Functions

Conversion

from_arrow(data[, schema, rechunk, ...])	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, *[, infer_schema_length, ...])	Construct a DataFrame from a sequence of dictionaries.
from_numpy(data[, schema, schema_overrides, ...])	Construct a DataFrame from a numpy ndarray.
from_pandas()	Construct a Polars DataFrame or Series from a pandas DataFrame or Series.
from_records(data[, schema, ...])	Construct a DataFrame from a sequence of sequences.

Eager/Lazy functions

arg_where()	Return indices where condition evaluates True.
concat()	Aggregate multiple Dataframes/Series to a single DataFrame/Series.
cut(s, bins[, labels, break_point_label, ...])	Bin values into discrete values.
date_range()	Create a range of type Datetime (or Date).
get_dummies(df, *[, columns, separator])	Convert categorical variables into dummy/indicator variables.
ones(n[, dtype])	Return a new Series of given length and type, filled with ones.
zeros(n[, dtype])	Return a new Series of given length and type, filled with zeros.

Miscellaneous

align_frames()

Align a sequence of frames using the unique values from one or more columns as a key.

Parallelization

collect_all(lazy_frames, *[, type_coercion, ...])

Collect multiple LazyFrames at the same time.

StringCache

toggle_string_cache(toggle)	Turn on/off the global string cache.
StringCache()	Context manager that allows data sources to share the same categorical features.