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Dato Dato
Asked:2024-12-03 13:06:01 +0000 UTC2024-12-03 13:06:01 +0000 UTC

如何解决 TypeError:无法将系列转换为 <class 'float'> 的问题？

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有这样一个数据框：

       newbs longitudeY1 latitudeX1   oldbs       longitudeY2        latitudeX2     BSC   LAC
0     IR021  105.98790  52.78068  IR0505   104.2578286633  52.655474988944  396402  5244
1     IR021  105.98790  52.78068  IR1017  104.59863944009  52.384744395507  396402  5244
2     IR021  105.98790  52.78068  IR1020  104.14058703968  52.010800749578  396402  5307
3     IR021  105.98790  52.78068  IR1023  104.15358510877  52.719410098781  396402  5319
4     IR021  105.98790  52.78068  IR1030  104.20639053885  52.573995078092  396402  5244
...      ...         ...        ...     ...               ...               ...     ...   ...
4192  IR066  105.68000  54.34308  IR2964  103.24349640892  52.974271985462  401257  5272
4193  IR066  105.68000  54.34308  IR2965  105.67618886914  54.995100603944  401257  5251
4194  IR066  105.68000  54.34308  IR2969  103.47831487935  52.720066254791  401257  5259
4195  IR066  105.68000  54.34308  IR2970  103.72418234894   52.09637656718  401257  5272
4196  IR066  105.68000  54.34308  IR2981  103.85440774559  52.517154218339  401257  5272

如何在此表中应用公式 sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2)) ？在我的代码中它抱怨错误：

Traceback (most recent call last):
  File "P:\projects\FillingInDataForTheSite\py.py", line 308, in <module>
    newNeighbourTable["distance"] = math.sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2))        
  File "C:\Users\david\AppData\Roaming\Python\Python310\site-packages\pandas\core\series.py", line 248, in wrapper
    raise TypeError(f"cannot convert the series to {converter}")
TypeError: cannot convert the series to <class 'float'>

这是我的代码，在评论中这些是我解决问题的尝试：

        newNeighbourTable = newdatatable.merge(olddatatable, how='cross')        
        print(" - Добавляю общую таблицу.")
        x1=newNeighbourTable["latitudeX1"].astype(float)
        x2=newNeighbourTable["latitudeX2"].astype(float)
        y1=newNeighbourTable["longitudeY1"].astype(float)
        y2=newNeighbourTable["longitudeY2"].astype(float)
        #newNeighbourTable["distance"] = ""
        newNeighbourTable["distance"] = math.sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2))        
        #for i, row in newNeighbourTable.iterrows():
        #    print(ewNeighbourTable.loc[i])
            #df_index = newNeighbourTable.loc[i]
            #results = math.sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2))
            #newNeighbourTable["distance"] = results
        print(newNeighbourTable)
        print(newNeighbourTable.dtypes)
python

1 个回答

  1. Best Answer
    newNeighbourTable["distance"] = math.sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2)) 
                                ^^^^^^^^^

    math适用于单个数字。你有 形式的数据Pandas.Series，里面有Numpy.array，所以Numpy它可以使用它：

    newNeighbourTable["distance"] = np.sqrt((x1-x2) * (x1-x2) + (y1-y2) * (y1-y2)) 
                                ^^^^^^^

    通常你不应该写循环；如果你写了iterrows，那么你就做错了。Pandas或中有现成的函数Numpy，或者您可以编写自己的函数并将其应用map到apply该系列中。

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