The Twitter Archive Analysis Project is a project for the wrangle and analyze data section of the Udacity Data Analyst Nanodegree program. In this project several data sets relating to the WeRateDogs Twitter account are gathered, cleaned, and analyzed.
In this project the Twitter account WeRateDogs, which posts tweets containing image and text information about a dog, including the dog's name, a rating, and often a stage such as 'doggo' or 'pupper' is analyzed primarily using matplotlib and seaborn visualizations. The data is initially gathered using the Twitter API through the tweepy library and is then cleaned.
This project makes use of the Twitter API, and therefore requires a consumer_key, consumer_secret, access_token, and access_secret for data to be gathered. However this is not necessary for running the visualizations in later portions of the project.
This code depends on the following libraries:
globjsonospandasnumpyrequeststweepymatplotlib.pyplotseaborn
In addition to these, the Jupyter Notebook, wrangle_act.ipynb assumes that the data set twitter-archive-enhanced.csv has been downloaded, extracted, and saved in the project folder. The files twitter_archive_master.csv and image_predictions_master.csv are also necessary to be included in the project folder if using the Notebook with the cleaned data sets and not going through the cleaning process itself or using the Twitter API.
The Binder badge above can be used to explore an executable environment for this project.
- organize and clear files in project folder
- include more statistical analysis?
- add features to README
- update and edit README
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give me that choice follow on Github
or email me at deepaksithu@gmail.com.
