eyasahli / udacity-dand-wrangle-and-analyze-data

Udacity-DAND-wrangle-and-analyze-data

Introduction :

Real-world data rarely comes clean. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assessed its quality and tidiness, then cleaned it. This is called data wrangling. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python (and its libraries).

The dataset that I wrangled (and analyzed and visualized) is 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 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.

WeRateDogs downloaded their Twitter archive and sent it to Udacity via email . This archive contains basic tweet data (tweet ID, timestamp, text, etc.)

Project Details :

my tasks in this project were as follows:

Data wrangling, which consists of : Gathering data (downloadable files), Assessing data, Cleaning data, Storing, analyzing, and visualizing wrangled data and Reporting on :

1. my data wrangling efforts and
2. my data analyses and visualizations