General functions

Working with options


Reset one option to their default value.

get_option(key[, default])

Retrieves the value of the specified option.

set_option(key, value)

Sets the value of the specified option.


Context manager to temporarily set options in the with statement context.

Data manipulations and SQL

melt(frame[, id_vars, value_vars, var_name, …])

Unpivot a DataFrame from wide format to long format, optionally leaving identifier variables set.

merge(obj, right[, how, on, left_on, …])

Merge DataFrame objects with a database-style join.

get_dummies(data[, prefix, prefix_sep, …])

Convert categorical variable into dummy/indicator variables, also known as one hot encoding.

concat(objs[, axis, join, ignore_index, sort])

Concatenate pandas-on-Spark objects along a particular axis with optional set logic along the other axes.

sql(query[, index_col, globals, locals])

Execute a SQL query and return the result as a pandas-on-Spark DataFrame.


Marks a DataFrame as small enough for use in broadcast joins.

Top-level missing data


Convert argument to a numeric type.


Detect missing values for an array-like object.


Detect missing values for an array-like object.


Detect existing (non-missing) values.


Detect existing (non-missing) values.

Top-level dealing with datetimelike

to_datetime(arg[, errors, format, unit, …])

Convert argument to datetime.

date_range([start, end, periods, freq, tz, …])

Return a fixed frequency DatetimeIndex.