DataFrame Accessor

General methods and attributes

cols(df, /[, to_list])

An API to gather name and columns to one.

Conversion

change_axis_type(df, dtype[, axis])	Change the type of the axis.
to_series(df, /[, name, index_column, ...])	Convert DataFrame to Series.
to_zh(df, /, column, *[, locale, dictionary])	Simple conversion and localization between simplified and traditional Chinese.
values_to_dict(df, /[, order, ascending, ...])	Convert values to dict.

Binary operator functions

boolean(df, /[, how, complement])	Return whether any (or all) element is True, potentially over an axis.
equal(df, /, other[, align, axis])	Return a boolean DataFrame containing the result of comparing with other.

GroupBy

groupby_index(df, /, **kwargs)

Group DataFrame by its index.

Computations / Descriptive Stats

decompose(df, /, method[, columns, drop])	Decompose DataFrame's columns.
top_n(df, /[, n, largest, keep, prefix, ...])	Returns each row's top n.
repeat(df, repeats, /[, axis])	Repeat row or column of a DataFrame.
weighted_mean(df, /, weights[, validate, ...])	Calculate the weighted score of selected columns in the DataFrame.

Reindexing / Selection

filter_in(df, condition, /[, how, complement])	Filter DataFrame contents.
set_unique_index(df, /, **kwargs)	Set unique index via reset_index().

Missing values

drop_inf(df, /[, axis, how, inf, subset])	Remove inf values.
drop_not_duplicates(df, /[, subset, keep])	Return duplicate DataFrame values.
drop_or_not(df, /[, drop])	Drop specified labels from rows or columns.
dropna_index(df, /[, how])	Return a new DataFrame with missing index removed.
fillna_regression(df, /, method, columns[, how])	Fill na value with regression algorithm.

Reshaping / Transposing

expand(df, /[, suffix, delimiter, flatten])

Transform each element of a list-like to a column.