_lng &lt;dbl&gt; | usertype &lt;chr&gt; | ride_distance &lt;dbl&gt; | date &lt;date&gt; | month &lt;chr&gt; | day &lt;chr&gt; | year &lt;chr&gt; | day_of_week &lt;ord&gt; | ride_length &lt;dbl&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| F3E84A230AF2D676 | classic_bike  | 2021-11-15 09:35:03 | 2021-11-15 09:42:08 | Clark St &amp; Grace St         | TA1307000127 | Clark St &amp; Leland Ave       | TA1309000014 | 41.95078 | -87.65917 | 41.96710 | -87.66743 | casual | 1940.643071 | 2021-11-15 | 11 | 15 | 2021 | Monday   |  425 |\n| 2A81E957DD24A3DC | classic_bike  | 2021-11-06 19:14:10 | 2021-11-06 19:33:19 | Larrabee St &amp; Armitage Ave  | TA1309000006 | Michigan Ave &amp; Oak St       | 13042        | 41.91808 | -87.64375 | 41.90096 | -87.62378 | casual | 2524.130848 | 2021-11-06 | 11 | 06 | 2021 | Saturday | 1149 |\n| A57F8F504A01004E | electric_bike | 2021-11-18 11:58:24 | 2021-11-18 12:08:35 | Michigan Ave &amp; Oak St       | 13042        | Michigan Ave &amp; Oak St       | 13042        | 41.90114 | -87.62353 | 41.90100 | -87.62375 | casual |   23.674046 | 2021-11-18 | 11 | 18 | 2021 | Thursday |  611 |\n| C79A70DFD07E75D9 | electric_bike | 2021-11-23 22:14:11 | 2021-11-23 22:44:01 | Sheridan Rd &amp; Noyes St (NU) | 604          | Sheridan Rd &amp; Noyes St (NU) | 604          | 42.05820 | -87.67755 | 42.05825 | -87.67752 | casual |    6.625242 | 2021-11-23 | 11 | 23 | 2021 | Tuesday  | 1790 |\n| 41E7F8FB5640B521 | electric_bike | 2021-11-05 16:48:10 | 2021-11-05 16:53:18 | Clark St &amp; Grace St         | TA1307000127 | Clark St &amp; Leland Ave       | TA1309000014 | 41.95086 | -87.65913 | 41.96707 | -87.66745 | member | 1931.724227 | 2021-11-05 | 11 | 05 | 2021 | Friday   |  308 |\n| 3DEAAA1701BBD1D3 | electric_bike | 2021-11-18 08:40:38 | 2021-11-18 08:48:56 | Desplaines St &amp; Kinzie St   | TA1306000003 | Dearborn St &amp; Monroe St     | TA1305000006 | 41.88863 | -87.64437 | 41.88160 | -87.63013 | member | 1415.569490 | 2021-11-18 | 11 | 18 | 2021 | Thursday |  498 |\n\n","text/latex":"A tibble: 6 × 20\n\\begin{tabular}{llllllllllllllllllll}\n ride\\_id & rideable\\_type & started\\_at & ended\\_at & start\\_station\\_name & start\\_station\\_id & end\\_station\\_name & end\\_station\\_id & start\\_lat & start\\_lng & end\\_lat & end\\_lng & usertype & ride\\_distance & date & month & day & year & day\\_of\\_week & ride\\_length\\\\\n <chr> & <chr> & <dttm> & <dttm> & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <chr> & <dbl> & <date> & <chr> & <chr> & <chr> & <ord> & <dbl>\\\\\n\\hline\n\t F3E84A230AF2D676 & classic\\_bike  & 2021-11-15 09:35:03 & 2021-11-15 09:42:08 & Clark St \\& Grace St         & TA1307000127 & Clark St \\& Leland Ave       & TA1309000014 & 41.95078 & -87.65917 & 41.96710 & -87.66743 & casual & 1940.643071 & 2021-11-15 & 11 & 15 & 2021 & Monday   &  425\\\\\n\t 2A81E957DD24A3DC & classic\\_bike  & 2021-11-06 19:14:10 & 2021-11-06 19:33:19 & Larrabee St \\& Armitage Ave  & TA1309000006 & Michigan Ave \\& Oak St       & 13042        & 41.91808 & -87.64375 & 41.90096 & -87.62378 & casual & 2524.130848 & 2021-11-06 & 11 & 06 & 2021 & Saturday & 1149\\\\\n\t A57F8F504A01004E & electric\\_bike & 2021-11-18 11:58:24 & 2021-11-18 12:08:35 & Michigan Ave \\& Oak St       & 13042        & Michigan Ave \\& Oak St       & 13042        & 41.90114 & -87.62353 & 41.90100 & -87.62375 & casual &   23.674046 & 2021-11-18 & 11 & 18 & 2021 & Thursday &  611\\\\\n\t C79A70DFD07E75D9 & electric\\_bike & 2021-11-23 22:14:11 & 2021-11-23 22:44:01 & Sheridan Rd \\& Noyes St (NU) & 604          & Sheridan Rd \\& Noyes St (NU) & 604          & 42.05820 & -87.67755 & 42.05825 & -87.67752 & casual &    6.625242 & 2021-11-23 & 11 & 23 & 2021 & Tuesday  & 1790\\\\\n\t 41E7F8FB5640B521 & electric\\_bike & 2021-11-05 16:48:10 & 2021-11-05 16:53:18 & Clark St \\& Grace St         & TA1307000127 & Clark St \\& Leland Ave       & TA1309000014 & 41.95086 & -87.65913 & 41.96707 & -87.66745 & member & 1931.724227 & 2021-11-05 & 11 & 05 & 2021 & Friday   &  308\\\\\n\t 3DEAAA1701BBD1D3 & electric\\_bike & 2021-11-18 08:40:38 & 2021-11-18 08:48:56 & Desplaines St \\& Kinzie St   & TA1306000003 & Dearborn St \\& Monroe St     & TA1305000006 & 41.88863 & -87.64437 & 41.88160 & -87.63013 & member & 1415.569490 & 2021-11-18 & 11 & 18 & 2021 & Thursday &  498\\\\\n\\end{tabular}\n","text/plain":"  ride_id          rideable_type started_at          ended_at           \n1 F3E84A230AF2D676 classic_bike  2021-11-15 09:35:03 2021-11-15 09:42:08\n2 2A81E957DD24A3DC classic_bike  2021-11-06 19:14:10 2021-11-06 19:33:19\n3 A57F8F504A01004E electric_bike 2021-11-18 11:58:24 2021-11-18 12:08:35\n4 C79A70DFD07E75D9 electric_bike 2021-11-23 22:14:11 2021-11-23 22:44:01\n5 41E7F8FB5640B521 electric_bike 2021-11-05 16:48:10 2021-11-05 16:53:18\n6 3DEAAA1701BBD1D3 electric_bike 2021-11-18 08:40:38 2021-11-18 08:48:56\n  start_station_name          start_station_id end_station_name           \n1 Clark St & Grace St         TA1307000127     Clark St & Leland Ave      \n2 Larrabee St & Armitage Ave  TA1309000006     Michigan Ave & Oak St      \n3 Michigan Ave & Oak St       13042            Michigan Ave & Oak St      \n4 Sheridan Rd & Noyes St (NU) 604              Sheridan Rd & Noyes St (NU)\n5 Clark St & Grace St         TA1307000127     Clark St & Leland Ave      \n6 Desplaines St & Kinzie St   TA1306000003     Dearborn St & Monroe St    \n  end_station_id start_lat start_lng end_lat  end_lng   usertype ride_distance\n1 TA1309000014   41.95078  -87.65917 41.96710 -87.66743 casual   1940.643071  \n2 13042          41.91808  -87.64375 41.90096 -87.62378 casual   2524.130848  \n3 13042          41.90114  -87.62353 41.90100 -87.62375 casual     23.674046  \n4 604            42.05820  -87.67755 42.05825 -87.67752 casual      6.625242  \n5 TA1309000014   41.95086  -87.65913 41.96707 -87.66745 member   1931.724227  \n6 TA1305000006   41.88863  -87.64437 41.88160 -87.63013 member   1415.569490  \n  date       month day year day_of_week ride_length\n1 2021-11-15 11    15  2021 Monday       425       \n2 2021-11-06 11    06  2021 