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Initial Description and Link:

• Demonstrates how to flip ggplot axes

• https://github.com/peterkowalchuk/FALL2023TIDYVERSE/blob/main/ggplot_forcats_fall.rmd

• Demonstrates how to scale axis and move labels (Kelly)

• https://github.com/autistic96/FALL2023TIDYVERSE/blob/main/ggplot_scaling_and_labeling.Rmd

• extended Lwin's Vignette

Revision/Addition Description and Link:

• Modified ggplot/forcats example to demonstrate sorting, other category
• https://github.com/peterkowalchuk/FALL2023TIDYVERSE/blob/main/ggplot_forcats_fall.rmd

Folorunsho Atanda Addition

• Demonstration of using map() from the purrr package
• Github link: https://github.com/folushoa/Data-Science/tree/Data-607/Tidyverse

Updates by Haig Bedros (@hbedros)

Vignette and Analysis:

• Explored a dataset from FiveThirtyEight and demonstrated the use of various tidyverse functions.
• https://github.com/acatlin/FALL2023TIDYVERSE/blob/main/hbe.rmd

Additional Contribution:

• Introduced a section on "Exploring Cumulative Distribution with tidyverse" titled "Cumulative Followers Distribution".
• https://github.com/acatlin/FALL2023TIDYVERSE/blob/main/ggplot_forcats.rmd

TidyVerse Create Repository README

Author

• Name: Mikhail Broomes
• Date: 2023-11-05

Link to code

• https://github.com/MAB592/FALL2023TIDYVERSE/blob/main/TidyVerse%20CREATE%20assignment.Rmd

Libraries

• To run the code in this repository, make sure you have the following R libraries installed:

The core R packages used are. - dplyr 1.1.2 - readr 2.1.4

Joins in R

In this repository, you will find information on how to perform a full join using the dplyr package in R. The focus is on merging two datasets containing movie ratings for the years 2021 and 2022. The goal is to combine these datasets and create a comprehensive list of movie ratings, ensuring that all movies from both years are included and missing values are filled with NA where necessary.

Dataset Description

The repository includes two datasets:

1. movieratings_2021: Contains movie ratings for the year 2021.
2. movieratings_2022: Contains movie ratings for the year 2022.

The merging process is based on a unique identifier for each movie.

Example Usage

To load the datasets and perform a full join, you can use the following code:

# Load the datasets
movieratings_2021 <- read_csv("URL_TO_MOVIERATINGS_2021_CSV_FILE")
movieratings_2022 <- read_csv("URL_TO_MOVIERATINGS_2022_CSV_FILE")

# Perform a full join
full_movie_ratings <- full_join(movieratings_2021, movieratings_2022, by = "Film")

## Author
* Matthew Roland
* Document demonstrates a use-case for the TidyR package, specifically, with regards to its pivot functions and searate function

Author

• Matthew Roland
• Date: 2023-06-11
• Link to rmd:
• https://raw.githubusercontent.com/peterkowalchuk/FALL2023TIDYVERSE/main/Roland%20Tidyverse_CREATE_Assignment.Rmd
• This vignette demonstrates a use-case for the TidyR package, specifically, with regards to using the Pivot and Separate functions to clean and tidy a dataset

Updates by Jean Jimenez (@sleepysloth12)

Vignette and Analysis:

• Explored a dataset from OpenNYC and demonstrate how to animate geographic data on a map over time
• https://github.com/peterkowalchuk/FALL2023TIDYVERSE/blob/main/jjimenez_tidyverse_queens_carcrash.Rmd

Revision/Addition Description and Link:

• Modified Stroke Data to include NIHSS and added function that calculates NIHSS
• https://github.com/peterkowalchuk/FALL2023TIDYVERSE/blob/main/Roland%20Tidyverse_CREATE_Assignment.Rmd

Updates by Stephen Phillips (@sphill12)

Added a few useful dplyr functions to help with data analysis

https://github.com/peterkowalchuk/FALL2023TIDYVERSE/blob/main/Tidyverse%20demo%20Stephen%20Phillips.Rmd

Tidyverse_Extend_LwinShwe

Adding more annotated codes to extend Tidyverse CREATE assignment submitted by Noori Selina

Extention of Mikhail's vignette by Tilon Bobb:

Created a similar example to the join function in the dplyr package

https://github.com/Kingtilon1/FALL2023TIDYVERSE/blob/tilon-bobbs-branch/TidyVerse%20CREATE%20assignment.Rmd

Readr package vignette by Tilon Bobb

Talked about the capabilities of the readr package can be found here

Updates by Haig Bedros (@hbedros)

Project Overview

This project, an extension of Selina Noori's earlier vignette, is an advanced exploration of the Census Income dataset. Developed by Haig Bedros, this submission delves deeper into data manipulation and analysis using the tidyverse suite in R, with a focus on the dplyr package.

Data Source

The analysis is based on the Census Income dataset, featuring a range of demographic information. This dataset provides a rich source for demonstrating complex data manipulation techniques.

Analysis Highlights

• Data Transformation: Enhanced manipulation of the dataset, introducing new categorizations and metrics.
• Insightful Summaries: Detailed summaries across multiple demographic groups, revealing deeper insights.
• Relationship Exploration: Investigating correlations between different demographic factors and income levels.

Conclusion

This extended analysis by Haig Bedros not only builds upon the foundational work of Selina Noori but also showcases the flexibility and power of tidyverse tools in uncovering nuanced insights from complex datasets.

Tidyverse_Extend_LwinShwe

Adding more annotated codes to extend Tidyverse CREATE assignment submitted by Noori Selina