# dask.dataframe.map_partitions

dask.dataframe.map_partitions(func, *args, meta=<no_default>, enforce_metadata=True, transform_divisions=True, align_dataframes=True, **kwargs)

  Apply Python function on each DataFrame partition.

  Parameters:
    func function

      Function applied to each partition.

    args, kwargs

      Arguments and keywords to pass to the function. At least one of the args should be a Dask.dataframe. Arguments and keywords may contain `Scalar`, `Delayed` or regular python objects. DataFrame-like args (both dask and pandas) will be repartitioned to align (if necessary) before applying the function (see `align_dataframes` to control).

    enforce_metadata bool, default True

      Whether to enforce at runtime that the structure of the DataFrame produced by `func` actually matches the structure of `meta`. This will rename and reorder columns for each partition, and will raise an error if this doesn’t work, but it won’t raise if dtypes don’t match.

    transform_divisions bool, default True

      Whether to apply the function onto the divisions and apply those transformed divisions to the output.

    align_dataframes bool, default True

      Whether to repartition DataFrame- or Series-like args (both dask and pandas) so their divisions align before applying the function. This requires all inputs to have known divisions. Single-partition inputs will be split into multiple partitions.

      If False, all inputs must have either the same number of partitions or a single partition. Single-partition inputs will be broadcast to every partition of multi-partition inputs.

    meta pd.DataFrame, pd.Series, dict, iterable, tuple, optional

      An empty `pd.DataFrame` or `pd.Series` that matches the dtypes and column names of the output. This metadata is necessary for many algorithms in dask dataframe to work. For ease of use, some alternative inputs are also available. Instead of a `DataFrame`, a `dict` of `{name: dtype}` or iterable of `(name, dtype)` can be provided (note that the order of the names should match the order of the columns). Instead of a series, a tuple of `(name, dtype)` can be used. If not provided, dask will try to infer the metadata. This may lead to unexpected results, so providing `meta` is recommended. For more information, see `dask.dataframe.utils.make_meta`.