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Projects

Project 1 : US Bikeshare Data

Project Submission Link

Overview:

In this project, Python is used to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. Wrote code to import the data & answer interesting questions by computing descriptive statistics. Wrote a script that took raw input to create an interactive experience in the terminal to present these statistics.

The developed CLI program allows the user to explore an US bikeshare system database and retrieve statistics information from the database. Filters the information by city, month and weekday, to visualize statistical information related to a subset of the data. The user is able to chose to view raw data and to sort it by columns, in an ascending or descending order.

Project 2 : Investigate a Dataset

Project Submission Link

Overview:

In this project, you will analyze a dataset and then communicate your findings about it. You will use the Python libraries NumPy, pandas, and Matplotlib to make your analysis easier

This data set(TMDB Movie Data) contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.

● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters.

● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is.

● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.

Project 3 : SQL for Data Analysis

Project Submission Link

Overview:

This project was about the exploration of a Digital Music Store Database, in which SQL queries had to be run and visualizations were made to showcase the queries output.

For the presentation component, four slides were created, and each had

  • A question of interest.
  • A supporting SQL query needed to answer the question.
  • A supporting visualization created using the final data of the SQL queries that answer the questions of interest.
  • A summary on each slide.

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