wanderly0501 / Data-Wrangling-of-WeRateDogs-Tweet-Archive

Gathered data from URL and twitter API, assessed and cleaned data in Python

Data Wrangling of WeRateDogs Tweet Archive

Overview

This project wrangled, analyzed and visualized the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a twitter account that rates people's dogs with a humorous comment. The output are two files storing clean data.

Installing

• Install Jupyter Notebook to run wrangle_act.ipynb.

• Need consumer_key, consumer_secret, access_token, access_secret to query from Twitter API.

• Require the following libraries installed.

• numpy

• pandas

• requests

• json

• matplotlib.pyplot

Files

• act_report: Communicates the insights and displays the Visualizations produced from the wrangled data.
• image_prediction.tsv: Data downloaded using Requests library and URL.
• tweet_json.txt: Data gathered from twitter API.
• twitter-archive-enhanced.csv: File downloaded from Udacity.
• twitter_archive_master.csv: The clean DataFrame 1.
• twitter_image_predictions.csv: The clean DataFrame 2.
• wrangle_act.ipynb: The main file containing all the gathering, wrangling and analyzing work.
• wrangle_report: Briefly describes my wrangling efforts.

Table of Contents

Gather Data

• Gather data from file on hand
• Download file using Requests library and URL
• Gather data from twitter API using Python's Tweepy library and store data

Assess Data

Clean Data

Store Data

Analyze and Visualize Data

• Visualization
• Insight

Resources

• Twitter API
• Files downloaded from Udacity