https://github.com/victoriapm/weratedogs_twitter_data_wrangling

Data wrangling, analyzing and visualizing of the tweet archive of WeRateDogs
https://github.com/victoriapm/weratedogs_twitter_data_wrangling

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Data wrangling, analyzing and visualizing of the tweet archive of WeRateDogs

• Host: GitHub
• URL: https://github.com/victoriapm/weratedogs_twitter_data_wrangling
• Owner: Victoriapm
• Created: 2020-04-16T15:49:15.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-04-29T13:52:15.000Z (about 5 years ago)
• Last Synced: 2025-01-17T05:43:57.787Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 4.81 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Wrangle and Analyze a Dataset: WeRateDogs Twitter Archive

## Introduction 

This project is the final task for part 4 of the Udacity Data Analyst Nano Degree. 

The project consists in creating a jupyter notebook to perform data wrangling tasks on a given dataset. 

## Learning objectives

- Data wrangling, which consists of:

    - Gathering data (downloadable file in the Resources tab in the left most panel of your classroom and linked in step 1 below).

    - Assessing data

- Cleaning data

- Storing, analyzing, and visualizing your wrangled data

- Reporting on 1) your data wrangling efforts and 2) your data analyses and visualizations

## Analysis Description

The dataset that will be wrangling (and analyzing and visualizing) in this project is the tweet archive of Twitter user [@dog_rates](https://twitter.com/dog_rates), also known as [WeRateDogs](https://en.wikipedia.org/wiki/WeRateDogs). 

WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. 

Why? 

Because...

!["they're good dogs Brent."](https://i.kym-cdn.com/photos/images/newsfeed/001/225/812/2b3.png)

WeRateDogs has over 4 million followers and has received international media coverage.

## Contents

* wrangle_act.ipynb file where the analysis has been developed, contains code with Markdown cells from Jupyter Notebook.

* .html file output of the .ipynb converted to web version for easy viewing

* twitter_archive_master.csv file with the clean data used 

* wrangle_report.pdf file with a written report about the wrangling efforts. This is to be framed as an internal document.

* act_report.pdf file with a written report that communicates the insights and displays the visualization(s) produced from the wrangled data. This is to be framed as an external document, like a blog post or magazine article.

## Pre-requisites

No installation is needed to view the analysis. 

To reproduce the project an installation of Python 3.5 and the following libraries is needed:

- pandas

- NumPy

- Matplotlib

- requests

- tweepy

- json