surveyweathertool.src.dashboard.utils

Module Contents

Functions

read_logos(logos_path)	Reads and returns the STC, UNICEF, DSA, and NOAA logos from the provided path.
filter_weather(weather_df, year[, month, season])	Filters the given DataFrame based on the provided year, month, or season.
filter_survey(survey_df[, wave, target_epsg])	Filters the given survey DataFrame based on the provided wave.
check_if_df_has_lat_long(df)	Checks if a dataframe has columns named "lat" and "long".
preprocess_data_input(→ pandas.DataFrame)	Lower-cases all column names and converts date column to datetime.
preprocess_weather_data(→ pandas.DataFrame)	Lower-cases all column names, converts date column to datetime & gets year/month as features.
load_data_from_google_drive(file_to_load)	Load data from Google Drive into a DataFrame
dataframe_reader(→ pandas.DataFrame)	Read data from various file formats and return a DataFrame.

surveyweathertool.src.dashboard.utils.read_logos(logos_path)

Reads and returns the STC, UNICEF, DSA, and NOAA logos from the provided path.

Parameters:

logos_pathstr

The path to the directory containing the logo images.

Returns:

tuple of PIL.Image.Image

The STC, UNICEF, and DSA logos as PIL Image objects.

surveyweathertool.src.dashboard.utils.filter_weather(weather_df: pandas.DataFrame, year: int, month: int = None, season: str = None)

Filters the given DataFrame based on the provided year, month, or season.

Parameters:

weather_dfpandas.DataFrame

The DataFrame to filter.

yearint

The year to filter on. Can be a specific year as a string or “All Years” to include all years.

monthint, optional

The month to filter on. Can be a specific month as an integer (1-12) or None.

seasonstr, optional

The season to filter on. Can be a specific season as a string or None.

Returns:

pandas.DataFrame

The filtered DataFrame.

surveyweathertool.src.dashboard.utils.filter_survey(survey_df: pandas.DataFrame, wave: int = 1, target_epsg: int = 4326)

Filters the given survey DataFrame based on the provided wave.

Parameters:

survey_dfpandas.DataFrame

The DataFrame to filter.

waveint, Optional

The wave to filter on. Can be a specific wave. Defaults to 1.

Returns:

pandas.DataFrame

The filtered DataFrame.

surveyweathertool.src.dashboard.utils.check_if_df_has_lat_long(df: pandas.DataFrame)

Checks if a dataframe has columns named “lat” and “long”.

Keyword arguments: df – the dataframe to check

surveyweathertool.src.dashboard.utils.preprocess_data_input(df: pandas.DataFrame) → pandas.DataFrame

Lower-cases all column names and converts date column to datetime.

Keyword arguments: df – the dataframe to check

surveyweathertool.src.dashboard.utils.preprocess_weather_data(df: pandas.DataFrame) → pandas.DataFrame

Lower-cases all column names, converts date column to datetime & gets year/month as features.

Keyword arguments: df – the dataframe to preprocess

surveyweathertool.src.dashboard.utils.load_data_from_google_drive(file_to_load: str)

Load data from Google Drive into a DataFrame :param file_to_load: The ID of the file to load from Google Drive :return: A DataFrame containing the data from the file

surveyweathertool.src.dashboard.utils.dataframe_reader(file_path: pathlib.Path, use_columns: List[str] | None = None, reset_index=False, *kwargs) → pandas.DataFrame

Read data from various file formats and return a DataFrame.

Parameters:

file_path (Path): The path to the input file. use_columns (Optional[List[str]]): A list of column names to include in the DataFrame.

If None, all columns will be included. Default is None.

reset_index (bool): Flag if want to reset index from original file. *kwargs (Optional[List]): Any keyword arguments to be passed to pandas reader function

Returns:

pd.DataFrame: A DataFrame containing the data from the input file.

Raises:

ValueError: If the file type is not supported.

Note:

Supported file formats: ‘.csv’, ‘.sav’, ‘.dta’, ‘.pickle’.