pandas Migration Patterns

The safest migration is not a blind import swap. Start by identifying the expensive parts of the pandas workflow and move data loading, filtering, and aggregations into Dask.

Migration sequence

1. Keep the pandas result contract unchanged.
2. Read data with Dask directly from cloud storage.
3. Push filters and projections early.
4. Avoid calling compute() until a small result is needed.

Anti-pattern

# Avoid loading a large dataset locally before handing it to Dask.
pandas_df = pandas.read_csv("s3://bucket/huge.csv")
ddf = dd.from_pandas(pandas_df, npartitions=100)

Better direction

ddf = dd.read_csv("s3://bucket/*.csv")
summary = ddf.groupby("account_id").amount.sum()