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This package is used to retrieve and transform historical weather data from www.worldweatheronline.com into pandas dataframe and csv.

Project description

WorldWeatherOnline historical weather data API wrapper

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This package is used to retrieve and transform historical weather data from www.worldweatheronline.com into pandas dataframe and csv.

You can get API key for free (free trial 500 requests/key/day for 60 days, as of 30-May-2019).

example API explorer: https://www.worldweatheronline.com/developer/premium-api-explorer.aspx

Input: api_key, location_list, start_date, end_date, frequency

Output: location_name.csv

Output column names: date_time, maxtempC, mintempC, totalSnow_cm, sunHour, uvIndex, uvIndex, moon_illumination, moonrise, moonset, sunrise, sunset, DewPointC, FeelsLikeC, HeatIndexC, WindChillC, WindGustKmph, cloudcover, humidity, precipMM, pressure, tempC, visibility, winddirDegree, windspeedKmph

Install the package:

pip install wwo-hist

Import package

from wwo_hist import retrieve_hist_data

Set working directory to store output csv file(s)

import os
os.chdir(".\YOUR_PATH")

Example code

frequency=3
start_date = '11-DEC-2018'
end_date = '11-MAR-2019'
api_key = 'YOUR_API_KEY'
location_list = ['singapore','california']

hist_weather_data = retrieve_hist_data(api_key,
                                location_list,
                                start_date,
                                end_date,
                                frequency,
                                location_label = False,
                                export_csv = True,
                                store_df = True)

Parameters:

api_key: string

(Premium/ free trial) API key from https://www.worldweatheronline.com/developer/api/

location_list: list of string

US Zipcode, UK Postcode, Canada Postalcode, IP address, Latitude/Longitude (decimal degree) or city name

start_date: string

Preferred date format: 'dd-mmm-yyyy'

end_date: string

Preferred date format: 'dd-mmm-yyyy'

frequency: integer

1, 3, 6, 12, 24

1 hourly, 3 hourly, 6 hourly, 12 hourly (day/night) or 24 hourly (day average)

location_label: bool, default = False

If True, all column names will have city name as prefix.

export_csv: bool, default = True

If False, no csv file will be exported to current directory.

store_df: bool, default = False

If True, retrieved dataframe(s) will be stored as list in the work space.

Console view

IPython

Output file

CSV file

Project details


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