Add a Woodwork DataFrame tips and tricks guide
- Langage dominant
- Python
- Étoiles
- 155
- Forks
- 24
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
There are some common woodwork questions that come up with new users, often times surrounding the most efficient way to access typing information. As the structure of how typing info is stored (Table Schema vs Column Schema) and how/when Woodwork initialization happens when getting subsets of data are somewhat opaque, we should provide a guide that helps users understand the best ways to get information from their dataframes.
Ex: Doing `df.ww.columns[col_name].origin` is more efficient than doing `df.ww[col_name].ww.origin`, because it avoids reinitializing woodwork on a new Series. This isn't clear unless you know the specifics of how Woodwork initialization works, so it'd be helpful to explain to users at some point in our documentation that they should do this (even if we dont want to explain why they should)
Ex 2: `df.ww.logical_types` will iterate through all of the columns in your dataframe, so which can be problematic in very wide dataframes if called excessively, so care should be taken to pull out that call from for loops to avoid unnecessary computation.
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