pandas DataFrame从列中提取坐标信息并在列表中形成经纬度对列表

Question

我有一个带有 text/tuple 列的 pandas 数据框，如所附屏幕截图所示。

下面也是列中数据的示例：

Colum title - POLYGON_WKT_TEXT
POLYGON ( (-105.01884585094353 39.62333777125623, 
        -105.01851820478282 39.62333686626711,
        -105.0185192106112 39.62315273546345,
        -105.01888004910847 39.6231533822067,
        -105.01888071966073 39.62322879067289,
        -105.01884585094353 39.62322827417681,
        -105.01884585094353 39.62333777125623) )
POLYGON ((-106.83036867299995 39.19331872400005, 
        -106.83027684299998 39.19329631000005,
        -106.83034537399999 39.19313263400005,
        -106.83060769199994 39.19318738000004, 
        -106.83056232299998 39.19329573700003, 
        -106.83052058199996 39.19328554900005, 
        -106.83048588899999 39.19336841100005, 
        -106.83036066599999 39.19333784600008, 
        -106.83036867299995 39.19331872400005))
        
        ...
        ...

我希望此字段采用以下格式：

column name - POLYGON_WKT_TXT
[(-105.01884585094353 39.62333777125623), (-105.01851820478282 39.62333686626711), ...(-106.83036867299995 39.19331872400005)]

到目前为止，我已经尝试将逗号 (",") 分成多列，但问题是列中值的长度变化最终导致我的解决方案效率不高。

预先感谢您以优雅的方式解决此任务。

Answer 1

如果我理解你的问题，这很简单
根据问题中提供的 WKT 文本创建数据框
由此创建列表元组。这就像使用 https://shapely.readthedocs.io/en/stable/manual.html#shapely.wkt.loads 和 exterior.coords
已提供图像输出，因为它的格式不如 markdown

import shapely.wkt
import pandas as pd

df = pd.DataFrame({"polygon_wkt_txt":["""POLYGON ( (-105.01884585094353 39.62333777125623, 
        -105.01851820478282 39.62333686626711,
        -105.0185192106112 39.62315273546345,
        -105.01888004910847 39.6231533822067,
        -105.01888071966073 39.62322879067289,
        -105.01884585094353 39.62322827417681,
        -105.01884585094353 39.62333777125623) )""",
"""POLYGON ((-106.83036867299995 39.19331872400005, 
        -106.83027684299998 39.19329631000005,
        -106.83034537399999 39.19313263400005,
        -106.83060769199994 39.19318738000004, 
        -106.83056232299998 39.19329573700003, 
        -106.83052058199996 39.19328554900005, 
        -106.83048588899999 39.19336841100005, 
        -106.83036066599999 39.19333784600008, 
        -106.83036867299995 39.19331872400005))"""]})

df["tuple_list"] = df["polygon_wkt_txt"].apply(lambda txt: list(shapely.wkt.loads(txt).exterior.coords))

df

pandas DataFrame从列中提取坐标信息并在列表中形成经纬度对列表

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