Check
Check data format
- heatpro.check.check_data_format.check_datetime_index(dataframe: DataFrame) bool[source]
Check if the index of a DataFrame is in datetime format.
- Parameters:
dataframe (pd.DataFrame) – data
- Returns:
True if the index is in datetime format, False otherwise.
- heatpro.check.check_data_format.check_energy_feature(dataframe: DataFrame) bool[source]
Check if the DataFrame contains a column with energy information.
- Parameters:
dataframe (pd.DataFrame) – data
- Returns:
True if column ENERGY_FEATURE_NAME is present, False otherwise
- Return type:
bool
- heatpro.check.check_data_format.find_duplicate_days(datetime_index: DatetimeIndex)[source]
Find and return a DataFrame containing (year, month, day) tuples that appear more than once in the given DatetimeIndex.
- Parameters:
datetime_index – pd.DatetimeIndex
- Returns:
DataFrame with columns ‘Year’, ‘Month’, ‘Day’ representing (year, month, day) tuples with multiple appearances.
- heatpro.check.check_data_format.find_duplicate_hours(datetime_index: DatetimeIndex)[source]
Find and return a DataFrame containing (year, month, day, hour) tuples that appear more than once in the given DatetimeIndex.
- Parameters:
datetime_index – pd.DatetimeIndex
- Returns:
DataFrame with columns ‘Year’, ‘Month’, ‘Day’, ‘Hour’ representing (year, month, day, hour) tuples with multiple appearances.
- heatpro.check.check_data_format.find_duplicate_months(datetime_index: DatetimeIndex)[source]
Find and return a DataFrame containing (year, month) tuples that appear more than once in the given DatetimeIndex.
- Parameters:
datetime_index – pd.DatetimeIndex
- Returns:
DataFrame with columns ‘Year’, ‘Month’ representing (year, month) tuples with multiple appearances.
- heatpro.check.check_data_format.find_xor_dates(df_left: DataFrame, df_right: DataFrame) DataFrame[source]
Find dates that are not in both index
- Parameters:
df_left (pd.DataFrame) – left DataFrame
df_right (pd.DataFrame) – right DataFrame
- Returns:
Dataframe showing of dates that are not in both index
- Return type:
pd.DataFrame
- heatpro.check.check_data_format.find_xor_hour(df_left: DataFrame, df_right: DataFrame) DataFrame[source]
Find hours that are not in both index
- Parameters:
df_left (pd.DataFrame) – left DataFrame
df_right (pd.DataFrame) – right DataFrame
- Returns:
Dataframe showing of hours that are not in both index
- Return type:
pd.DataFrame
- heatpro.check.check_data_format.find_xor_months(df_left: DataFrame, df_right: DataFrame) DataFrame[source]
Find month that are not in both index
- Parameters:
df_left (pd.DataFrame) – left DataFrame
df_right (pd.DataFrame) – right DataFrame
- Returns:
Dataframe showing of month that are not in both index
- Return type:
pd.DataFrame
Check weight format
- heatpro.check.check_weight_format.check_weight_format(weights: DataFrame) None[source]
Verify that DataFrame format is correct to be used as weight for potentially future disaggregation.
- Parameters:
weights (pd.DataFrame) – DataFrame having to role of containing weights
- Raises:
ValueError – Should have DatetimeIndex
ValueError – Should contain WEIGHT_NAME_REQUIRED column