dataframes#

Contain functions for handling dataframes in checks.

Functions

validate_columns_exist(df, columns[, ...])

Validate given columns exist in dataframe.

select_from_dataframe(df[, columns, ...])

Filter DataFrame columns by given params.

un_numpy(val)

Convert numpy value to native value.

generalized_corrwith(x1, x2, method)

Compute pairwise correlation.

floatify_dataframe(df)

Return a dataframe where all the int columns are converted to floats.

floatify_series(ser)

Return a series that if the type is int converted to float.

default_fill_na_per_column_type(df, cat_features)

Fill NaN values per column type.

is_float_column(col)

Check if a column must be a float - meaning does it contain fractions.

default_fill_na_series(col[, is_cat_column])

Fill NaN values based on column type if possible otherwise returns None.

cast_categorical_to_object_dtype(df)

Cast categorical columns to the object dtype.

hide_index_for_display(df)

Hide the index of a dataframe for display.