Functions#

Conversion#

`from_arrow`(data[, schema, schema_overrides, ...])	Create a DataFrame or Series from an Arrow Table or Array.
`from_dataframe`(df, *[, allow_copy])	Build a Polars DataFrame from any dataframe supporting the interchange protocol.
`from_dict`(data[, schema, schema_overrides, ...])	Construct a DataFrame from a dictionary of sequences.
`from_dicts`(data[, schema, schema_overrides, ...])	Construct a DataFrame from a sequence of dictionaries.
`from_numpy`(data[, schema, schema_overrides, ...])	Construct a DataFrame from a NumPy ndarray.
`from_pandas`(data, *[, schema_overrides, ...])	Construct a Polars DataFrame or Series from a pandas DataFrame, Series, or Index.
`from_records`(data[, schema, ...])	Construct a DataFrame from a sequence of sequences.
`from_repr`(data)	Construct a Polars DataFrame or Series from its string representation.
`json_normalize`(data, *[, separator, ...])	Normalize semi-structured deserialized JSON data into a flat table.

`align_frames`(*frames, on[, how, select, ...])	Align a sequence of frames using common values from one or more columns as a key.
`concat`(items, *[, how, rechunk, parallel])	Combine multiple DataFrames, LazyFrames, or Series into a single object.
`escape_regex`(s)	Escapes string regex meta characters.

`collect_all`(lazy_frames, *[, type_coercion, ...])	Collect multiple LazyFrames at the same time.
`collect_all_async`(lazy_frames, *[, gevent, ...])	Collect multiple LazyFrames at the same time asynchronously in thread pool.

Set the global random seed for Polars.

Note that the StringCache can be used as both a context manager and a decorator, in order to explicitly scope cache lifetime.

`StringCache`()	Context manager for enabling and disabling the global string cache.
`enable_string_cache`()	Enable the global string cache.
`disable_string_cache`()	Disable and clear the global string cache.
`using_string_cache`()	Check whether the global string cache is enabled.