Saturday    1149       \n3 2021-11-18 11    18  2021 Thursday     611       \n4 2021-11-23 11    23  2021 Tuesday     1790       \n5 2021-11-05 11    05  2021 Friday       308       \n6 2021-11-18 11    18  2021 Thursday     498       "},"metadata":{}}]},{"cell_type":"code","source":"# analyze ridership data by usertype and weekday\ndf %>% \n  mutate(weekday = wday(started_at)) %>%  #creates weekday field using wday()\n  group_by(usertype, weekday) %>%  #groups by usertype and weekday\n  summarise(number_of_rides = n()\t\t\t\t\t\t\t#calculates the number of rides \n  ,average_duration = mean(ride_length)) %>% \t\t# calculates the average duration\n  arrange(usertype, weekday)\t\t\t\t\t\t\t\t# sorts\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:20:05.225414Z","iopub.execute_input":"2022-10-21T04:20:05.226763Z","iopub.status.idle":"2022-10-21T04:20:05.616251Z"},"trusted":true},"execution_count":36,"outputs":[{"name":"stderr","text":"\u001b[1m\u001b[22m`summarise()` has grouped output by 'usertype'. You can override using the\n`.groups` argument.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A grouped_df: 14 × 4</caption>\n<thead>\n\t<tr><th scope=col>usertype</th><th scope=col>weekday</th><th scope=col>number_of_rides</th><th scope=col>average_duration</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>1</td><td>287409</td><td>1614.8434</td></tr>\n\t<tr><td>casual</td><td>2</td><td>193059</td><td>1437.8708</td></tr>\n\t<tr><td>casual</td><td>3</td><td>189661</td><td>1252.5735</td></tr>\n\t<tr><td>casual</td><td>4</td><td>193386</td><td>1213.9254</td></tr>\n\t<tr><td>casual</td><td>5</td><td>210825</td><td>1251.6093</td></tr>\n\t<tr><td>casual</td><td>6</td><td>243104</td><td>1322.3779</td></tr>\n\t<tr><td>casual</td><td>7</td><td>359614</td><td>1588.4810</td></tr>\n\t<tr><td>member</td><td>1</td><td>290946</td><td> 830.5445</td></tr>\n\t<tr><td>member</td><td>2</td><td>361887</td><td> 714.5053</td></tr>\n\t<tr><td>member</td><td>3</td><td>417120</td><td> 702.8027</td></tr>\n\t<tr><td>member</td><td>4</td><td>411994</td><td> 707.0913</td></tr>\n\t<tr><td>member</td><td>5</td><td>401093</td><td> 716.1125</td></tr>\n\t<tr><td>member</td><td>6</td><td>366250</td><td> 727.5950</td></tr>\n\t<tr><td>member</td><td>7</td><td>338563</td><td> 839.8172</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA grouped_df: 14 × 4\n\n| usertype &lt;chr&gt; | weekday &lt;int&gt; | number_of_rides &lt;int&gt; | average_duration &lt;dbl&gt; |\n|---|---|---|---|\n| casual | 1 | 287409 | 1614.8434 |\n| casual | 2 | 193059 | 1437.8708 |\n| casual | 3 | 189661 | 1252.5735 |\n| casual | 4 | 193386 | 1213.9254 |\n| casual | 5 | 210825 | 1251.6093 |\n| casual | 6 | 243104 | 1322.3779 |\n| casual | 7 | 359614 | 1588.4810 |\n| member | 1 | 290946 |  830.5445 |\n| member | 2 | 361887 |  714.5053 |\n| member | 3 | 417120 |  702.8027 |\n| member | 4 | 411994 |  707.0913 |\n| member | 5 | 401093 |  716.1125 |\n| member | 6 | 366250 |  727.5950 |\n| member | 7 | 338563 |  839.8172 |\n\n","text/latex":"A grouped\\_df: 14 × 4\n\\begin{tabular}{llll}\n usertype & weekday & number\\_of\\_rides & average\\_duration\\\\\n <chr> & <int> & <int> & <dbl>\\\\\n\\hline\n\t casual & 1 & 287409 & 1614.8434\\\\\n\t casual & 2 & 193059 & 1437.8708\\\\\n\t casual & 3 & 189661 & 1252.5735\\\\\n\t casual & 4 & 193386 & 1213.9254\\\\\n\t casual & 5 & 210825 & 1251.6093\\\\\n\t casual & 6 & 243104 & 1322.3779\\\\\n\t casual & 7 & 359614 & 1588.4810\\\\\n\t member & 1 & 290946 &  830.5445\\\\\n\t member & 2 & 361887 &  714.5053\\\\\n\t member & 3 & 417120 &  702.8027\\\\\n\t member & 4 & 411994 &  707.0913\\\\\n\t member & 5 & 401093 &  716.1125\\\\\n\t member & 6 & 366250 &  727.5950\\\\\n\t member & 7 & 338563 &  839.8172\\\\\n\\end{tabular}\n","text/plain":"   usertype weekday number_of_rides average_duration\n1  casual   1       287409          1614.8434       \n2  casual   2       193059          1437.8708       \n3  casual   3       189661          1252.5735       \n4  casual   4       193386          1213.9254       \n5  casual   5       210825          1251.6093       \n6  casual   6       243104          1322.3779       \n7  casual   7       359614          1588.4810       \n8  member   1       290946           830.5445       \n9  member   2       361887           714.5053       \n10 member   3       417120           702.8027       \n11 member   4       411994           707.0913       \n12 member   5       401093           716.1125       \n13 member   6       366250           727.5950       \n14 member   7       338563           839.8172       "},"metadata":{}}]},{"cell_type":"code","source":"# Analyzed Dataset\nanalyzed_df <- df %>% \n  group_by(usertype, day_of_week) %>% \n  summarise(number_of_rides = n(), average_duration = mean(ride_length),  average_distance = mean(ride_distance)) %>%\narrange(usertype, day_of_week)\nas_tibble(analyzed_df)","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:32:34.769955Z","iopub.execute_input":"2022-10-21T04:32:34.776119Z","iopub.status.idle":"2022-10-21T04:32:35.231053Z"},"trusted":true},"execution_count":53,"outputs":[{"name":"stderr","text":"\u001b[1m\u001b[22m`summarise()` has grouped output by 'usertype'. You can override using the\n`.groups` argument.