create_empty_ts¶

Inputs¶

scenarios_dirstr: scenarios: path to scenarios directory
destinationstr: raw/time_series/empty_ts_efficiencies.csv: path of output directory for empty ts with efficiencies of all scenarios raw/time_series/empty_ts_feedin.csv: path of output directory for empty ts with feedins of all scenarios raw/time_series/empty_ts_load.csv: path of output directory for empty ts with loads of all scenarios

Outputs¶

pandas.DataFrame: Empty ts in oemof-B3 resource format.

Description¶

The script creates empty DataFrames for load, feed-in and efficiency time series data that serve as template for input data.

create_empty_ts.create_empty_ts(name)¶

This function provides a Dataframe with a time series of zeros according to the start, periods and freq of the scenario specifications

Parameters: name (str) – Name of the ts
Returns: df – Dataframe containing ts with zeros as values and name as column name
Return type: Dataframe

create_empty_ts.create_empty_ts_with_zero_or_nan_values(periods, date_rng, name)¶

Returns a pandas DataFrame with time series values set to either zeros or NaNs, based on settings.yaml

Parameters

periods (int) – Number of periods in the time series
date_rng (pd.DatetimeIndex) – Datetime index specifying start and end dates of the time series
name (str) – Name of the time series column in the DataFrame

Returns

df – A pandas DataFrame containing the time series values, with ‘name’ as the column name.

Return type

pd.DataFrame

Raises

KeyError – If settings.create_empty_ts.ts_values is not set to either ‘zeros’ or ‘empty’.

create_empty_ts.drop_duplicates(_df)¶

Remove duplicate rows from a pandas DataFrame based on specified columns.

Parameters: _df (pandas DataFrame) – The DataFrame to remove duplicates from.
Returns: _df – The updated DataFrame with duplicate rows removed.
Return type: pandas DataFrame

Notes

Duplicate rows are determined based on the values in the specified columns. By default, all columns except the “series” column are used to determine duplicates. If there are multiple rows with the same values in the specified columns, only the first occurrence is kept and subsequent occurrences are dropped.

create_empty_ts.get_df_of_all_empty_ts(profile_names, _region)¶

This function provides a Dataframe with all ts of a profile (load, feedin or efficiency)

Inputs¶

profile_nameslist: List with names of profiles (loads, feedins or efficiencies)
_regionstr: Region

Outputs¶

ts_dfDataframe: Dataframe with empty time series (consisting of zeros)

create_empty_ts.get_sub_dict(subsub_key, _dict)¶

This function extracts a subsub-dictionary from a dictionary using a subsub-key

Inputs¶

subsub_keystr: Key of the subsub-dictionary
_dictdict: Dictionary with two inner dictionaries

Outputs¶

subsub_dictdictionary: Subsub-dictionary

create_empty_ts.save_ts(_df, path)¶

This function saves time series that contain values of datetime format Datetime format used: “%Y-%m-%d %H:%M:%S”

Parameters

_df (Dataframe) – Dataframe with value(s) of datetime format
path (str) – Path where df is saved to