polars.DataFrame.to_dict#
- DataFrame.to_dict(*, as_series: bool = True) dict[str, Series] | dict[str, list[Any]] [source]#
Convert DataFrame to a dictionary mapping column name to values.
- Parameters:
- as_series
True -> Values are Series False -> Values are List[Any]
See also
Examples
>>> df = pl.DataFrame( ... { ... "A": [1, 2, 3, 4, 5], ... "fruits": ["banana", "banana", "apple", "apple", "banana"], ... "B": [5, 4, 3, 2, 1], ... "cars": ["beetle", "audi", "beetle", "beetle", "beetle"], ... "optional": [28, 300, None, 2, -30], ... } ... ) >>> df shape: (5, 5) ┌─────┬────────┬─────┬────────┬──────────┐ │ A ┆ fruits ┆ B ┆ cars ┆ optional │ │ --- ┆ --- ┆ --- ┆ --- ┆ --- │ │ i64 ┆ str ┆ i64 ┆ str ┆ i64 │ ╞═════╪════════╪═════╪════════╪══════════╡ │ 1 ┆ banana ┆ 5 ┆ beetle ┆ 28 │ │ 2 ┆ banana ┆ 4 ┆ audi ┆ 300 │ │ 3 ┆ apple ┆ 3 ┆ beetle ┆ null │ │ 4 ┆ apple ┆ 2 ┆ beetle ┆ 2 │ │ 5 ┆ banana ┆ 1 ┆ beetle ┆ -30 │ └─────┴────────┴─────┴────────┴──────────┘ >>> df.to_dict(as_series=False) {'A': [1, 2, 3, 4, 5], 'fruits': ['banana', 'banana', 'apple', 'apple', 'banana'], 'B': [5, 4, 3, 2, 1], 'cars': ['beetle', 'audi', 'beetle', 'beetle', 'beetle'], 'optional': [28, 300, None, 2, -30]} >>> df.to_dict(as_series=True) {'A': shape: (5,) Series: 'A' [i64] [ 1 2 3 4 5 ], 'fruits': shape: (5,) Series: 'fruits' [str] [ "banana" "banana" "apple" "apple" "banana" ], 'B': shape: (5,) Series: 'B' [i64] [ 5 4 3 2 1 ], 'cars': shape: (5,) Series: 'cars' [str] [ "beetle" "audi" "beetle" "beetle" "beetle" ], 'optional': shape: (5,) Series: 'optional' [i64] [ 28 300 null 2 -30 ]}