如何在meteostat的函数Point(lat=float,lon=float)中使用填充有浮点数的列？ Python

Question

我正在尝试使用 Daily(Point(lat,lon), start-date, end-date) 构建数据框， 的函数meteostat 库，使用纬度和经度返回由 Point(lat,lon) 指示的位置从开始日期到结束日期的所有每日天气统计数据。

问题是 (lat, lon) 参数必须是 float ，因此只能指示一个位置。我想添加几个地点并收集每个地点的每日气象数据。

import meteostat
from datetime import datetime
from meteostat import Point, Daily
import matplotlib.pyplot as plt
from meteostat import Stations
import pandas as pd
import numpy 

data = pd.read_csv(r'C:\Users\leoac\OneDrive\Desktop\Coding\Python apps\Correlation temp-goals in Serie A\seasons 09-19.csv', ";")
date_not_converted = data['Date']
date_being_converted = datetime.strptime(date_not_converted,'%d,%m,%Y')             #1bis non può essere una serie...allora provo a cambiare il tipo di dati
date = date_being_converted.strftime('%Y,%m,%d')

#plot = Daily(Point(data['lat'][15],data['lon'][15]),d1,d2).fetch()
data['temp']  = Daily(Point(data['lat'][1],data['lon'][1]),datetime(date),datetime(date)).fetch() #1 sistemare il formato data
print(data['temp'])                                                                               #2 trovare un modo per inserire i vettori date e lat/lon nel df
data['temp'].plot(y=['tavg'])
plt.show()

print(data)

Answer 1

这是一个受this github issue 启发的解决方案。它对不同位置发出并行请求，然后将结果合并到 pandas 数据帧中。

from datetime import datetime
from meteostat import Point, Daily
from multiprocessing import cpu_count

from joblib import Parallel, delayed
import pandas as pd

def get_bulk_data(row):
    location = Point(row.lat, row.lon)
    data = Daily(location, row.Date, row.Date).fetch()
    data["latitude"] = row.lat
    data["longitude"] = row.lon
    return data

if __name__ == "__main__":
    df = pd.read_csv("seasons.csv", sep=";")
    df["Date"] = pd.to_datetime(df["Date"], format="%d,%m,%Y")

    executor = Parallel(n_jobs=cpu_count(), backend='multiprocessing')
    tasks = (
        delayed(get_bulk_data)(row)
        for _, row in df.iterrows()
    )
    list_of_locations_data = executor(tasks)
    data_full = pd.concat(list_of_locations_data)
    print(data_full)

它适用于以下 csv 和日期格式，如果您的代码略有不同，您可以调整代码：

Date;lat;lon
18,02,1997;50.3;-4.7
12,07,1998;41.3;1.5