https://github.com/muhammedbuyukkinaci/data-science-notes
Listing my Data Science Notes
https://github.com/muhammedbuyukkinaci/data-science-notes
Last synced: 6 months ago
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Listing my Data Science Notes
- Host: GitHub
- URL: https://github.com/muhammedbuyukkinaci/data-science-notes
- Owner: MuhammedBuyukkinaci
- Created: 2023-02-07T18:19:38.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-06-05T20:37:02.000Z (over 1 year ago)
- Last Synced: 2025-02-09T23:19:20.515Z (8 months ago)
- Size: 34.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Data-Science-Notes
Listing my Data Science Notes
1) We can access variables in pd.DataFrame().query() method like below
```
df = pd.DataFrame({'a':[1,2,3],'b':['x','y','z]})
BIGGER_FILTER = 2
df.query("a > @BIGGER_FILTER")
```
2) Usage of `.query()` can be encouraged. It is simple than complex filters.
3) For columns in the datetime format, use **parse_dates=['date_column_here']** in pd.read_csv().
4) Prefer dumping via to_parquet, to_feather, to_pickle instead of to_csv. It will preserver or data types and consume less spaces on hard disc.
5) We can use pd.DataFrame().style instead of MS Excel for formatting files.
6) validate option for pd.DataFrame().merge(validate=)
7) Converting string columns which are categorical to category type is a best practice. We can do this via `.astype('category')`
8) [Yellowbrick](https://github.com/DistrictDataLabs/yellowbrick) is a Python library that has useful visualizations for ML.