Getting Weather in DataFrame

get_weather.py

import requests
from datetime import datetime

import pandas as pd

BREST = (48.39029, -4.4833)
NANTES = (47.218371, -1.553621)

DFLT_START = datetime(2018, 1, 1)
DFLT_END = datetime.today()


def get_weather_hourly_daily(
    city: tuple[float, float], start: datetime = DFLT_START, end: datetime = DFLT_END
) -> tuple[pd.DataFrame, pd.DataFrame]:
    """Get Weather Data from Open-Meteo API for a given city"""
    # Define the API endpoint and parameters
    url = "https://archive-api.open-meteo.com/v1/era5"
    hourly = [
        "temperature_2m",
        "relativehumidity_2m",
        "apparent_temperature",
        # "precipitation_probability",  # does not work
        "precipitation",
    ]
    daily = [
        "temperature_2m_max",
        "temperature_2m_min",
        "apparent_temperature_max",
        "apparent_temperature_min",
    ]
    params = {
        "latitude": city[0],
        "longitude": city[1],
        "start_date": start.strftime("%Y-%m-%d"),
        "end_date": end.strftime("%Y-%m-%d"),
        "hourly": ",".join(hourly),
        "daily": ",".join(daily),
        "timezone": "Europe/Berlin",
    }

    # Send a GET request to the API and retrieve the data
    response = requests.get(url, params=params)
    print(response.status_code)
    data = response.json()

    # Convert the data to a Pandas DataFrame
    # df = pd.DataFrame(data["forecast"])
    df_hourly = pd.DataFrame(data["hourly"]).dropna()
    df_daily = pd.DataFrame(data["daily"]).dropna()

    for df in (df_hourly, df_daily):
        df["time"] = pd.to_datetime(df["time"])
        df["month"] = df.time.dt.month
        df["year"] = df.time.dt.year
        df.set_index("time", inplace=True)

        df.rename(columns={c: c.replace("_2m", "") for c in df.columns}, inplace=True)

    return df_hourly, df_daily
  
  
  df_hourly, df_daily = get_weather_hourly_daily(BREST)
  average_temp = df_daily.groupby(["month", "year"]).mean(numeric_only=True)
  print(average_temp.describe())