“ [Index(['latitude','longitude'],dtype ='object')]都不在[index]中”

时间:2019-09-30 08:50:59

标签: python-3.x pandas

我有一个带有地理位置的pandas数据框,我试图创建一个列并将其传递给该列,该函数将为每个位置获取走分。

这是我的数据框:

df_test[['latitude', 'longitude']]

    latitude    longitude
0   50.673170   -120.322639
1   50.669597   -120.341833
2   50.650727   -120.150661
3   50.687545   -120.297688
4   50.772361   -122.811211
5   50.882304   -119.865000
6   50.643431   -120.362385
7   50.707459   -120.376297
8   50.708614   -120.409419
9   50.697850   -120.389101
10  50.659250   -119.998597

当我在单个变量上测试函数时,一切正常:

walkscore(df_test['latitude'][0], df_test['longitude'][0], key)

71

但是当我尝试通过以下方式将此函数传递给整个数据集时,出现了一个错误:

df_test.loc['walkscore'] = df_test.loc[['latitude', 'longitude']].\
    apply(lambda x:
                    walkscore(x['latitude'], x['longitude'], apikey), axis='columns')

KeyError: "None of [Index(['latitude', 'longitude'], dtype='object')] are in the [index]"

我尝试重置索引,但没有帮助。我在这里做错什么了吗?

1 个答案:

答案 0 :(得分:1)

删除loc,因为需要显示列,而不是索引值:

df_test['walkscore'] = df_test.\
    apply(lambda x: walkscore(x['latitude'], x['longitude'], apikey), axis='columns')

使用示例功能验证:

apikey = 'aaa'
def walkscore(x, y, apikey):
    return tuple((x, y))

df_test['walkscore'] = df_test.\
    apply(lambda x: walkscore(x['latitude'], x['longitude'], apikey), axis='columns')

print (df_test)
     latitude   longitude                                  walkscore
0   50.673170 -120.322639                    (50.67317, -120.322639)
1   50.669597 -120.341833  (50.669596999999996, -120.34183300000001)
2   50.650727 -120.150661           (50.650727, -120.15066100000001)
3   50.687545 -120.297688                   (50.687545, -120.297688)
4   50.772361 -122.811211           (50.772361, -122.81121100000001)
5   50.882304 -119.865000                      (50.882304, -119.865)
6   50.643431 -120.362385                   (50.643431, -120.362385)
7   50.707459 -120.376297                   (50.707459, -120.376297)
8   50.708614 -120.409419          (50.708614000000004, -120.409419)
9   50.697850 -120.389101                    (50.69785, -120.389101)
10  50.659250 -119.998597                    (50.65925, -119.998597)