Polar, frost climate coverage

Key: koeppen_ef | Category: Climatic

Spatial and temporal coverage
Shape type	First	Last	Coverage
Country			100.00 %
Region			100.00 %
District			100.00 %
Total	1901	2020	100.00 %

Data Layer information

Source file is available (Show file)

from datalayers.datasources.koeppen_layer import KoeppenLayer


class KoeppenEf(KoeppenLayer):
    def __init__(self) -> None:
        super().__init__()

        self.climate_types = [
            self.ClimateTypes.EF,
        ]

Data is available locally

Data is loaded into the database

Log | Files

Operation
Database unit
Value type	`percentage`
Temporal resolution	`year`

Original data information

Information	Description
Format	GeoTiff
Format unit
Spatial details
Spatial coverage
Temporal details
Temporal coverage
Source
Language
License
Date published
Date last accessed	None
Citation

The Data Layers data can be accessed via an API. Below you see minimal code snippets to query the data. For more information regarding the API please look at the documentation.

import requests
from requests.auth import HTTPBasicAuth
from urllib.parse import urlencode

import pandas as pd
import matplotlib.pyplot as plt

# set host, like http://localhost:8000, to where your Data Hub is running
HOST = ''
# in case of basic auth set to HTTPBasicAuth('user', 'password')
AUTH = None

q = {
    'datalayer_key': 'koeppen_ef',

    # Optional filters to narrow down the returned data:
    #'shape_id': '',
    #'shape_type': '',
    #'start_date': '',
    #'end_date': '',
}
d = requests.get(f"{HOST}/api/datalayers/data/?{urlencode(q)}", auth=AUTH).json()
koeppen_ef_df = pd.DataFrame(d['data'])
koeppen_ef_df['year'] = pd.to_datetime(koeppen_ef_df['year'], format="%Y")

There is no ready use snippet for API usage in R yet, though you can adapt the Python example to your R needs.

Polar, frost climate coverage

Data Layer information

src/datalayer/koeppen_ef.py

Original data information