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/html":"<table class=\"dataframe\">\n<caption>A tibble: 14 × 5</caption>\n<thead>\n\t<tr><th scope=col>usertype</th><th scope=col>day_of_week</th><th scope=col>number_of_rides</th><th scope=col>average_duration</th><th scope=col>average_distance</th></tr>\n\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;ord&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n</thead>\n<tbody>\n\t<tr><td>casual</td><td>Sunday   </td><td>287409</td><td>1614.8434</td><td>2433.727</td></tr>\n\t<tr><td>casual</td><td>Monday   </td><td>193059</td><td>1437.8708</td><td>2270.612</td></tr>\n\t<tr><td>casual</td><td>Tuesday  </td><td>189661</td><td>1252.5735</td><td>2242.841</td></tr>\n\t<tr><td>casual</td><td>Wednesday</td><td>193386</td><td>1213.9254</td><td>2240.750</td></tr>\n\t<tr><td>casual</td><td>Thursday </td><td>210825</td><td>1251.6093</td><td>2268.423</td></tr>\n\t<tr><td>casual</td><td>Friday   </td><td>243104</td><td>1322.3779</td><td>2284.771</td></tr>\n\t<tr><td>casual</td><td>Saturday </td><td>359614</td><td>1588.4810</td><td>2473.236</td></tr>\n\t<tr><td>member</td><td>Sunday   </td><td>290946</td><td> 830.5445</td><td>2186.421</td></tr>\n\t<tr><td>member</td><td>Monday   </td><td>361887</td><td> 714.5053</td><td>2072.956</td></tr>\n\t<tr><td>member</td><td>Tuesday  </td><td>417120</td><td> 702.8027</td><td>2080.827</td></tr>\n\t<tr><td>member</td><td>Wednesday</td><td>411994</td><td> 707.0913</td><td>2095.610</td></tr>\n\t<tr><td>member</td><td>Thursday </td><td>401093</td><td> 716.1125</td><td>2094.768</td></tr>\n\t<tr><td>member</td><td>Friday   </td><td>366250</td><td> 727.5950</td><td>2069.064</td></tr>\n\t<tr><td>member</td><td>Saturday </td><td>338563</td><td> 839.8172</td><td>2226.435</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA tibble: 14 × 5\n\n| usertype &lt;chr&gt; | day_of_week &lt;ord&gt; | number_of_rides &lt;int&gt; | average_duration &lt;dbl&gt; | average_distance &lt;dbl&gt; |\n|---|---|---|---|---|\n| casual | Sunday    | 287409 | 1614.8434 | 2433.727 |\n| casual | Monday    | 193059 | 1437.8708 | 2270.612 |\n| casual | Tuesday   | 189661 | 1252.5735 | 2242.841 |\n| casual | Wednesday | 193386 | 1213.9254 | 2240.750 |\n| casual | Thursday  | 210825 | 1251.6093 | 2268.423 |\n| casual | Friday    | 243104 | 1322.3779 | 2284.771 |\n| casual | Saturday  | 359614 | 1588.4810 | 2473.236 |\n| member | Sunday    | 290946 |  830.5445 | 2186.421 |\n| member | Monday    | 361887 |  714.5053 | 2072.956 |\n| member | Tuesday   | 417120 |  702.8027 | 2080.827 |\n| member | Wednesday | 411994 |  707.0913 | 2095.610 |\n| member | Thursday  | 401093 |  716.1125 | 2094.768 |\n| member | Friday    | 366250 |  727.5950 | 2069.064 |\n| member | Saturday  | 338563 |  839.8172 | 2226.435 |\n\n","text/latex":"A tibble: 14 × 5\n\\begin{tabular}{lllll}\n usertype & day\\_of\\_week & number\\_of\\_rides & average\\_duration & average\\_distance\\\\\n <chr> & <ord> & <int> & <dbl> & <dbl>\\\\\n\\hline\n\t casual & Sunday    & 287409 & 1614.8434 & 2433.727\\\\\n\t casual & Monday    & 193059 & 1437.8708 & 2270.612\\\\\n\t casual & Tuesday   & 189661 & 1252.5735 & 2242.841\\\\\n\t casual & Wednesday & 193386 & 1213.9254 & 2240.750\\\\\n\t casual & Thursday  & 210825 & 1251.6093 & 2268.423\\\\\n\t casual & Friday    & 243104 & 1322.3779 & 2284.771\\\\\n\t casual & Saturday  & 359614 & 1588.4810 & 2473.236\\\\\n\t member & Sunday    & 290946 &  830.5445 & 2186.421\\\\\n\t member & Monday    & 361887 &  714.5053 & 2072.956\\\\\n\t member & Tuesday   & 417120 &  702.8027 & 2080.827\\\\\n\t member & Wednesday & 411994 &  707.0913 & 2095.610\\\\\n\t member & Thursday  & 401093 &  716.1125 & 2094.768\\\\\n\t member & Friday    & 366250 &  727.5950 & 2069.064\\\\\n\t member & Saturday  & 338563 &  839.8172 & 2226.435\\\\\n\\end{tabular}\n","text/plain":"   usertype day_of_week number_of_rides average_duration average_distance\n1  casual   Sunday      287409          1614.8434        2433.727        \n2  casual   Monday      193059          1437.8708        2270.612        \n3  casual   Tuesday     189661          1252.5735        2242.841        \n4  casual   Wednesday   193386          1213.9254        2240.750        \n5  casual   Thursday    210825          1251.6093        2268.423        \n6  casual   Friday      243104          1322.3779        2284.771        \n7  casual   Saturday    359614          1588.4810        2473.236        \n8  member   Sunday      290946           830.5445        2186.421        \n9  member   Monday      361887           714.5053        2072.956        \n10 member   Tuesday     417120           702.8027        2080.827        \n11 member   Wednesday   411994           707.0913        2095.610        \n12 member   Thursday    401093           716.1125        2094.768        \n13 member   Friday      366250           727.5950        2069.064        \n14 member   Saturday    338563           839.8172        2226.435        "},"metadata":{}}]},{"cell_type":"markdown","source":"From this Dataset we can infer that member riders have the highest number of rides during weekdays, peaking on tuesday while casual riders mostly ride during weekends peaking on saturday and  sunday. ","metadata":{}},{"cell_type":"markdown","source":"### Share \n\n* Create effective data visualizations.\n* Present your findings","metadata":{}},{"cell_type":"code","source":"# Let's visualize the usertype proportion\nggplot (data = df) +\ngeom_bar (mapping = aes(x = usertype, fill=usertype)) +\nlabs(title = \"Usertype Proportion: Member vs Casual riders\")","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:22:12.051445Z","iopub.execute_input":"2022-10-21T04:22:12.052943Z","iopub.status.idle":"2022-10-21T04:22:15.383112Z"},"trusted":true},"execution_count":44,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAABmJLR0QA/wD/AP+gvaeTAAAg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\n7ttEMny50Z5sFxHt5p96r5KPbjx6aff6ZavWbtj2y47d29bs+m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RB2AEAACiCsAMAAFAEYQcAAKAIwg4AAEARhB0AAIAiCDsAAABFEHYA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than half of Cyclistic customer base have signed up as members. This means there is significant increase in the amount of loyal customers who are ready to continue with the products and services of the company on an annual basis. \n","metadata":{}},{"cell_type":"code","source":"# Let's visualize the usertype proportion by rideable bike type\n\nggplot (data = df) +\ngeom_bar (mapping = aes(x = usertype, fill=usertype)) +\nfacet_wrap(~rideable_type)\nlabs(title = \"Usertype Proportion: Member vs Casual riders\")","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:22:28.585421Z","iopub.execute_input":"2022-10-21T04:22:28.586890Z","iopub.status.idle":"2022-10-21T04:22:34.513560Z"},"trusted":true},"execution_count":45,"outputs":[{"output_type":"display_data","data":{"text/plain":"$title\n[1] \"Usertype Proportion: