- resqpy.olio.wellspec_keywords.get_all_well_data(file: TextIO, well_name: str, pointers: List[Tuple[int, Union[None, str]]], column_list: List[str] = , selecting: bool = False, keep_duplicate_cells: bool = False, keep_null_columns: bool = True, last_data_only: bool = True) Optional[DataFrame] [source]¶
Creates a dataframe of all the well data for a given well name in the wellspec file.
This differs from the get_well_data function in that here multiple datasets for a well are combined into a single dataframe if they exist.
file (TextIO) – the opened wellspec file object.
well_name (str) – name of the well.
pointers (List[Tuple[int, None/str]]) – a list of the file object’s start position of the well data represented as number of bytes from the beginning of the file and the well’s date. If no date existed before the well in the file, the date will be None.
column_list (List[str]) – if present, each dataframe returned contains these columns, in this order. If None, the resulting dictionary contains only well names as keys (each mapping to None rather than a dataframe). If an empty list (default), each dataframe contains the columns listed in the corresponding wellspec header, in the order found in the file.
selecting (bool) – True if the column_list contains at least one column name, False otherwise (default).
keep_duplicate_cells (bool) – if True (default), duplicate cells are kept, otherwise only the last entry is kept.
keep_null_columns (bool) – if True (default), columns that contain all NA values are kept, otherwise they are removed.
last_data_only (bool) – If True, only the last entry of well data in the file are used in the dataframe, otherwise all of the well data are used at different times.
Pandas dataframe of all well data for a specific well name or None if all the data are NA.