Wrangle Report - WeRateDogs

In this report I have summarised the process of data wrangling I have performed to gather the data from different sources to analyse and give interesting insights from the WeRateDogs twitter Handle.
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.” WeRateDogs has over 4 million followers and has received international media coverage.

The goal of the project include:

Data Gathering

In this step, It was required to gather the data from three sources.

Data Assessment

In this step I have assessed the data for the quality and the tideness. Quality assessment include:

I have found the following issues related to the data:
Twitter Archive :

Image Prediction :

Tweets data from API :

Cleaning Data

In this part I have cleaned the data and fixed the issues which I found in the assess part. Following operations were performed.

from subprocess import call
call(['python', '-m', 'nbconvert', 'wrangle_report.ipynb'])
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