Python Dataframe ValueError：使用iterable设置时，必须具有相等的len键和值

Question

我有一个数据框，如下所示：

       PR         Order     Season  Rj
0   3001913971  3445046069  202112  NaN
1   3002026058  1445132366  202121  NaN
2   3002026059  1445132365  202122  NaN
3   3002026063  1445132367  202211  NaN
4   3002026069  1445132375  202121  NaN

当我第一次运行下面的代码时，它工作得很好

df['Season'] = df['Season'].astype(str)
df.loc[(df['Season'].str[-2:] == '11') & (df['Season'].str.len() == 6),'Season'] = 'Spring ' + df.loc[df['Season'].str[-2:] == '11','Season'].str[:4]
df.loc[(df['Season'].str[-2:] == '12') & (df['Season'].str.len() == 6),'Season'] = 'Summer ' + df.loc[df['Season'].str[-2:] == '12','Season'].str[:4]
df.loc[(df['Season'].str[-2:] == '21') & (df['Season'].str.len() == 6),'Season'] = 'Autumn ' + df.loc[df['Season'].str[-2:] == '21','Season'].str[:4]
df.loc[(df['Season'].str[-2:] == '22') & (df['Season'].str.len() == 6),'Season'] = 'Holiday ' + df.loc[df['Season'].str[-2:] == '22','Season'].str[:4]

第一次运行的结果如下所示

      PR           Order    Season       Rj
0   3001913971  3445046069  Summer 2021  NaN
1   3002026058  1445132366  Autumn 2021  NaN
2   3002026059  1445132365  Holiday 2021 NaN
3   3002026063  1445132367  Spring 2022  NaN
4   3002026069  1445132375  Autumn 2021  NaN

但当我第二次运行它时，它将引发错误

ValueError: Must have equal len keys and value when setting with an iterable

你知道为什么吗？非常感谢

Answer 1

第二次运行代码时，Season字符串的长度不再是6（并且没有一个字符串的11作为最后两个字母），因此代码的第二行应该将字符串'Spring '分配给数据帧的空片段，这当然是不可能的

通常，在提取这样的数据时，最好保留原始列并将派生值作为附加列添加。这避免了上述问题，也有助于捕获错误。冗余可能是一件好事。顺便说一句，您也可以直接从整数值中提取数据，而无需先将它们转换为字符串。地板分割和模运算符是您所需要的全部：

df['Year'] = df.Season // 100
df['Season_cat'] = (df.Season % 100).astype('category').cat.rename_categories(
    {11: 'Spring', 12: 'Summer', 21: 'Autumn', 22: 'Holiday'})

df

    PR          Order       Season  Rj      Year    Season_cat
0   3001913971  3445046069  202112  NaN     2021    Summer
1   3002026058  1445132366  202121  NaN     2021    Autumn
2   3002026059  1445132365  202122  NaN     2021    Holiday
3   3002026063  1445132367  202211  NaN     2022    Spring
4   3002026069  1445132375  202121  NaN     2021    Autumn