在Pandas DataFrames中尋找最近點

Question

我對Python很陌生。我在Postgres有下列表格。這些是四個座標聯動相同Id與ZONE名字我已存儲的多邊形值這個數據在Python數據幀稱爲df1

Id Order Lat    Lon   Zone 
00001 1 50.6373473 3.075029928   A 
00001 2 50.63740441 3.075068636   A 
00001 3 50.63744285 3.074951754   A 
00001 4 50.63737839 3.074913884   A 
00002 1 50.6376054 3.0750528   B 
00002 2 50.6375896 3.0751209   B 
00002 3 50.6374239 3.0750246   B 
00002 4 50.6374404 3.0749554   B 

我有Lon和Lat值JSON數據，我已經存儲了他們是蟒蛇數據幀稱爲df2。

Lat     Lon 
50.6375524099 3.07507914474 
50.6375714407 3.07508201591 

我的任務是與每個區域的四個座標中df1比較df2Lat和Lon值提取區域名稱，並將其添加到df2。

例如(50.637552409 3.07507914474)屬於Zone B。

#This is ID with Zone 
df1 = pd.read_sql_query("""SELECT * from "zmap" """,con=engine) 
#This is with lat,lon values 
df2 = pd.read_sql_query("""SELECT * from "E1" """,con=engine) 
df2['latlon'] = zip(df2.lat, df2.lon) 
zones = [ 
["A", [[50.637347297, 3.075029928], [50.637404408, 3.075068636], [50.637442847, 3.074951754],[50.637378390, 3.074913884]]]] 
for i in range(0, len(zones)): # for each zone points 
    X = mplPath.Path(np.array(zones[i][1])) 
    # find if points are Zones 
    Y= X.contains_points(df2.latlon.values.tolist()) 
    # Label points that are in the current zone 
    df2[Y, 'zone'] = zones[i][0] 

目前我已爲區域'A'手動完成它。我需要爲df2中的座標生成「區域」。

Answer 1

這聽起來像是一個很好的使用案例scipy cdist，也討論了here。

import pandas as pd 
from scipy.spatial.distance import cdist 


data1 = {'Lat': pd.Series([50.6373473,50.63740441,50.63744285,50.63737839,50.6376054,50.6375896,50.6374239,50.6374404]), 
     'Lon': pd.Series([3.075029928,3.075068636,3.074951754,3.074913884,3.0750528,3.0751209,3.0750246,3.0749554]), 
     'Zone': pd.Series(['A','A','A','A','B','B','B','B'])} 

data2 = {'Lat': pd.Series([50.6375524099,50.6375714407]), 
     'Lon': pd.Series([3.07507914474,3.07508201591])} 


def closest_point(point, points): 
    """ Find closest point from a list of points. """ 
    return points[cdist([point], points).argmin()] 

def match_value(df, col1, x, col2): 
    """ Match value x from col1 row to value in col2. """ 
    return df[df[col1] == x][col2].values[0] 


df1 = pd.DataFrame(data1) 
df2 = pd.DataFrame(data2) 

df1['point'] = [(x, y) for x,y in zip(df1['Lat'], df1['Lon'])] 
df2['point'] = [(x, y) for x,y in zip(df2['Lat'], df2['Lon'])] 

df2['closest'] = [closest_point(x, list(df1['point'])) for x in df2['point']] 
df2['zone'] = [match_value(df1, 'point', x, 'Zone') for x in df2['closest']] 

print(df2) 
# Lat  Lon  point       closest     zone 
# 0 50.637552 3.075079 (50.6375524099, 3.07507914474) (50.6375896, 3.0751209) B 
# 1 50.637571 3.075082 (50.6375714407, 3.07508201591) (50.6375896, 3.0751209) B