General Functions#

Data manipulations#

cudf.concat(objs[, axis, join, ...])

Concatenate DataFrames, Series, or Indices row-wise.

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

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

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

Bin values into discrete intervals.

cudf.factorize(values[, sort, ...])

Encode the input values as integer labels

cudf.get_dummies(df[, prefix, prefix_sep, ...])

Returns a dataframe whose columns are the one hot encodings of all columns in df

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

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

cudf.merge(left, right, *args, **kwargs)

Merge GPU DataFrame objects by performing a database-style join operation by columns or indexes.

cudf.pivot(data[, columns, index, values])

Return reshaped DataFrame organized by the given index and column values.

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

Create a spreadsheet-style pivot table as a DataFrame.

cudf.unstack(df, level[, fill_value])

Pivot one or more levels of the (necessarily hierarchical) index labels.

Top-level conversions#

cudf.to_numeric(arg[, errors, downcast])

Convert argument into numerical types.

cudf.from_dataframe(df[, allow_copy])


Converts from a DLPack tensor to a cuDF object.

cudf.from_pandas(obj[, nan_as_null])

Convert certain Pandas objects into the cudf equivalent.

Top-level dealing with datetimelike data#

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

Convert argument to datetime.

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

Return a fixed frequency DatetimeIndex.

Top-level dealing with Interval data#

cudf.interval_range([start, end, periods, ...])

Returns a fixed frequency IntervalIndex.