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- builtins.object
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- retreive_data
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- Filter
- Interactive_maps
class Filter(retreive_data) |
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Filter(apiKey, apiSecret)
# Move the functions to a class
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- Method resolution order:
- Filter
- retreive_data
- builtins.object
Methods defined here:
- __init__(self, apiKey, apiSecret)
- Initialize self. See help(type(self)) for accurate signature.
- calculate_new_point(self, lat, lon, distance, bearing)
- Calculate a new point given a starting point, distance, and bearing.
:param lat: starting latitude in degrees
:param lon: starting longitude in degrees
:param distance: distance to move in meters
:param bearing: bearing to move in degrees (0 is north)
:return: tuple containing the new latitude and longitude in degrees
- compute_filter(self, lat, lon, distance)
- Calculates the bounding box coordinates for a given location and distance.
Parameters:
lat (float): The latitude of the location.
lon (float): The longitude of the location.
distance (float): The distance from the location, in kilometers, to the edge of the bounding box.
Returns:
A tuple containing four floats representing the bounding box coordinates: (min_lat, min_lon, max_lat, max_lon).
- filterStations(self, address, distance, startDate=None, endDate=None, csvfile='KEcheck3.csv')
- This method filters weather station data within a certain distance from a given address.
Parameters:
address (str): Address to center the bounding box around.
distance (float): The distance (in kilometers) from the center to the edge of the bounding box.
startDate (str): The start date for filtering the weather station data in the format 'YYYY-MM-DD'.
endDate (str): The end date for filtering the weather station data in the format 'YYYY-MM-DD'.
csvfile (str): The name of the csv file containing the weather station data.
Returns:
pandas.DataFrame: The filtered weather station data within the bounding box.
- filterStationsList(self, address, distance=100)
- Filters stations based on their proximity to a given address and returns a list of station codes that fall within the specified distance.
Args:
address (str): Address to filter stations by.
distance (float, optional): Maximum distance (in kilometers) between the stations and the address. Default is 100 km.
Returns:
List of station codes that fall within the specified distance from the given address.
- getLocation(self, address)
- This method retrieves the latitude and longitude coordinates of a given address using the Nominatim API.
Parameters:
-----------
address : str
The address of the location you want to retrieve the coordinates for.
Returns:
--------
Tuple (float, float)
The latitude and longitude coordinates of the location.
- get_stations_info(self, station=None, multipleStations=[], countrycode=None)
- Retrieves information about weather stations from an API endpoint and returns relevant information based on the parameters passed to it.
Args:
station (str, optional): Code for a single station to retrieve information for. Defaults to None.
multipleStations (list, optional): List of station codes to retrieve information for multiple stations. Defaults to [].
countrycode (str, optional): Country code to retrieve information for all stations located in the country. Defaults to None.
Returns:
pandas.DataFrame: DataFrame containing information about the requested weather stations.
Methods inherited from retreive_data:
- aggregate_variables(self, dataframe)
- Aggregates a pandas DataFrame of weather variables by summing values across each day.
Args:
dataframe (pandas.DataFrame): DataFrame containing weather variable data.
Returns:
pandas.DataFrame: DataFrame containing aggregated weather variable data, summed by day.
- get_measurements(self, station, startDate=None, endDate=None, variables=None, dataset='controlled', aggregate=False)
- Get measurements for a specified station and time period.
:param station: The station ID for which to retrieve measurements.
:type station: str
:param startDate: The start date of the time period for which to retrieve measurements.
:type startDate: datetime or str, optional
:param endDate: The end date of the time period for which to retrieve measurements.
:type endDate: datetime or str, optional
:param variables: A list of variable shortcodes to retrieve measurements for. If None, all variables are retrieved.
:type variables: list or None, optional
:param dataset: The dataset to retrieve measurements from. Default is 'controlled'.
:type dataset: str, optional
:param aggregate: Whether to aggregate variables by sensor ID. Default is False.
:type aggregate: bool, optional
:return: A Pandas DataFrame containing the requested measurements.
:rtype: pandas.DataFrame
- get_variables(self)
- Retrieves information about available weather variables from an API endpoint.
Returns:
dict: Dictionary containing information about available weather variables, keyed by variable shortcode.
- k_neighbours(self, station, number=5)
- Returns a dictionary of the nearest neighbouring stations to the specified station.
Args:
station (str): Code for the station to find neighbouring stations for.
number (int, optional): Number of neighbouring stations to return. Defaults to 5.
Returns:
dict: Dictionary containing the station codes and distances of the nearest neighbouring stations.
- multiple_measurements(self, stations_list, csv_file, startDate, endDate, variables, dataset='controlled')
- Retrieves measurements for multiple stations and saves the aggregated data to a CSV file.
