General functions

Data manipulations

concat(objs[, axis, join, ignore_index, ...])	Concatenate dataframe objects along a particular axis with optional set logic along the other axes.
factorize(values[, sort, use_na_sentinel])	Encode the object as an enumerated type or categorical variable.
get_dummies(data[, prefix, prefix_sep, ...])	Convert categorical variable into dummy/indicator variables.
merge(df, right[, how, on, left_on, ...])	Merge DataFrame or named Series objects with a database-style join.

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 numeric data

to_numeric(arg[, errors, downcast])

Convert argument to a numeric type.

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.