flasc.flasc_dataframe

flasc.flasc_dataframe#

FLASC DataFrame module.

Classes

FlascDataFrame

Subclass of pandas.DataFrame for working with FLASC data.
class flasc.flasc_dataframe.FlascDataFrame(*args, channel_name_map=None, long_data_columns=None, **kwargs)[source]#

Subclass of pandas.DataFrame for working with FLASC data.

Stores data in preferred Flasc format, or user format, with option to convert between the two.

Want handling to go between long and wide.

_metadata: list[str] = ['channel_name_map', '_channel_name_map_inverse', '_user_format', '_long_data_columns']#
property in_flasc_format#

Return True if the data is in FLASC format, False otherwise.

property _constructor#

Used when a manipulation result has the same dimensions as the original.

_repr_html_()[source]#

Printout when displaying results in jupyter notebook.

property n_turbines#

Return the number of turbines in the dataset.

check_flasc_format()[source]#

Raise an error if the data is not in FLASC format.

copy_metadata(other)[source]#

Copy metadata from another FlascDataFrame to self.

Parameters:

other (FlascDataFrame) -- DataFrame to copy metadata from.

convert_to_user_format(inplace=False)[source]#

Convert the DataFrame to the format that the user expects, given the channel_name_map.

Parameters:

inplace (bool) -- If True, modify the DataFrame in place. If False, return a new DataFrame.

Returns:

FlascDataFrame in user format if inplace is False, None otherwise.

Return type:

FlascDataFrame

convert_time_to_datetime(inplace=False)[source]#

Convert the time column to a datetime representation.

Parameters:

inplace (bool) -- If True, modify the DataFrame in place. If False, return a new DataFrame.

Returns:

FlascDataFrame with time column as datetime object if inplace is False, None otherwise

Return type:

FlascDataFrame

convert_to_flasc_format(inplace=False)[source]#

Convert the DataFrame to the format that FLASC expects.

Parameters:

inplace (bool) -- If True, modify the DataFrame in place. If False, return a new DataFrame.

Returns:

FlascDataFrame in FLASC format if inplace is False, None otherwise

Return type:

FlascDataFrame

# TODO: could consider converting "time" to datetime type here. If so, will want to keep # the original "time" column for back-conversion if needed. # Similarly, we could sort on time, but perhaps both are too meddlesome

_convert_long_to_wide(df_)[source]#

Convert a long format DataFrame to a wide format DataFrame.

Parameters:

df (FlascDataFrame) -- Long format FlascDataFrame

Returns:

Wide format FlascDataFrame

Return type:

FlascDataFrame

_convert_wide_to_long(df_)[source]#

Convert a wide format DataFrame to a long format DataFrame.

Parameters:

df (FlascDataFrame) -- Wide format FlascDataFrame

Returns:

Long format FlascDataFrame

Return type:

FlascDataFrame

to_feather(path, **kwargs)[source]#

Raise warning about lost information and save to feather format.

export_to_windup_format(turbine_names: list[str] | None = None, time_col: str = 'time', power_col: str = 'pow', windspeed_col: str = 'ws', winddirection_col: str = 'wd', normal_operation_col: str | None = None, pitchangle_col: str | None = None, genrpm_col: str | None = None, downtimecounter_col: str | None = None, turbine_num_digits: int = 3)[source]#

Convert the DataFrame to the format that wind-up expects.

Parameters:

  • turbine_names (list[str] | None)

  • time_col (str)

  • power_col (str)

  • windspeed_col (str)

  • winddirection_col (str)

  • normal_operation_col (str | None)

  • pitchangle_col (str | None)

  • genrpm_col (str | None)

  • downtimecounter_col (str | None)

  • turbine_num_digits (int)

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