Chisle
코딩 에이전트 플러그인, 20개 실시간 작업에서 기본 모델 52% 활용, 간결한 페르소나와 출력 압축 제공
Python으로 과거 날씨·기후 데이터를 조회하고 분석합니다
Access and analyze historical weather and climate data with Python.
개발 도구PythonGitHub @meteostat직접 설치운영자 미확인
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메이커가 쓴 소개는 위의 한 줄이 전부입니다. 더 자세한 내용은 저장소 README에서 읽을 수 있습니다. 저장소 README ↗
README 전체를 불러오는 중입니다.
README 전문 보기 ↗The Meteostat Python package is available through PyPI:
pip install meteostat
Let's plot 2018 temperature data for Frankfurt, Germany:
from datetime import date
import matplotlib.pyplot as plt
import meteostat as ms
# Specify location and time range
POINT = ms.Point(50.1155, 8.6842, 113) # Try with your location
START = date(2018, 1, 1)
END = date(2018, 12, 31)
# Get nearby weather stations
stations = ms.stations.nearby(POINT, limit=4)
# Get daily data & perform interpolation
ts = ms.daily(stations, START, END)
df = ms.interpolate(ts, POINT).fetch()
# Plot line chart including average, minimum and maximum temperature
df.plot(y=[ms.Parameter.TEMP, ms.Parameter.TMIN, ms.Parameter.TMAX])
plt.show()
Take a look at the expected output:
Please read our contributing guidelines for details on how to contribute to the Meteostat Python library.
Meteostat has been featured and used by various media outlets and organizations, including:
Join the growing community of users and researchers relying on Meteostat for their weather data needs.
Meteostat is licensed under the MIT License. Data provided by Meteostat is generally licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Please refer to the documentation for more information.