相关疑难解决方法(0)

我有一个pandas数据框,如下所示:

In [23]: dataframe.head()
Out[23]: 
column_id   1  10  11  12  13  14  15  16  17  18 ...  46  47  48  49   5  50  \
row_id                                            ...                           
1         NaN NaN   1   1   1   1   1   1   1   1 ...   1   1 NaN   1 NaN NaN   
10          1   1   1   1   1   1   1   1   1 NaN ...   1   1   1 NaN   1 NaN   
100         1   1 NaN   1   1   1   1   1 NaN   1 ... NaN NaN   1   1   1 NaN …

示例CSV如下所示:

 user_id  lat         lon
    1   19.111841   72.910729
    1   19.111342   72.908387
    2   19.111542   72.907387
    2   19.137815   72.914085
    2   19.119677   72.905081
    2   19.129677   72.905081
    3   19.319677   72.905081
    3   19.120217   72.907121
    4   19.420217   72.807121
    4   19.520217   73.307121
    5   19.319677   72.905081
    5   19.419677   72.805081
    5   19.629677   72.705081
    5   19.111860   72.911347
    5   19.111860   72.931346
    5   19.219677   72.605081
    6   19.319677   72.805082
    6   19.419677   72.905086

我知道我可以使用hasrsine进行距离计算(而且python也有hasrsine包):

def haversine(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in …