load_from_tsfile_to_dataframe#
- load_from_tsfile_to_dataframe(full_file_path_and_name, return_separate_X_and_y=True, replace_missing_vals_with='NaN', encoding='utf-8')[source]#
Load data from a .ts file into a Pandas DataFrame.
- Parameters:
- full_file_path_and_name: str
The full pathname of the .ts file to read.
- return_separate_X_and_y: bool
true if X and Y values should be returned as separate Data Frames ( X) and a numpy array (y), false otherwise. This is only relevant for data that
- replace_missing_vals_with: str
The value that missing values in the text file should be replaced with prior to parsing.
- encoding: str
encoding is the name of the encoding used to read file using the open function.
- Returns:
- DataFrame (default) or ndarray (i
If return_separate_X_and_y then a tuple containing a DataFrame and a numpy array containing the relevant time-series and corresponding class values.
- DataFrame
If not return_separate_X_and_y then a single DataFrame containing all time-series and (if relevant) a column “class_vals” the associated class values.