Member vs Casual riders\"\n\nattr(,\"class\")\n[1] \"labels\""},"metadata":{}},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAABmJLR0QA/wD/AP+gvaeTAAAg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\nEAlhBwAQCWEHABAJYQcAEAlhBwAQCWEHABAJY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HDSbX+48zd7L73L+IpE4urzXu7cvvGtcx+e3rL6qV+05quXbXHIpX9e6we7n3jCuPWX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\nAACREHYAAJEQdgA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Let's visualize the number of rides by usertype and day of week\ndf %>% \n  mutate(weekday = wday(started_at)) %>% \n  group_by(usertype, day_of_week) %>% \n  summarise(number_of_rides = n()) %>% \n  arrange(usertype, day_of_week)  %>% \n  ggplot(aes(x = day_of_week, y = number_of_rides, fill = usertype)) +\n  geom_col(position = \"dodge\") +\n   labs(title = \"number of rides by Usertype and Day of Week\")\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:24:39.993479Z","iopub.execute_input":"2022-10-21T04:24:39.995055Z","iopub.status.idle":"2022-10-21T04:24:41.002952Z"},"trusted":true},"execution_count":47,"outputs":[{"name":"stderr","text":"\u001b[1m\u001b[22m`summarise()` has grouped output by 'usertype'. You can override using the\n`.groups` argument.\n","output_type":"stream"},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAABmJLR0QA/wD/AP+gvaeTAAAg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\nUyMufRti4pAB4DmePmToSa4TQI0X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Wp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\nxrJg1znpXlXusQlSuPvgWsKFX3RdH9OlQ8aZfqkXfEPataj29eQ+/ere36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,"metadata":{"image/png":{"width":420,"height":420}}}]},{"cell_type":"code","source":"# Let's create a visualization for average trip duration grouping by day of week and usertype\ndf %>% \n  mutate(weekday = wday(started_at)) %>% \n  group_by(usertype, day_of_week) %>% \n  summarise(number_of_rides = n()\n            ,average_duration = mean(ride_length)) %>% \n  arrange(usertype, day_of_week)  %>% \n  ggplot(aes(x = day_of_week, y = average_duration, fill = usertype)) +\n  geom_col(position = \"dodge\") +\n  labs(title = \"Average trip duration by Usertype and Day of Week\")\n","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:25:39.856655Z","iopub.execute_input":"2022-10-21T04:25:39.858246Z","iopub.status.idle":"2022-10-21T04:25:40.513067Z"},"trusted":true},"execution_count":48,"outputs":[{"name":"stderr","text":"\u001b[1m\u001b[22m`summarise()` has grouped output by 'usertype'. You can override using the\n`.groups` argument.\n","output_type":"stream"},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAABmJLR0QA/wD/AP+gvaeTAAAg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\nroV3yMMNfS0pCce+uJQQe27BscSU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sA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\n7tq1+4HU7KK7i5LCA1tR1HvfFQ9shQfSvUvFfHjoPt9ioNIci+jwUKlFKB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%>% \n  mutate(weekday = wday(started_at)) %>% \n  group_by(usertype, day_of_week) %>% \n  summarise(number_of_rides = n()\n            ,average_duration = mean(ride_length), average_distance = mean(ride_distance)) %>% \n  arrange(usertype, day_of_week)  %>% \n  ggplot(aes(x = day_of_week, y = average_distance, fill = usertype)) +\n  geom_col(position = \"dodge\") +\n  labs(title = \"Average trip distance by Usertype and Day of Week\")","metadata":{"execution":{"iopub.status.busy":"2022-10-21T04:27:59.466877Z","iopub.execute_input":"2022-10-21T04:27:59.471460Z","iopub.status.idle":"2022-10-21T04:28:00.277935Z"},"trusted":true},"execution_count":52,"outputs":[{"name":"stderr","text":"\u001b[1m\u001b[22m`summarise()` has grouped output by 'usertype'. You can override using the\n`.groups` argument.\n","output_type":"stream"},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAABmJLR0QA/wD/AP+gvaeTAAAg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\n++M8XRp3LYPD7C6bny1HSJaPai2S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vQ\nkhwdKyJ/xSQF1w6yJ8RcuBSlpnhIUvSW04n2Ni2KOSctwU1r+nvt2HzR3Xgu7AUAAEAelxtn\n7LwCm06b1tQ1aY09+Mm52NL9IkRkT6xV/W3GkzMPWlXV5Ffoke4vPvdYDRFJjvtbRKr43iqv\nqq/pp3+jk5umP+6aPHXq1K5du1yTDRs2DAhwBco8xGg0iojBYPD29vZ0LR7jbIKIWCwWVVUz\nXljHFEUREbPZnJ+bYDKZhN+IFL8RDofDs8V4kPM3wmQy5eeDwfkboShKnm1CUlKSp0tA+nLp\nPXYuJ3d8P3PGQlvZtq89FG5PPhtrNJcObTR5yZtB6vU/137y3vwxlvKf9a4U5EiKE5FQ861P\nRYSajdYYq7tx1+TevXsnTZrkmly8eHHRokVzY8eyxGg0+vv7e7oKz/Pz40q6eHl5eXl5eboK\nDzMYDPxGiIivr6+nS/A8fiMkb/9GEOzyrNwLdknXDn4yfeYPeyObdx74VvcW3ooiXuHLly+/\nOd/StOuIwz/s2vjxv73fb2Kw+IpIpNUR5nXjYvEVq90UbHI37tqK2WwuUKCAa9JgMOTNsyDO\n/5KKSN4sL9c4+0AThCbwGyEiHAwiwsEgIjQBdyGXgt31E+uHvTLbWKPNu/N7Vgx1e2K5dhGf\n9ZGXRcTsW11k88EEa5iXxTnrcIItsGqgu3HXGtq0adOmTRvXZFRU1NWrV3Nkl+6Ov7+/t7e3\n1WqNjo6+89I6ZTabAwMDReTatWv5+cJTSEiIwWCIj49PSEjwdC0e4+fn5+PjY7PZoqKiPF2L\nx5hMpqCgIBGJioqy2+2eLsdjgoODjUZjfHx8fHy8p2vxGF9fX19fX7vdfu3aNU/XgntMbnx4\nQnXEv/Xqh5aWL8x5vX/KVBd1ePazfQddSHa9ojs2n4sPqlJBRLyDHgz3Mq7ddtk5wxq7e+f1\n5DoPhrkbz4W9AAAAyONy44xd/IXP98dbn63ht2vnTteg2ad89YpdC8YPGDlu3uDuLYKUhF0/\nL94SF/B63woiIop5WOdKrywYt7HIiEpBSatmTvELf6hHMT8RcTcOAACQzym5cP3+3C+vDpi6\nL9VgYNmxn0+rl3Rt38K5S7buPZJoDChbvlrHZ/o3LHnzjaKq/efPpi37efvVRKVczeYDhvWL\ncH4Y1t14eqKiomw2W07t2F3gUqykuBQbGRnJpdi4uDguxXIp1nkp9tq1a1yK5VJs3r8UGxoa\n6ukSkI7cCHYeRLDLywh2TgQ7IdiJCMHuJoKdEOxwF3LjPXYAAADIBbl9HzsAAO4tAe+9mfsb\nTRIxTZqa+9vFvY4zdgAAADpBsAMAANAJgh0AAIBOEOwAAAB0gmAHAACgE30v5vwAACAASURB\nVAQ7AAAAnSDYAQAA6ATBDgAAQCcIdgAAADrBN0+IeO6u4oaJH+T+dgEAgF5xxg4AAEAnCHYA\nAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6\nQbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6QbAD\nAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQ\nCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQCYId\nAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOiEydMFAADyroD33szlLdpEbCLyxju5vF1A\nHzhjBwAAoBMEOwAAAJ0g2AEAAOgE77HDDbn/ThoRSRKxTJ6R+9sFAECXCHYAkA7+qwPgXsSl\nWAAAAJ0g2AEAAOgEwQ4AAEAndP4eO7PZbDLl3X00GAze3t6ersLzLBaLqqqersJjFEUREbPZ\nnJ+b4Pw95TfCyWKxOBwOT1fhYSaTiYNBUZQ824SkpCRPl4D05d3Qky3MZrPBcOezkvZcKCU9\neeplzFNNEBGLxeK5jXueM9iZTCYtx6peOfc9T72MefY3Iu+kfE/1IU/9RniqCXnqNyIVgl2e\npfNgFx8fb7PZ7rhYQC6Ukh6bzRYdHe2hjafmqSaISExMTH4+PxESEmIwGBISEhISEjxdi8f4\n+fn5+PjY7faoqChP13KDZ38j7HYPBsvbeKoPiYmJ8fHxHtp4ap5qgsPhyDu/EbhX6DzYAZni\nkTtcWJ3/vP527m/aHU/d6cP41pTc3y4A6EleOdENAACAu0SwAwAA0AmCHQAAgE7wHjsAAPIc\n7zZd5dc/cn+7l6tVzP2NIhtxxg4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAA\noBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6wVeKeYx3m66ydXvub5eviwEAQK84YwcAAKAT\nBDsAAACdINgBAADoBMEOAABAJwh2AAAAOkGwAwAA0AmCHQAAgE4Q7AAAAHSCYAcAAKATBDsA\nAACdINgBAADoBMEOAABAJwh2AAAAOkGwAwAA0AmCHQAAgE4Q7AAAAHSCYAcAAKATBDsAAACd\nINgBAADoBMEOAABAJwh2AAAAOkGwAwAA0AmCHQAAgE4Q7AAAAHTC5OkCAEBExLtNV/ntz9zf\n7uVqFXN/o+54t+kqm7Z6ZNN5qg8AsowzdgAAADpBsAMAANAJgh0AAIBO8B47wPO823SVHX/l\n/nZ5WxUA6Axn7AAAAHSCM3bwJD4DCABANiLYAQDyFu82XWX7ntzfLv/fgw5wKRYAAEAnCHYA\nAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6\nQbADAADQCYIdAACAThDsAAAAdMKUO5tRbddWzp+3btveq4mGoiXKt+8x4JHaYSIi4ti0dM7q\nLbvPXDdWrnZ/7yF9yvgYbz7I3awMHgIAAJB/5dIZu58mDV+86UK73kMmTxjZolzSnHGDVp2J\nFZHj34yZuuz3hp36vfFST99j60cPna/efIi7WRk8BAAAID/LjTN29qQzc3ddaT7p/Q5Vg0Wk\nfKXq57d3XTX3YIeJNaYsOxDRY0rnVmVEJGKydOn13pfne3Qv6idqcvqzwsxuHwIAAJC/5cYZ\nO3viyVJlyrQtG3BzQKkdaEmOjk2K3nI60d6mRTHnqCW4aU1/rx2bL4qIu1kZPAQAACCfy40z\ndl6BTadNa+qatMYe/ORcbOl+Eclxy0Wkiu+tGqr6mn76N1pEkuP+TndWctP0x12Te/fu/f77\n712TPXr0KFSoUE7s1L3L39/f0yXkCfRBaIKI0ISb6IPQBBHR3IS4uLicrgRZk0sfnnA5ueP7\nmTMW2sq2fe2hcOvJOBEJNd/66EOo2WiNsYqIIyn9We7GXZOnTp1asWKFa7JTp04lSpS4Y1VJ\nd7NL9xpvb+90x/NVE8RNH2iCU77qA01wog9CE0TEfRNSIdjlWbkX7JKuHfxk+swf9kY27zzw\nre4tvBXlusVXRCKtjjCvG1eEr1jtpmCTiBjczHI37tpKUFBQ5cqVXZNms9lms+XG7t07aIgT\nfRCaICI04Sb6IDRBRGjCvS+Xgt31E+uHvTLbWKPNu/N7Vgy98b8Bs291kc0HE6xhXhbnyOEE\nW2DVwAxmZfAQp2bNmjVr1sw1GRUVFRUVdcfyAu64hI64a0i+aoK46QNNcMpXfaAJTvRBaIKI\nuG8C7hW58eEJ1RH/1qsfWlq+MOf1/q5UJyLeQQ+GexnXbrvsnLTG7t55PbnOg2EZzMrgIQAA\nAPlcbpyxi7/w+f5467M1/Hbt3OkaNPuUr1k1cFjnSq8sGLexyIhKQUmrZk7xC3+oRzE/ERHF\n7G6W24cAAADkb7kR7KIPnRSRBZPfSjkYWHbs59PqRXSd+HzStC+mjL2aqJSr2XzCsH7KzQXc\nzcrgIQAAAPlZbgS7Yg++/d2DbuYpxod6DXuoV2ZmZfAQAACAfCyXvlIMAAAAOY1gBwAAoBME\nOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAA\nAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g\n2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEA\nAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgE\nwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4A\nAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAn\nCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnTJ4u\nIGd5e3t7uoQ8x9/f39Ml5An0QWiCiNCEm+iD0AQR0dyEuLi4nK4EWcMZOwAAAJ3Q+Rm7xMRE\nm812x8UCcqGUPCM2Njbd8XzVBHHTB5rglK/6QBOc6IPQBBFx3wTcKzhjBwAAoBMEOwAAAJ0g\n2AEAAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEA\nAOgEwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgE\nwQ4AAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4A\nAEAnCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAn\nCHYAAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYA\nAAA6QbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6\nQbADAADQCYIdAACAThDsAAAAdIJgBwAAoBMEOwAAAJ0g2AEAAOgEwQ4AAEAnCHYAAAA6Ycrl\n7S0a2Mv7zbndCvk4Jy/+Prrf2/+kXOCZhcs7FvQWERHHpqVzVm/Zfea6sXK1+3sP6VPGx5jh\nOAAAQL6Wm8FOPfrbwpXnorqoqmso6q8on4KPvdivqmukVIDZ+cPxb8ZMXXaqx6DBzwTb1syb\nPXqobcmHAxT34wAAAPlcLgW7C79OG/PR1kvRSanGL+2PCarSqFGjqqkfoCZPWXYgoseUzq3K\niEjEZOnS670vz/foHmZOf7yoX67sBwAAQN6VS++xC6nRedQbb78/eWSq8b9ikoJrB9kTYi5c\nilJTjCdFbzmdaG/Tophz0hLctKa/147NF92N58Y+AAAA5G2ZO2N3aMOyL3/8/fSlyGaT53Yz\nb/vzXI3m1QpreaBXYPGIQLEne6ca3xNrVX+b8eTMg1ZVNfkVeqT7i889VkNEkuP+FpEqvrfK\nq+pr+unf6OSm6Y+7Jrdt27Z48WLX5IgRI8LDw+9YnkPLPuhFYGBguuP5qgnipg80wSlf9YEm\nONEHoQki4r4JqcTExOR0Jcga7cFOndOnyaBF25wTvmNnPBo748Haa5r1nbl+3iBTlt7jZk8+\nG2s0lw5tNHnJm0Hq9T/XfvLe/DGW8p/1rhTkSIoTkVDzrU9FhJqN1hiru3HX5JUrV7Zv3+6a\nTExMNJvNd6wk9RViXXPXkHzVBHHTB5rglK/6QBOc6IPQBBFx3wTcK7QGu2NLOg1atK3loGlT\nXupSs3y4iASXf3dS/6uvzhvcvnbLtQMrZWHbRq/w5cuX35yyNO064vAPuzZ+/G/v95sYLL4i\nEml1hHnduFh8xWo3BZvcjbvWWapUqU6dOrkm/fz8EhMT71hJvvrshbuG5KsmiJs+0ASnfNUH\nmuBEH4QmiIj7JuBeoTXYTRz2c0jlUetnvXjrkb6VRs3dmrwtdPK4CTJwSbZUU7uIz/rIyyJi\n9q0usvlggjXMy+KcdTjBFlg10N24aw01a9asWbOmazIqKio2NvaO2w3IlurvEe4akq+aIG76\nQBOc8lUfaIITfRCaICLum4B7hdYPT3x9JaFc7+5pxx/vWTbx6uqsbTvq8Oxn+w66kOx694Jj\n87n4oCoVRMQ76MFwL+PabZedM6yxu3deT67zYJi78awVAAAAoCdag11Ji/H6kXTeKXltX7TR\nUixr2y5QtmvB+Isjx83b8e+hI/v+WjptxJa4gP59K4iIKOZhnSsdWTBu4+7D547/8/HYKX7h\nD/Uo5ud2HAAAIN/Tein2tfsL917c84+39zUIvfXJ1vhzG/ssOx5a56OsbdtgCp0we/zCuUtm\nTByTaAwoW77aiKnjavvfeNtmRNeJzydN+2LK2KuJSrmazScM66dkOA4AAJDPaQ12nZZ99Hqp\nDs3L1Or9XHcR2bf0kwlRfy+Ys+Sso+jSr57UuBKjV/Hvvvsu5YgluOqAVycNSHdpxfhQr2EP\n9dI8DgAAkL9pvRTrU6jtnr3fPVHP8PGUcSKyacywNz5YHNCgy8o9fz/Btz4AAADkAZm4QXGB\n8m2+2NhmweUT+46dsxl9ipevWjzIknOVAQAAIFMy/V2xPoXK3FeoTE6UAgAAgLuRie+KvbLr\n235PPNT721POyfWP1G74aI/l2y/nTGEAAADIHK3BLvrIRxUaPPHJ6l1m7xsPCalT/tTGpU81\nLv/hgWs5Vh4AAAC00hrsFjz+WpxP7S2nz85vXcI5Uuft5cdPb7vfN3Fslyze7gQAAADZSGuw\nm3o0OqLnrMZhPikHvQvVmzGgYtSR6TlQGAAAADJHa7Czq6pXoFfacaOvUcSRdhwAAAC5TGuw\nG1y6wKF5Y84k2VMOOpLPj5t1MKD4czlQGAAAADJH6+1OBnwz9q1aw6tWajFsaJ/GNSJ8DdYT\n+//8dMo766/axq0dnKMlAgAAQAutwS6k2sv7Vhu7PDd63JAtrkHvkErjv/xqbL1COVMbAAAA\nMiETNygu3WbIjlMD/v1j856Dp+LtpqJlqz7Q/L4CRiXnigMAAIB2mfvmiciz/5lDStZvVNI5\nef7o4fMiIlKxYsXsLgwAAACZozXYJV5Z/0STrmsPRaY7V1XV7CsJAAAAWaE12H3Uoce6I9fb\nDRzVukZpE1dfAQAA8h6twW7ijstlu65YPad9jlYDAACALNN0HzvVfv2y1V6qa42crgYAAABZ\npinYKUb/B4K8jy/amdPVAAAAIMs0fvOEsnTNhOR1T/ee8OnFOFvOVgQAAIAs0foeu86jVhUp\nav709d6fvfFsSFiYz+23rztz5kwO1AYAAIBM0BrsQkNDQ0NblaqVo8UAAAAg67QGu5UrV6Y7\nrjrir8dlXzkAAADIKo3vsXPrv/WPFyxUOVtKAQAAwN3QesZOtcfOeqnfpxt2Xk247cMTF06f\nUnyq5EBhAAAAyBytZ+z2vPnAkFlLY4LKVChqO3nyZKUatWrWqGS6ek4JeXDOqh9ytEQAAABo\nofWM3Wsz9xWsNvHwttGqPbasf3CTWZ+NLhGQcGlztTJtY4v55WiJAAAA0ELrGbtfY5JLd2sn\nIorRv0dh3427r4qIT+Hmn/UuPbHz/BwsEAAAIAdc+nPMY489ti0m2dOFZCetwS7YpFivW50/\n31/c7+yqs86fS3UqHnV0ao6UBgAAkGPiL/y+Zs2aC1a7pwvJTlqDXd/wgKML3zmTZBeREu3D\n/1v7kXP8woaLOVUaAABAdnPYou4myqn2ZLuabcVkO63B7rlP+iVcXlEutOSJRHu5nn3jL33e\nsM+I9958ud0H/4ZUHZmjJQIAAN0bUaJAgRIjUo78Nb6uoignk27EMIf1yuxRz9QoF+ZtNhco\nWKJl1yF/XEl0LRx7astL3R4pWSjI4hdSqXaL8fPWOlKsamHFgsHlpiZFbX/6gSr+lpBYuzqp\nTFCZjhtF5IlQ3wIlRhyY01hRlJlnY1M8yNEy2Me/6DPOCV+jodHcvbNebBfq52s2ehUqUbXn\niNlXrA6NBeQarR+eKNr83