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Wes here. From what I understand, pandas is the middleware layer powering about 90% (if not more) of analytical applications in Python. It is what people use fo
by wesm 9y ago
Wes here. From what I understand, pandas is the middleware layer powering about 90% (if not more) of analytical applications in Python. It is what people use for data ingest, data prep, and feature engineering for machine learning models.
The existence of other database systems that perform equivalent tasks isn't useful if they are not accessible to Python programmers with a convenient API.
- FridgeSeal 9y agoThis is exactly how I use it. I pull the relevant data out of a production database, clean it, add relevant columns, filter out trash data, use seaborn to produce some simple plots to see what my data approximately looks/structured like then off to sklearn.
- atupis 9y agoDefinitely this and I like how simple plotting is at pandas, usually df['some_column'].plot() gives decent plot out of box.