paradance.dataloader.BaseDataLoader

class paradance.dataloader.BaseDataLoader(file_path: str | None = None, file_name: str | None = None, file_type: str | None = 'csv', max_rows: int | None = None, clean_zero_columns: bool | List | None = None, config: Dict | None = None)

Base class for data loaders.

__init__(file_path: str | None = None, file_name: str | None = None, file_type: str | None = 'csv', max_rows: int | None = None, clean_zero_columns: bool | List | None = None, config: Dict | None = None) → None

Methods

__init__([file_path, file_name, file_type, ...])
add_one_smoothing(column)	Add one smoothing to a column.
clean_columns_zero([columns])	Clean columns with all zeros.
clean_one_label_users(df[, user_column, ...])	Remove users with only one label.
clip_and_sum_with_group(df, groupby, clip_column)	Clip and sum with group.
clip_clean_count_with_group(df, groupby, ...)	Clip and count with group.
column_name_spliting([delimiter])	Split column names by delimiter.
load_data()	Load data from file.

abstract load_data() → DataFrame

Load data from file.

column_name_spliting(delimiter: str = '.') → None

Split column names by delimiter.

add_one_smoothing(column: str) → None

Add one smoothing to a column.

Parameters:

column – column name

clean_columns_zero(columns: bool | List = False) → None

Clean columns with all zeros.

Parameters:

columns – columns to clean

static clip_and_sum_with_group(df: DataFrame, groupby: str, clip_column: str) → Series | None

Clip and sum with group.

Parameters:

• df – dataframe

• groupby – groupby column

• clip_column – column to clip

static clean_one_label_users(df: DataFrame, user_column: str = 'user_id', label_column: str = 'label') → DataFrame

Remove users with only one label.

Parameters:

• df – dataframe

• user_column – user column name

• label_column – label column name

static clip_clean_count_with_group(df: DataFrame, groupby: str, label_column: str, clip_column: str | None = None) → Tuple

Clip and count with group.

Parameters:

• df – dataframe

• groupby – groupby column

• clip_column – column to clip

• label_column – label column