General functions

Data manipulations

cut(x, bins[, right, labels, retbins, ...])	Bin values into discrete intervals.
concat(objs[, axis, join, ignore_index, ...])
get_dummies(data[, prefix, prefix_sep, ...])	Convert categorical variable into dummy/indicator variables.
melt(frame[, id_vars, value_vars, var_name, ...])	Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
merge(df, right[, how, on, left_on, ...])	Merge DataFrame or named Series objects with a database-style join.
qcut(x, q[, labels, retbins, precision, ...])	Quantile-based discretization function.

Top-level missing data

isna(obj)	Detect missing values.
isnull(obj)	Detect missing values.
notna(obj)	Detect existing (non-missing) values.
notnull(obj)	Detect existing (non-missing) values.

Top-level dealing with datetimelike

to_datetime(arg[, errors, dayfirst, ...])	Convert argument to datetime.
date_range([start, end, periods, freq, tz, ...])	Return a fixed frequency DatetimeIndex.

Top-level evaluation

eval(expr[, parser, engine, local_dict, ...])

Evaluate a Python expression as a string using various backends.

Misc

CustomReduction([name, is_gpu])
ExecutableTuple(*args)