https://github.com/h-fuzzy-logic/python-exploring-user-generated-events
Using Python and Pandas to explore log files of user generated events. Inspired by Kaggle's 2019 Data Science Bowl
https://github.com/h-fuzzy-logic/python-exploring-user-generated-events
exploratory-data-analysis json kaggle-competition pandas python
Last synced: 3 months ago
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Using Python and Pandas to explore log files of user generated events. Inspired by Kaggle's 2019 Data Science Bowl
- Host: GitHub
- URL: https://github.com/h-fuzzy-logic/python-exploring-user-generated-events
- Owner: h-fuzzy-logic
- Created: 2020-02-01T02:13:26.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-02-01T02:36:02.000Z (over 6 years ago)
- Last Synced: 2025-04-02T20:34:15.684Z (over 1 year ago)
- Topics: exploratory-data-analysis, json, kaggle-competition, pandas, python
- Language: Jupyter Notebook
- Homepage:
- Size: 8.79 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Python-Exploring-User-Generated-Events
Wrangling user generated event data from Kaggle's 2019 Data Science Bowl with Python and Pandas. Code demonstrates:
* How Python's def can make code easier to comprehend within a Jupyter notebook
* How Python's %%time can help uncover performance bottlenecks
* How Python's json module can make parsing JSON data easier
* How Pandas can be used to summarize events by user when faced with a log-style data file
NOTE: Data files are not included with the repo and can be found at https://www.kaggle.com/c/data-science-bowl-2019/data.