In this project, I documented my data wrangling efforts in a Jupyter Notebook and displayed them using Python analyses and visualizations (and its libraries).

The dataset wrangled (and analyzed and visualized) was 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. WeRateDogs has over 4 million followers and has received international media coverage.

WeRateDogs downloaded their Twitter archive and sent it to Udacity via email exclusively for you to use in this project. This archive contains basic tweet data (tweet ID, timestamp, text, etc.) for all 5000+ of their tweets as they stood on August 1, 2017. More on this soon.

Data wrangling, which consists of:

• Gathering data ( 3 data set was used, one data was scrapped from twitter, the other 2 were downloaded from a link. downloadable file here).
• Assessing data
• Cleaning data
• Storing, analyzing, and visualizing your wrangled data
• Reporting on data wrangling efforts and data analyses and visualizations