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.

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