General functionsΒΆ

All supported general functions

Data manipulations

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

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

crosstab(index, columns[, values, rownames, ...])

Compute a simple cross tabulation of two (or more) factors.

pivot(data[, index, columns, values])

Return reshaped DataFrame organized by given index / column values.

pivot_table(data[, values, index, columns, ...])

Create a spreadsheet-style pivot table as a DataFrame.

cut(x, bins[, right, labels, retbins, ...])

Bin values into discrete intervals.

qcut(x, q[, labels, retbins, precision, ...])

Quantile-based discretization function.

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

Concatenate pandas objects along a particular axis.

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

Convert categorical variable into dummy/indicator variables.

merge(left, right[, how, on, left_on, ...])

Merge DataFrame or named Series objects with a database-style join.

merge_asof(left, right[, on, left_on, ...])

Perform a merge by key distance.

unique(values)

Return unique values based on a hash table.

Top-level missing data

isna(obj)

Detect missing values for an array-like object.

isnull(obj)

Detect missing values for an array-like object.

notna(obj)

Detect non-missing values for an array-like object.

notnull(obj)

Detect non-missing values for an array-like object.

Top-level dealing with numeric data

to_numeric(arg[, errors, downcast])

Convert argument to a numeric type.

Top-level dealing with datetimelike data

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

Return a fixed frequency DatetimeIndex.

bdate_range([start, end, periods, freq, tz, ...])

Return a fixed frequency DatetimeIndex with business day as the default.

to_datetime(arg[, errors, dayfirst, ...])

Convert argument to datetime.