def missing_values_table(dataframe, na_name=False):na_columns = [col for col in dataframe.columns if dataframe[col].isnull.sum > 0] n_miss = dataframe[na_columns].isnull.sum.sort_values(ascending=False)ratio = (dataframe[na_columns].isnull.sum / dataframe.shape[0] * 100).sort_value...
def missing_values_table(dataframe, na_name=False):na_columns = [col for col in dataframe.columns if dataframe[col].isnull.sum > 0] n_miss = dataframe[na_columns].isnull.sum.sort_values(ascending=False)ratio = (dataframe[na_columns].isnull.sum / dataframe.shape[0] * 100).sort_value...
to_pandas write_csv write_parquet to_numpy shape get_column to_dict row pipe drop_nulls with_row_index schema collect_schema columns rows iter_rows select rename head tail drop unique filter sort is_duplicated is_empty is_unique null_count item clone gather_every to_arrow sample unpivot Lazy...