T3fFB0/b7VBEb+iz3350tf/m/b+H6paoNwjX//wXI6WCAAAMK1t\nreEbLjzYtX+XviViTu+cO392q19PXzv7rVmRuHPf1qr85Gkl/H99+kWEGvdu+mrcgEe/3bZw\nz6e9XQ932CJ71Wp9tWmPSTOG+BiUpz5dUXzDsF5v/jVm+XcPFK5YtmZrw+BW897d98L0+53L\nx5ycvDEqscmHt7LmgVlthuy//FCXXvXLB/295evP3xv88++n//t1slE0FZA7tAY7Ean5+Msr\nHn/Z+XPXKT+3efnwiTjvKhVLmpWMHwcAAHBXbAmHX9lwrkTrrzd82ck50imgcfuFW1dcSeha\nyOf9h/ueViI2n97dsKC3iIi88+2w2o9P6fPWG4+PLhvoXP76mbeiZuz8eXAd52SZZi2UayEi\nUrtFq5YFfUQqDAn3n7f4TZn+vXOBP0YtUAyWaU+Xc9UQte/8kK8OTO9cSUREnbzw+drPzH23\n7+YXFzYvpqWA3JH1b54oUKJCzUqkOgAAkOMUg4+XIlEHVuw8c9050vDdrZcvX+5ayMcWv2/C\n/shKAz+9GapERNq+Pl1Eln14OMUqLJ89l9F33vcfXSMhcu2CC3EiojriXlp9umC1t+v6m10L\n+BXpcSPViYhi6jF1pa/R8OOr27QWkCu0BruGDRu+/19s2vEL24Y0bdEjW0sCAAC4jdFS4se3\ne6hnvqxfKqhMjUb/6z903tIfI22qiCRGrrOr6j8f1FdSsAQ1F5Hof6Jda/Dyr1XYnFHsKfvU\nBIOizJx+UESu7B1xIN768LSuKRcIqtg95aTJO+LREO/rp37RWEDuuMOl2JgTR88n20Xkjz/+\nKHvgwKG4ArfPV//9fsu2X0/mVHUAACC/Uh23ffq02YhPL/V+9dtv12za8tvWnxd9MX/q0Jcb\nfPvvLw0NXiJSfcQn77UolmoNlsBbp+gUwx2+T8ES+OBLxf3nLnhH3v5q/curTJaSM5qG3baE\nkvoypVkR1ZEk2grIHXcIdt+0vv+Zw5HOn794uP4X6S1ToPSg7K4KAADkQ7fdh+TizkjXz9bY\nQ7v3RRWsWbdb/+Hd+g8XkQPrJlRp+/qLY/b8PbWtUXnJFlXxkUcauZa3JRz85ru9YTV9M7X5\nfmNqTnnu68Vnjw7ddqF4m5UFTbed4Ys6tEzkkVu1Jp1afTXRr0Zz75CG2VXA3btDsGv05pS5\nUYkiMmDAgOYTpj5VyCfVAgZzQMMnOudUdQAAIH/wNRoSL39/xfpeqNkgIolX/3h+41nX3LiL\nHzZoML32G9t3j6vnHCl9Xz0RscXZTN4R46qEjP+814bxe1uG3QhSXw7q0GvRkU8vpPMuslTU\nFKcFy3Z9yzjggVHPPXbZah/8QdNUS8ZdWPjKqtfe6xAhIiKOpSM6Xrc72kxsbvIueTcFZK87\nBLuKXXtVFBGRpUuXdnym73PF/HOhJgAAkN+071Fh/MQdNVv0HPF0C+uFg4umTL8Y6iX/2Zxz\nA0uPb1Xoow0TmrU93qdB1bKOqJPffvyJ0Vxw3KTaIvLS2jnzK/yvTblqj3drX7d8yL8bl33+\n8+HqvT/vUTijE2bmALOIfDTz46TK9bt3u19EvAKbvVwi4P3vD3oHtRgTEZRqeb/wutOfqHrg\nqWfqRwTu3bR8xaYTheu/+HmbklkuICdo/fDEL7/88mIx3/PHjzgnEy/teOOVQUNGv/Pz8es5\nVhsAAMgvao/fNGvoUwFnNrwysO8r496Lqt7tp+XNXXMVY+B3/6wf3KXJvnVLJrw2asr8VUFN\nun+9/VD34v4i4l/yyb//XvPMwyW3rFgwdsL0HZdD3pi/bvcnT2e8xcL3T25Xp/SWt4YOf/tH\n12DfMTVEpOLAyWkTUuF67+3/dsK1Xavfnjhl02Gv7kOn7v1tipciWS4gJ2i9j11y9O/dm7b7\n7lhYctw+1XatQ5XmP11NEJEPp8xbdOif/5XkTB4AAMg6xeA76IMvBn0gjqSY/y7bShYPkduv\nk/oUaTRj6c8z3Dw8sMIjc1c+MtfN3D6HrvZJM2j2q7l614lUg9dPXFcUZfywaumuJ6LdiK3t\nRqQ7K+MCco3WM3ZLO3ZZuT+519AXROTSrpd+upowaO3hayd+rWM+N7zr8pysEAAA5CMGSwFn\nqst9DuuVQbMOBJR4uUOKO9LdW7SesZu0/VKp9t/On9BWRP6euMUS2HR6m/JGKT/96Yhmn00R\neSYniwQAAMhZz78wLP7Iiu3Xk59dMdTTtWSd1mB3OslWrWEJ58+fbr9csMZUo4iI+JX1syX8\nkzO1AQAA5JLNyz46YQvsMfarj1uFp537eOfOQfcVyv2qMktrsGtcwLL/+7/klepJUT9/eTm+\n7aIbX7W2c9V/Zt9KGT8WAAAgj9t3KaPPgy5Zdm+88UxrsBvfu0KTaX0e67vL9OfniilkUrOi\ntsSj8z/44MWtF4q0+CBHSwQAAIAWWoNdg3c3jjvbetLCGVbFp8+U36r7mWPPrnp+zFz/4k0X\nf9UpR0sEAACAFlqDncFU8PVlO16LvxJnDAm0GETEO7jNt+saPvBQw0Bj6q9OAwAAQO7TGuxu\nLO0bGnjr5yodWmd7PQAAAMiijIJd7dq1FYNl964/nD9nsOSePXuyuS4AAABkUkbBzt/fXzFY\nnD8HBaX+xjQAAADkKRkFu19//dX18y+//JLzxQAAgPzo+vWc+ur5gICAHFpz3pS599gBAADk\nBK+Jo7N9nclj3sr2deZxGQW7VatWaVxLhw4dsqMYAAAAZF1Gwa5jx44a16KqanYUAwAAgKzL\nKNht2rTJ9bPDemns/3rvSCj2zAv9WzSoFmRMPLLv97nvzjxfovOmtVNyvEwAAADcSUbBrnnz\n5q6ffxlQbUd8+S2n/rw/5MbnZB9q+3j/QX0eKFq78+geBxY8nLNlAgAA4E4MGpcb8cWRck9/\n6Ep1TibfylP7Vji2bHgOFAYAAIDM0RrsjibYDF7pLWwQe9J/2VkRAAAAskRrsHuykO/Rz0ae\nTLKnHLQnnX5twRHfwt1yoDAAAABkjtZgN3pu96SozTWrtZn2+co/9hw48Nefq5bMaFu9xvpr\niU99OCpHSwQAANATX6Ph2SPXcmLNWm9QXLL9vI3TTE+OmPdyz59dg0avQs9P2zC7fcmcqAwA\nAACZkolvnnjwxdnnnnnlxzU//3vsnNXgHR5RvVXbh0v631pD80rlNx88kgNFZp2vr6+iKHdc\nzJELpeQZgYGB6Y7nqyaImz7QBKd81Qea4EQfhCaIiPsmpBITE5PTlSBrtF6KdTIHlG73VL9R\nY94Y+9rIZ55smzLVich/p05mZ2nZwWazJWvg6TJzFU1wognCwSAiNOEm+iA0QUTcN0GXPbHG\n7hvRvU2F8CDfoLCHuo/cH2d1jidc/G3g483CgvxNFt8y1Zq+881h5/jJH+Y+Wq9KiJ+lUHjZ\nbsOmXberIiJqkqIob5259V23IWaj8zKru/XkKJ1/V2xycrLNZrvjYvnq+4ETEhLSHc9XTRA3\nfaAJTvmqDzTBiT4ITRAR903QITW5X+3Ga/zazF/4fZjp0vSBzzRrZLiy920ReaVRu29Cuy38\n7r1wH9umJa8M63b/03FXCiduq9Fu0AOj562dWzf+9O89nxrSvnzrXwZUymAL6a6nuJcxR3dL\n58EOAAAgrcgDr3x2PPmXyE+bB3qJSPWNF9t0W3LZ6ihkNpQd8NqC3i88WshHRCqVe+3l6Y/9\nHWdtEv3Ddbvj+ee7NyjiK3Vrr/+m6NGA4Iw3ke56CHYAAADZ7L/vtnkHP+xMdSLiHz7g118H\nOH9+eehzG1d9/e6+QydPntjz65qbC7zcve6CdiXLNG/zcJPGjR9q07FdtSIZbyLd9eS0zL3H\nDgAAQAccSQ7F4J123J505tGIEt0mLI02hjZt9/TMr79wjhvMoUt2ntu7YWH7esUPbFjUqmbx\nNqN+TvtwEUeymtF6chpn7AAAQL4T3q5G4oRvdsVa6/qbRST+4uflao344uDJ6ieH/XA66fzh\n1UXMBhGJv7TEufyFzR9MXm2b+v7Iqk3avijy7/QGdceMkHf2OOdGWm98eDru/BdxdoeIXDuY\n/npyGmfsAABAvhNaa+ZjRRxtH+q/5pcdu7eue/7hl5MCn3gw0GIpqME3RgAAIABJREFUWE91\nJH+wbPOp/05s++HTbi1Gisi/xy6aikRP+2DUM+8t/mPPP9s3r5r80eHAik+KiCiWBgUsy557\nZ/fhU//8vq5PqyEGRRERd+uxZ1jV3eOMHQAAyHcUo/+yfzYO7/fai91bXbYH1m3Vd9PcN0Uk\noPgrP7x7csirT86MMdWs32r8in2F/1dtdOPqj16LXPfBtZGzhjV7NTIwrGTdB/tvmjvcuapV\nP87o1vftJlXeTbA7mjw7p8OlYRmvp6pvDqYvgh0AAMiPLCH1Z36zfmaa8UdemX3oldm3Jnec\n+VhERKoOndl6aNrFpXCD/hv/7a86Ei5ek7CCPvLxwIzXIyLx9py67zXBDgAA4G4pBp+wgp4u\nInvfYzdu2oxsXBsAAAAyJXNn7A5tWPblj7+fvhTZbPLcbuZtf56r0bxaYdfcHs8NzO7yAAAA\noJX2YKfO6dNk0KJtzgnfsTMejZ3xYO01zfrOXD9vkEnJofIAAACgldZLsceWdBq0aFvLQdP2\nHjnrHAku/+6k/g03zx/cfu7BHCsPAAAAWmkNdhOH/RxSedT6WS/WiCjmHDH5Vho1d+v46gU3\nj5uQY+UBAABAK63B7usrCeV6d087/njPsolXV2drSQAAAMgKrcGupMV4/UhM2vFr+6KNlmLZ\nWhIAAACyQuuHJ167v3DvxT3/eHtfg9Bb35gbf25jn2XHQ+t8lDO1AQCA/CJ5zFueLkEPtAa7\nTss+er1Uh+ZlavV+rruI7Fv6yYSovxfMWXLWUXTpV0/mZIUAAED/Cuz6O9vXGVO3RravM4/T\neinWp1DbPXu/e6Ke4eMp40Rk05hhb3ywOKBBl5V7/n6iqF8OFggAAABtMnGD4gLl23yxsc2C\nyyf2HTtnM/oUL1+1eJAl5yoDAABApmgNdnFxcTd+8i1cubrz2yZscXE2k9li8eILZwEAADxP\naybz9/d3N8tg8g0vU+7+5o88N2x0q0pB2VQYAAAAMkfre+zmfjijTqBFMXjVbvFY/0FDXhw8\n8PGH7rMYlNA6XQYP6NmgcqHfFk97pHqZ+Uejc7RcAAAAuKP1jF29q18NTgr7cvfOrjVDXYOR\n/3xdr0Ev/0mHlz8Snhxz6Okq941+ckm/3c/nTKkAAADIiNYzdi+9t73c/xanTHUiElK98+Je\npab1GCoiXgUqvju7ftTB6dlfIwAAADTQGuz2xVt9S6RzWxO/kn6J135y/uwT7mdPPpdtpQEA\nANzL4i8uUBTlZJI917aoNdg9G+5/aPb4M7dX5kg+9+a0A/7Fejsn1038xzukbfbWBwAAAI20\nvsdu5Mo3PrzvlSrlmw4c0O2+SqUsknTq0O7l82b/ftX4wY4xSdG/dHq079qtJx+buy5HywUA\nAMhWdqvDaNZ6pivbH54R1RarmNzeliRdWgspWGvooV8WNAo++d7oF7s+0bHjE11ffG3yPq/a\n8zYeeKlWQVv8/l+PeQ14Z8V3z1XKfNkAAAC5rZjFNOanBbXDAiwmc1jE/R9tv7xj4bCKYcEW\n/9CGnYdG2lTnYvbks5Oef7xM4SCLf0j15l0WbbuQqYeLSPThla1qlfbx8g6v1ODNxXsyXq2I\nhJiNM0+fHtrlwbDw7pndqUwkzGJNe/+499y5w7vXfrfy65Wrf/vr6OVDW55tHBRzPd6v6PMx\n5w98OPLxzG4eAADAU6Z0mjLgk/WH/9nayffY802rP7FcWfTT9k1fjv3n2+ndV59yLjO6aZ0P\nfjVNXLTy9w0rn2ugPtss4uMj0dofLiLtmoz8f3v3HdhE/f9x/J2kTdu0pS1tgVJ2C7KHooiC\nDEER2aJMKVO+gigIXxyAzB+IIFsEFJQlQ1ARRBREhoKgFkWQAl9A9igdlNKVNvf7I1AqNmla\nKUk/eT7+Sj6Xu3vfO5fk1Uvu2uSVGdu/2zCksee4XvXH/HTF/mJFZF3/pwNbj9i5d1F+tyjf\n/zQirHK9sMr1su+e3dqxUrsYc9ppO7MAAAC4oPtnfTaw9X0iMmpO/QXNt361/u1aJg+p/crQ\n8Le+/CFWOlZIPj/jnZ+v7kxc2biYUUTub9DE/GXwhEE/9t/a2pHZb65l0dYxXSqJSMPGT8bv\nLv5+v1WvfZtlZ7EicqXi7Lf6NC/AFjka7LSs5HlDByz97pe41Myc45fOnNb5VC/AigEAAJyr\n5KM3r+NmDDIavMrVMt3MRcEees2iiUhizDeaZnkswCvnXIEZMSKtHZndasiT4dm3e/aJmDP5\n08QYXzuLFZHI3gUMV44GuwMTmr4879fKDVtWCTzy7d5zrdp18JK0w99v1xVvNn/10oKtGwAA\nwGXk8vs0zwAfvUfgjeRLuhyDOl2u8cnmz9tyzmssbtTpvfJcbLHiRkerdrCIO7w593BwzUnH\n9ny7ZfeRCt4ejeYt+2LD1wf/921Yyk/JpXO5vh0AAEBRF1BpgJZ1bf6ZNK+bjKOefrz/ypP5\nWsi8rbev8rti9tHA+3rdlcXmytFgtzspo0LXNiKiM/g9X8K0PTpORHxKNFnWu8Kkzh/8+zoA\nAABcjXfxp2e2DB/dqO3CNV8fPPDTuy81nv3j+aiO5fK1kE1RLaau2PjLT9unv9hs8pHkNz9u\nf1cWmytHg12Qh8583Wy93aCM7/kN5623y3cqk/i/mf++DgAAABc0ZNOvYzoVnzzouQcbt1n6\nW9jyXT8/HuiV92y3GIxhW959dt34AY2adlp6wDD980NDqgb++8Xa4uhv7PqH+0/76O2z49eU\n9TKUbRd+buYikUdF5NJ3l/99EQAAAPfYhfTb54OG1vnSnHp70rATCcNu3dZ7lnjj/S/eeL8g\ns5tK9stM7yciP7/49h2z21qsiMSbC/4vyBw9YjdwyYDU2M8iQsqdSsuK6NU/5cryhn1GTpsw\nrM27h4rXeK3AqwcAAMDd4ugRu7Am7xxYHzZ+4Ua9TnzDBq4auq7HrOk/aVqxiCfXbRlYqCUC\nAADAEQ4GO0t6url6h2Gfdbx5YLLLjK1PDTt26oZ39fvKeerszwsAAIB7waGvYrWs64Emn5Zr\nT+QcLFa2Sp2qpDoAAABX4VCw0xkChlcrfnLJz4VdDQAAAArM0ZMnxuzeXPvskMFzNsSlF/xM\nDQAAABQeR0+eaPPcKEvJcu8P7fj+MO+SYaHenn9LhKdOnSqE2gAAAJAPjgY7b29vkdJPP126\nUKsBAADuKemB2s4uQQWOBruNGzcWah0AAAD4lxwNdgAAAIXE39/f2SUoIn/B7uh3a1Z9s/fM\nlfjHpi7o6rln34XaTWqWKKTKAAAAkC+OBzttfp9Ggz/eY71jGjPn6eQ5zepteqz/3G0LB3tw\nNTsAAABnc/RyJydWdhr88Z7HB8/6/fh560hQ5Xcmv9Bw5wcvtVsQU2jlAQAAwFGOBrtJw7cW\nr/b6tnmv1I68eWKsh6nq6wt+HF8reOe4iYVWHgAAABzlaLBbdzU1onf3f4537FUpLY4TZgEA\nAJzP0WBXzstw/XjSP8cTDl8zeHFxOwAAAOdzNNi92aDE/1b0+ulqWs7BlAvb+6w5GVLvtUIo\nDAAAAPnjaLDrtGZROd2ZJhXrDhwxQUQOr14y8b+9q1d+8owlbO6nzxVmhQAAAHCIo8HOJ7T1\ngd+/fOZB/YczxonIjtHDx767wv/hZz8/cPCZMN9CLBAAAACOcfQ6dteztGKVn/pk+1OLY08d\nPnEh0+BTpnKNMoFehVocAAAAHOdosAsNiXymV+8+ffq0qFuxfmjFQq0JAAAABeDoV7FNImXV\n3LEt65UtU7fFW7NXnkjIKNSyAAAAkF+OBrtvfj4Rd3zf/EnDIy0xE4f2rBIa3OSZgR9v+inV\nUqjlAQAAwFGOBjsRCYp48MVR03ccPHfx8A/vvtk749Dnfdo2DA6r1ve/UwuvPgAAADgoH8Eu\nW6nqjw6dMHfnT/tmDG6VEXv0o+mv3/WyAAAAkF+OnjyRLfXy0S8/W79+/fqN3x9Is2gBFep1\n6dLV8dk/fjHKe8KCrqE+twYsO1bP37gr+ux1Q7WaDXq/3KeijyGvSXZmAQAAcF+OHrG7fu6P\nZbPHtX+sVkBYta6DRm06lNr5pbFf7T2acCp64dsjHVuG9r8flnx+ITFT07KHTq4fPXPN3oad\nBowd2st0YtuoVz/Q8ppkZxYAAAB35ugRu8BydSyaZgyo0K7/yG5du7ZrVtdTl4/VXNo9a/Si\nH69cS//bqJYxY82RyOdndG5RUUQip8qzUdNWXXy+e5ivzUmlPG3OAgAA4N4cPWLXqseQZZv2\nxMefXLfo7Wea3051miUl6XpKnrMXr9359bFTpk/923+VTb+260xa1lPNS1vvegU1ruNn/Hnn\nZTuT7MwCAADg5hw9YvfV8tm5jp/b1rFSuxhz2mn7sxsDykQGSFaGd87BjBsHRaS66XYNNUwe\n3x66ZmdSRmObs1h9/fXX06ZNy767YMGCypUr57l1bnVRvuDg4FzH3aoJYqMPNMHKrfpAE6zo\ng9AEEbHdhDvEx8cXdiUoGEeDnZaVPG/ogKXf/RKXmplz/NKZ0zqf6gVbtyX9hoiEeN4+9SHE\n02BOMtuZZGcWK7PZnJSUdHsVFotOl5/vjN0ADbGiD0ITRIQm3EIfhCaICE0o+hwNdgcmNH15\n3q+VG7asEnjk273nWrXr4CVph7/frivebP7qpQVbt97LJCLxZksp481vhK+aszyCPOxMsjOL\nVbVq1YYMGZJ919/f/8aNG3lWku9zg4syWw1xqyaIjT7QBCu36gNNsKIPQhNExHYTUFQ4uru+\nOfdwcM1Jx/aM0rKSK/kFNZq3bFRZ/9QrO2tWbJ1cuoAnLniaaonsjEk1lzJ6WUeOpWYG1Aiw\nM8nOLFaVK1fO+d1rYmJiampqnpX4F2wDiiZbDXGrJoiNPtAEK7fqA02wog9CE0TEdhNQVDh6\n8sTupIwKXduIiM7g93wJ0/boOBHxKdFkWe8Kkzp/ULB1ewc2CzcaNu+Jtd41J0f/cj3j/mal\n7EyyMwsAAICbczTYBXnozNdv/pStQRnf8xvOW2+X71Qm8X8zC7hynefwzlWPLx63PfrYhZN/\nfDhmhm94y+etx/9sTbIzCwAAgHtz9KvY/uH+0z56++z4NWW9DGXbhZ+buUjkURG59N2/utRI\nZJdJg9JnfTJjTFyaLqJOk4nDB+jymmRnFgAAAHfmaLAbuGTAhGbTI0LKHY09E9Grf8obLzbs\nU7JTRfO77x4qXmO6gwsxGMt8+eWXfxvSGVpGDW8ZldujbU2yMwsAAIAbczTYhTV558D6sPEL\nN+p14hs2cNXQdT1mTf9J04pFPLluy8BCLREAAACOyMdJ3HU6Dvus4zDr7S4ztj417NipG97V\n7yuXr/8tBgAAgEJS8KvzFCtbpc5dLAQAAAD/jqNnxQIAAMDFEewAAAAUQbADAABQBMEOAABA\nEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsA\nAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ\n7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAA\nFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbAD\nAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAE\nwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAA\nQBEEOwAAAEUQ7AAAABTh4ewCCpefn5/BYMjzYRn3oBSXERwcnOu4WzVBbPSBJli5VR9oghV9\nEJogIrabcIf4+PjCrgQFo3iwS0tLy8rKyvNh3vegFJeRlJSU67hbNUFs9IEmWLlVH2iCFX0Q\nmiAitptwB03TCrsSFIziwS4zMzMzMzPPh7nVi9ZsNuc67lZNEBt9oAlWbtUHmmBFH4QmiIjt\nJqCo4Dd2AAAAiiDYAQAAKIJgBwAAoAiCHQAAgCIIdgAAAIog2AEAACiCYAcAAKAIgh0AAIAi\nCHYAAACKINgBAAAogmAHAACgCIIdAACAIgh2AAAAiiDYAQAAKIJgBwAAoAiCHQAAgCIIdgAA\nAIog2AEAACiCYAcAAKAIgh0AAIAiCHYAAACKINgBAAAogmAHAACgCIIdAACAIgh2AAAAiiDY\nAQAAKIJgBwAAoAiCHQAAgCIIdgAAAIog2AEAACiCYAcAAKAIgh0AAIAiCHYAAACKINgBAAAo\ngmAHAACgCIIdAACAIgh2AAAAiiDYAQAAKIJgBwAAoAiCHQAAgCIIdgAAAIog2AEAACiCYAcA\nAKAIgh0AAIAiCHYAAACKINgBAAAogmAHAACgCIIdAACAIgh2AAAAiiDYAQAAKIJgBwAAoAiC\nHQAAgCIIdgAAAIog2AEAACiCYAcAAKAIgh0AAIAiCHYAAACKINgBAAAogmAHAACgCIIdAACA\nIgh2AAAAivBw7uov7x01YMofOUf6frS2Q7C3iIhYdqyev3FX9Nnrhmo1G/R+uU9FH4PdcQAA\nALfm5GCX+FuiT3DbVwbUyB4p7+9pvXFy/eiZa04/P/ilvkGZmxa+N+rVzJXv/0dnexwAAMDN\nOTnYXfkzKbD6I488UuPOCVrGjDVHIp+f0blFRRGJnCrPRk1bdfH57qU8cx8P8733xQMAALgU\nJwe735LSg+oFZqUmxV63lCwRmH3gLf3arjNpWS83L2296xXUuI7f7J93Xn6m1clcx7t3rWQd\nSUlJSUhIyF6+t7e3wcAXtX9DQ6zog9AEEaEJt9AHoQki4nATsrKyCrsSFIyTg92BZLP2w5zn\n5saYNc3DN/TJ7q8MbFtbRDJuHBSR6qbb5dUweXx76FpG49zHs+9u27ZtwoQJ2XdXrFhRtWrV\nPMtIvxvbUlQEBQXlOu5WTRAbfaAJVm7VB5pgRR+EJoiI7SbcIS4urrArQcE4M9hlZZxPNnhW\nCHlk6soJgdr1fZuXTPtgtFflZb2rBlrSb4hIiOftvxtCPA3mJLOt8XtfPAAAgKtxZrAzGMPX\nrl17655X4y4jj235dfuHh3pPb6T3MolIvNlSynjzgixXzVkeQR62xrOX2bBhw/nz52ffDQ4O\nvnbt9vE8W7zvyvYUEbYa4lZNEBt9oAlWbtUHmmBFH4QmiIjtJtxB07TCrgQF4+SvYu9Qr6TP\ntvhYEfE01RLZGZNqLmX0sk46lpoZUCPA1nj2EkJDQ0NDQ7PvJiYmms15H89zqxetrYa4VRPE\nRh9ogpVb9YEmWNEHoQkiYrsJKCqceYHixGPv9es/+FKG5daAZeeFlMDqVUTEO7BZuNGweU+s\ndYI5OfqX6xn3Nytla9wJ1QMAALgYZwa7YpW6BKdcfm3cwp8PHT1++LfVs0buuuH/Qv8qIiI6\nz+Gdqx5fPG579LELJ//4cMwM3/CWz5f2tTkOAADg9pz5VazeI2Tie+M/WrByzqTRaQb/SpVr\njpw5rp7fzQsUR3aZNCh91iczxsSl6SLqNJk4fIDO7jgAAICbc/Jv7LyCavznjcn/yXWaztAy\nanjLKIfHAQAA3Jszv4oFAADAXUSwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4A\nAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEE\nOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAA\nRRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwA\nAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRB\nsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAA\nUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEO\nAABAEQQ7AAAARXg4u4DCpdPpdDqds6twLTTEij4ITRARmnALfRCaICION0HTtMKuBAWjeLDz\n8/MzGAx5Piz9HpTiMoKDg3Mdd6smiI0+0AQrt+oDTbCiD0ITRMR2E+4QFxdX2JWgYBQPdsnJ\nyZmZmXk+zO8elOIybL0a3aoJYqMPNMHKrfpAE6zog9AEEXE4sXHEzmUpHuw0TWPnuwMNsaIP\nQhNEhCbcQh+EJogITSj6OHkCAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ\n7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAA\nFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbAD\nAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAE\nwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7AAAARRDsAAAAFEGwAwAAUATBDgAA\nQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABFEOwAAAAUQbADAABQBMEOAABAEQQ7\nAAAARRDsAAAAFEGwAwAAUATBDgAAQBEEOwAAAEUQ7AAAABRBsAMAAFAEwQ4AAEARBDsAAABF\nEOwAAAAUQbADAABQhIezCygAy47V8zfuij573VCtZoPeL/ep6GNwdkkAAADOV/SO2J1cP3rm\nmr0NOw0YO7SX6cS2Ua9+oDm7JAAAAFdQ1IKdljFjzZHI5yd1btGwxgONh04dnHx+86qLN5xd\nFgAAgPMVsWCXfm3XmbSsp5qXtt71Cmpcx8/4887Lzq0KAADAFRSx39hl3DgoItVNt8uuYfL4\n9tC17LuxsbGnTp3KvluxYkWj0XgvK3R9np6ezi7BJdAHoQkiQhNuoQ9CE0TE4SaYzebCrgQF\nU8SCnSX9hoiEeN4+WyLE02BOur177d27d8KECdl3V6xYUbVq1TwXm35Xi3RxAQEBuY67VRPE\nRh9ogpVb9YEmWNEHoQkiYrsJd4iLiyvsSlAwRSzY6b1MIhJvtpQy3vwS+ao5yyPo326F19Q5\n/7ay/HO1cz5ogjipCUIfRIQmiIjrNUHog4jQBBQpRSzYeZpqieyMSTWXMnpZR46lZgbUuP3n\nRatWrZo2bZp9NysryzX/qvD19fX29s7MzLx27Vrej1aUp6dnsWLFRCQhIcFisTi7HKcJCgrS\n6/UpKSmpqanOrsVpeEWIiIeHh/VgSWJiYlZWlrPLcZrAwECDwZCampqSkuLsWpzGZDL5+Phk\nZWUlJiY6u5bcaRrJ00UVsWDnHdgs3Pj+5j2xTZ8qIyLm5Ohfrmd0blYq+wFGozHnj+oSExNd\neefTNM2Vyyts2dvu5n2wcvMm5NwZnFuJE/GKyMnNm8ArAgVWxM6KFZ3n8M5Vjy8etz362IWT\nf3w4ZoZveMvnS/s6uywAAADnK2JH7EQkssukQemzPpkxJi5NF1GnycThA3TOLgkAAMAVFL1g\nJzpDy6jhLaOcXQYAAICLKWpfxQIAAMAGgh0AAIAiCHYAAACKINgBAAAogmAHAACgCIIdAACA\nIgh2AAAAiiDYAQAAKIJgBwAAoAiCHQAAgCIIdgAAAIog2AEAACiCYAcAAKAIgh0AAIAiCHYA\nAACKINgBAAAogmAHAACgCIIdAACAIgh2AAAAiiDYAQAAKIJgBwAAoAiCHQAAgCIIdgAAAIog\n2AEAACiCYAcAAKAIgh0AAIAiCHYAAACK0Gma5uwaClFiYmJmZqazq8hFbGxsQkKCj49P2bJl\nnV2L06Smpp49e1ZEIiIiDAaDs8txmpMnT2ZmZoaGhgYFBTm7Fqe5evVqfHy8t7d3uXLlnF2L\n06Snp58+fVpEKlSoYDQanV2O0/z1118ZGRkhISHFixd3di1OEx8ff/XqVaPRWKFCBWfXYlNI\nSIizS0AuFA92LmvKlCnr16+vXbv2kiVLnF2L00RHR7/wwgsisnHjxrCwMGeX4zStWrW6evXq\nkCFDoqKinF2L08ycOXPlypVVqlT55JNPnF2L0xw+fNi6D6xbt86VP84LW4cOHc6dO/fCCy9Y\n3x/c0/z585csWVK+fPn169c7uxYUMXwVCwAAoAiCHQAAgCIIdgAAAIrgN3bOERMTc+7cuYCA\ngAcffNDZtThNQkLCr7/+KiKNGjXy9vZ2djlOs2vXroyMjMjISHf+WdWxY8fOnDnj7+/foEED\nZ9fiNElJSfv37xeRRx55xGQyObscp9mzZ09KSkqlSpUqVark7Fqc5sSJE6dOnTKZTI888oiz\na0ERQ7ADAABQBF/FAgAAKIJgBwAAoAgPZxdQJP2xbfXazTuPnbmU5WEqUaZyk9ZduzSvercW\nvrJf119aTJ7ZzXV/XDKmW+ffb2R0W7S6W6m//QwoesqAcXsvV+w8Y3avyH+/Fpftw+5BPaad\nu/7PcZ3OuGHDusJY471vxdEFg0duubJs/doAg8468s3LPeefTn53zfpI75uXko4e32/iIeP6\nT9938K/De7AV96ZRee4AUZ061J67fHi4f6GW4bIvkJx+/W/U+KMJdwyaQrusXtwj50i7du06\nfLC6b8lcflZYJDbTqgCfC8kXz133LhEWVPCLUReh/uCeIdjl2+kNE0Yv+f3x5/p27lfZy5J8\n4vcfls997XjKrNFtKjq7tHtHZ9B9v/xYt//WvT2kZSyOvmrd/repAAAUzUlEQVTQ6ZxX1D1S\ne9iYyemZIqJlXR81Zsp9L74RVdZfRHQ6dY5/l366trb5qw1XU3uVNImIpqWtOp+saZbVRxJG\n17t5rfmt/0vyK/uiOtvsMHfYAe4i78Dmb41skXPEYCxxx2Oeeuqpqj5F+8OoYJ8Lu8eN3FT3\nrfdevGvHBQAh2BXAR2sPlm7+1ss96ljvVq11f1XjXyOWTpc27zkye5ZFM+iLfPop2ax27A+L\nM7S5xlubknz+kwtSqlGxq2ccXkgRbUVA5aoBIiKiZSWIiH9EtZpVAp1b0l3nF/acl37zb7uv\n9OpcQURSr6xPyDL2qmDcuOaI1GssIlkZ5/cmZVTvV+1frqgo7gOFtwNoWWk6g2qnh+s9Q2vW\nrGlrqnWTX3zxxXtZUmH4l58LjlBy90BhINjlW0qWlp5wOedIhXaDRlVKFBHRzO3aP9NzyZrn\nQnysk7p3bP/weytfLu0X1alDm9mTjkyZ+uv5JL+gkg8/1WdIl4bWx6Rd/X3R/NW/xRxP9Qht\n1C4q+yMiI/HPxfOX7z14IinDElI6slX3IZ0fCT/2wZDRP1Rfu/Tm++C1E+/3Gr5j/tpPwo33\n9H+tFivfy7Br5Cfnrvcue/P7pqPLfgyuO9Dr2DvZj8lKP7/ivUXf/3LkmllfrnK9zgMGNa7o\nLyK2WmGrD+LarbjN9rNvyYxb/8HCb/YcjE/Xh0fU6RD1wuNVb/5b2CvRXy9YsSnm7EW9b3Cd\nx9q+1Lutj17n9FboPILaFvf55rtD0rmCiJzf/JNPaKfHesSsnP5JltbYoJOUyxssmvZkveIi\nYmvr7GyFrX3A1qJy7ZKdVTh9h7GYEz6ePHHLgeN6U8jDrfq+3K2hnd2je8f23Rd9eHnJrB2H\nfJYvH21re52+V9xFd2xy5/btWy9aZf0q1mWfU/vsfS7YKH5h7+e+ik+TiyOf/fHRT5e/6uDu\nodJugELCdwf51q99ravR8/oOH7ds3Ve/HzuboYnBO7J+/fp5zrjpzanlOwyZt3D+Sx2qbl05\nZfWVFBHRMuPGDpm472pgn2Fj33ypa8LWWV/GpVof/9HICXviy748ZtKMqR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Key findings from ggplot2 visualizations\n\n* More than half of the Cyclistic customers have signed up as annual members. This proves that the company has already built up a certain level of loyalty among its customers. However, to increase revenue generation they hope to maximize the number of riders and target converting more casual riders to annual members.\n\n* On weekdays, there are more rides by member riders peaking on Tuesday whereas more rides by casual riders are recorded on weekends. We can infer that more member riders use Cyclistic bikes to commute to work/school while casual riders use Cyclistic bikes for occasional or recreational purposes.\n\n* Casual riders have about twice as much average trip duration as member riders, peaking on Saturday and Sunday. The high average trip duration of casual riders on weekends might be caused by the use of rides for touristic or leisure activities.\n\n* The average trip distance for casual riders is also slightly longer than member riders, with both peaking on weekends.","metadata":{}},{"cell_type":"markdown","source":"### Act\n\n*Recommendations*\n\nProceeding from the analysis conducted, I would make a few suggestions to convert casual riders into Cyclistic members\n\n* The marketing team can increase rates for the trip duration for casual riders. However, incentivize them to sign up as annual members by offering lower rates on trip duration for member riders.\n\n* The marketing team can create advertisement billboards and flyers close to leisure and tourist centers offering membership sign-up discounts with details of their benefit.\n\n* In conclusion, the marketing team can encourage more casual riders to sign up as members by providing them with a membership bonus on trip distance on weekends. For example, as members, they get a 25% discount on 1000 meters, a 50% discount for 2000 meters on weekends, and so on.","metadata":{}}]}