Parameters:
stations_list (list): A list of strings containing the names of the stations to retrieve data from.
csv_file (str): The name of the CSV file to save the data to.
startDate (str): The start date for the measurements, in the format 'yyyy-mm-dd'.
endDate (str): The end date for the measurements, in the format 'yyyy-mm-dd'.
variables (list): A list of strings containing the names of the variables to retrieve.
dataset (str): The name of the dataset to retrieve the data from. Default is 'controlled'.
Returns:
df (pandas.DataFrame): A DataFrame containing the aggregated data for all stations.
Raises:
ValueError: If stations_list is not a list.
- raw_measurements(self, station, startDate=None, endDate=None, variables=None)
Data descriptors inherited from retreive_data:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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class Interactive_maps(retreive_data) |
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Interactive_maps(apiKey, apiSecret)
# A different class for visualisations
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- Method resolution order:
- Interactive_maps
- retreive_data
- builtins.object
Methods defined here:
- __init__(self, apiKey, apiSecret)
- Initialize self. See help(type(self)) for accurate signature.
- create_animation(self, data, valid_sensors, day=100, T=10, interval=500)
- Creates an animation of pollutant levels for a given range of days and valid sensors.
Parameters:
data (DataFrame): A pandas DataFrame containing pollution data.
valid_sensors (list): A list of valid sensor names.
day (int): The starting day of the animation (default is 100).
T (int): The range of days for the animation (default is 10).
interval (int): The interval between frames in milliseconds (default is 500).
Returns:
HTML: An HTML object containing the animation.
- draw_map(self, map_center)
- Creates a Folium map centered on the specified location and adds markers for each weather station in the area.
Args:
map_center: a tuple with the latitude and longitude of the center of the map
Returns:
A Folium map object
- encode_image(self, ws, df_rainfall)
- Encodes a station's rainfall data plot as a base64-encoded image.
Args:
- ws (str): the code for the station to encode the image for
- df_rainfall (pandas.DataFrame): a DataFrame containing the rainfall data for all stations
Returns:
- str: a string containing an HTML image tag with the encoded image data, or a message indicating no data is available for the given station
- get_map(self, subset_list, start_date=None, end_date=None, data_values=False, csv_file='KEcheck3.csv', min_zoom=8, max_zoom=11, width=850, height=850, png_resolution=300)
- Creates a Folium map showing the locations of the weather stations in the given subsets.
Parameters:
-----------
subset_list : list of lists of str
List of subsets of weather stations, where each subset is a list of station codes.
start_date : str, optional
Start date in the format YYYY-MM-DD, default is None.
end_date : str, optional
End date in the format YYYY-MM-DD, default is None.
data_values : bool, optional
If True, the map markers will display a plot of rainfall data, default is False.
csv_file : str, optional
The name of the CSV file containing the rainfall data, default is 'KEcheck3.csv'.
min_zoom : int, optional
The minimum zoom level of the map, default is 8.
max_zoom : int, optional
The maximum zoom level of the map, default is 11.
width : int, optional
The width of the map in pixels, default is 850.
height : int, optional
The height of the map in pixels, default is 850.
png_resolution : int, optional
The resolution of the PNG image if data_values is True, default is 300.
Returns:
--------
my_map : folium.folium.Map
A Folium map object showing the locations of the weather stations in the given subsets.
- plot_station(self, ws, df_rainfall)
- Plot the rainfall data for a specific weather station.
Args:
- ws: string, the code of the weather station to plot
- df_rainfall: DataFrame, a pandas DataFrame with rainfall data
Returns:
- None if no data is available for the specified station
- a Matplotlib figure showing rainfall data for the specified station otherwise
Methods inherited from retreive_data:
- aggregate_variables(self, dataframe)
- Aggregates a pandas DataFrame of weather variables by summing values across each day.
Args:
dataframe (pandas.DataFrame): DataFrame containing weather variable data.
Returns:
pandas.DataFrame: DataFrame containing aggregated weather variable data, summed by day.
- get_measurements(self, station, startDate=None, endDate=None, variables=None, dataset='controlled', aggregate=False)
- Get measurements for a specified station and time period.
:param station: The station ID for which to retrieve measurements.
:type station: str
:param startDate: The start date of the time period for which to retrieve measurements.
:type startDate: datetime or str, optional
:param endDate: The end date of the time period for which to retrieve measurements.
:type endDate: datetime or str, optional
:param variables: A list of variable shortcodes to retrieve measurements for. If None, all variables are retrieved.
:type variables: list or None, optional
:param dataset: The dataset to retrieve measurements from. Default is 'controlled'.
:type dataset: str, optional
:param aggregate: Whether to aggregate variables by sensor ID. Default is False.
:type aggregate: bool, optional
:return: A Pandas DataFrame containing the requested measurements.
:rtype: pandas.DataFrame
- get_stations_info(self, station=None, multipleStations=[], countrycode=None)
- Retrieves information about weather stations from an API endpoint and returns relevant information based on the parameters passed to it.
