General Functions#

Data manipulations#

cudf.concat(objs[, axis, join, ...])

Concatenate DataFrames, Series, or Indices row-wise.

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

Bin values into discrete intervals.

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

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

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.


Converts from a DLPack tensor to a cuDF object.

Top-level dealing with datetimelike#

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

Convert argument to datetime.