如何将linestring转换为地质层中的多个经度纬度列

Question

这是我的一行输入，

Name                    geometry
Jalan W.R. Supratman    LINESTRING (95.317339 5.5603499, 95.3169007 5.5602832, 95.3165735 5.5602391, 95.3161729 5.5602097, 95.3161289 5.5601326, 95.3160873 5.5600178)

这是我的预期输出

Name                                  Langitude         Longitude
Jalan W.R. Supratman                  95.317339         5.5603499
Jalan W.R. Supratman                  95.3169007        5.5602832
Jalan W.R. Supratman                  95.3165735        5.5602391
Jalan W.R. Supratman                  95.3161729        5.5602097
Jalan W.R. Supratman                  95.3161289        5.5601326
Jalan W.R. Supratman                  95.3160873        5.5600178

编辑：

这是我尝试

def utm_to_latlon(coords, zone_number, zone_letter):
    easting = coords[0]
    northing = coords[1]
    return utm.to_latlon(easting, northing, zone_number, zone_letter)

# Using nested list comprehension
df ["lat_lon_tuple"] = [[utm_to_latlon(xy, 44, "N") for xy in tuple(geom.coords)] for geom in df.geometry]

错误消息的内容

<ipython-input-5-4dfd2badb8b4> in <listcomp>(.0)
      5 
      6 # Using nested list comprehension
----> 7 df ["lat_lon_tuple"] = [[utm_to_latlon(xy, 44, "N") for xy in tuple(geom.coords)] for geom in df.geometry]

AttributeError: 'str' object has no attribute 'coords'

Answer 1

用索引爆炸，然后应用系列：

import pandas as pd
import geopandas as gpd
from shapely.geometry import LineString

df = gpd.GeoDataFrame(
    {'Name': ['Jalan W.R. Supratman', 'Other Street'],
     'geometry': [LineString([(95.317339, 5.5603499), (95.3169007,5.5602832), (95.3165735, 5.5602391), (95.3161729,5.5602097), (95.3161289, 5.5601326), (95.3160873, 5.5600178)]),
                  LineString([(95.0, 6.0), (95.01, 6.01)])]})

print(df.set_index('Name').geometry
        .apply(lambda x: list(x.coords))
        .explode(ignore_index=False)
        .apply(pd.Series)
        .reset_index()
        .rename(columns={0: 'Langitude', 1: 'Longitude'}))

结果：

                   Name  Langitude  Longitude
0  Jalan W.R. Supratman  95.317339   5.560350
1  Jalan W.R. Supratman  95.316901   5.560283
2  Jalan W.R. Supratman  95.316574   5.560239
3  Jalan W.R. Supratman  95.316173   5.560210
4  Jalan W.R. Supratman  95.316129   5.560133
5  Jalan W.R. Supratman  95.316087   5.560018
6          Other Street  95.000000   6.000000
7          Other Street  95.010000   6.010000

Answer 2

您可以转换定义使用coords属性，然后将其转换为 shapely.deometry.multipoint ：

df['geometry'] = df['geometry'].apply(
    lambda x: shapely.geometry.MultiPoint(list(x.coords))
)

完成此操作后，您可以使用 df.explode ：：

In [10]: df.explode(index_parts=False)
Out[10]:
                   geometry
0  POINT (95.31734 5.56035)
0  POINT (95.31690 5.56028)
0  POINT (95.31657 5.56024)
0  POINT (95.31617 5.56021)
0  POINT (95.31613 5.56013)
0  POINT (95.31609 5.56002)