Args:
station (str, optional): Code for a single station to retrieve information for. Defaults to None.
multipleStations (list, optional): List of station codes to retrieve information for multiple stations. Defaults to [].
countrycode (str, optional): Country code to retrieve information for all stations located in the country. Defaults to None.
Returns:
pandas.DataFrame: DataFrame containing information about the requested weather stations.
- get_variables(self)
- Retrieves information about available weather variables from an API endpoint.
Returns:
dict: Dictionary containing information about available weather variables, keyed by variable shortcode.
- k_neighbours(self, station, number=5)
- Returns a dictionary of the nearest neighbouring stations to the specified station.
Args:
station (str): Code for the station to find neighbouring stations for.
number (int, optional): Number of neighbouring stations to return. Defaults to 5.
Returns:
dict: Dictionary containing the station codes and distances of the nearest neighbouring stations.
- multiple_measurements(self, stations_list, csv_file, startDate, endDate, variables, dataset='controlled')
- Retrieves measurements for multiple stations and saves the aggregated data to a CSV file.
Parameters:
stations_list (list): A list of strings containing the names of the stations to retrieve data from.
csv_file (str): The name of the CSV file to save the data to.
startDate (str): The start date for the measurements, in the format 'yyyy-mm-dd'.
endDate (str): The end date for the measurements, in the format 'yyyy-mm-dd'.
variables (list): A list of strings containing the names of the variables to retrieve.
dataset (str): The name of the dataset to retrieve the data from. Default is 'controlled'.
Returns:
df (pandas.DataFrame): A DataFrame containing the aggregated data for all stations.
Raises:
ValueError: If stations_list is not a list.
- raw_measurements(self, station, startDate=None, endDate=None, variables=None)
Data descriptors inherited from retreive_data:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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class retreive_data(builtins.object) |
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retreive_data(apiKey, apiSecret)
# Get data class
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Methods defined here:
- __init__(self, apiKey, apiSecret)
- Initialize self. See help(type(self)) for accurate signature.
- aggregate_variables(self, dataframe)
- Aggregates a pandas DataFrame of weather variables by summing values across each day.
Args:
dataframe (pandas.DataFrame): DataFrame containing weather variable data.
Returns:
pandas.DataFrame: DataFrame containing aggregated weather variable data, summed by day.
- get_measurements(self, station, startDate=None, endDate=None, variables=None, dataset='controlled', aggregate=False)
- Get measurements for a specified station and time period.
:param station: The station ID for which to retrieve measurements.
:type station: str
:param startDate: The start date of the time period for which to retrieve measurements.
:type startDate: datetime or str, optional
:param endDate: The end date of the time period for which to retrieve measurements.
:type endDate: datetime or str, optional
:param variables: A list of variable shortcodes to retrieve measurements for. If None, all variables are retrieved.
:type variables: list or None, optional
:param dataset: The dataset to retrieve measurements from. Default is 'controlled'.
:type dataset: str, optional
:param aggregate: Whether to aggregate variables by sensor ID. Default is False.
:type aggregate: bool, optional
:return: A Pandas DataFrame containing the requested measurements.
:rtype: pandas.DataFrame
- get_stations_info(self, station=None, multipleStations=[], countrycode=None)
- Retrieves information about weather stations from an API endpoint and returns relevant information based on the parameters passed to it.
Args:
station (str, optional): Code for a single station to retrieve information for. Defaults to None.
multipleStations (list, optional): List of station codes to retrieve information for multiple stations. Defaults to [].
countrycode (str, optional): Country code to retrieve information for all stations located in the country. Defaults to None.
Returns:
pandas.DataFrame: DataFrame containing information about the requested weather stations.
- get_variables(self)
- Retrieves information about available weather variables from an API endpoint.
Returns:
dict: Dictionary containing information about available weather variables, keyed by variable shortcode.
- k_neighbours(self, station, number=5)
- Returns a dictionary of the nearest neighbouring stations to the specified station.
Args:
station (str): Code for the station to find neighbouring stations for.
number (int, optional): Number of neighbouring stations to return. Defaults to 5.
Returns:
dict: Dictionary containing the station codes and distances of the nearest neighbouring stations.
- multiple_measurements(self, stations_list, csv_file, startDate, endDate, variables, dataset='controlled')
- Retrieves measurements for multiple stations and saves the aggregated data to a CSV file.
Parameters:
stations_list (list): A list of strings containing the names of the stations to retrieve data from.
csv_file (str): The name of the CSV file to save the data to.
startDate (str): The start date for the measurements, in the format 'yyyy-mm-dd'.
endDate (str): The end date for the measurements, in the format 'yyyy-mm-dd'.
variables (list): A list of strings containing the names of the variables to retrieve.
dataset (str): The name of the dataset to retrieve the data from. Default is 'controlled'.
Returns:
df (pandas.DataFrame): A DataFrame containing the aggregated data for all stations.
Raises:
ValueError: If stations_list is not a list.
- raw_measurements(self, station, startDate=None, endDate=None, variables=None)
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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