Data Analysis Nanodegree Projects

By Nacer KROUDIR

This repository contains 3 projects related to the Data Analysis Nanodegree program delivered by Udacity and ALX. The projects are focused on different aspects of data analysis, including data wrangling, data visualization, and exploratory data analysis.

Project 1: Investigate TMDB Movies dataset

In this project, you can find a jupyter notebook of the data analysis and the corresponding dataset. The purpose of this project is to familiarise yourself with the data analysis process and the jupyter notebook workflow.

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Project 2: Data Wrangling for WeRateDogs Twitter account

this project is centered around the data wrangling process, from data gathering through different means (link, API...), passing by data assessing and data cleaning. I worked with a messy dataset and performed data wrangling techniques to clean and transform the data into a usable format. I used tools such as pandas, numpy, and matplotlib to explore, clean, and visualize the data. I made two reports:

• The first report is highlighting the problems I found on the datasets and the steps I went through in data cleaning.
• The second report communicates the key findings and results obtained in the data analysis.

Both reports are included as .pdf in the project folder.

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Project 3: Data Visualization for Ford GoBike Dataset

This project focused on creating effective data visualizations using Python libraries such as matplotlib, seaborn and folium. I used the skills and knowledge learned in the program to create visualizations that effectively communicate insights from Ford GoBike dataset. The project includes an elegant presentation of the key findings made in jupyter notebook.

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Installation

To run these projects on your local machine, you will need to have Python 3 and Jupyter Notebook installed. You can install these dependencies using Anaconda or by running the following commands in your terminal:

pip install jupyter
pip install numpy
pip install pandas
pip install matplotlib
pip install seaborn
pip install folium
pip install requests
pip install beautifulsoup4

Usage

To run the projects, simply open the Jupyter Notebook files (.ipynb) in the corresponding project folders. Each notebook contains detailed instructions and code for completing the project.