python - pandas 对列值进行排序

Question

即)

        count
2015-01  2
2015-02  1
2015-03  4

对于我尝试过的组 pd.groupby(b,by=[b.index.month,b.index.year])

但存在对象没有属性“月份”错误

Answer 1

应用sorted，并将key参数设置为pd.to_datetime

df.assign(date=df.date.apply(sorted, key=pd.to_datetime))

  id                                  date
0  a              [2015-02-01, 2015-03-01]
1  b                          [2015-03-01]
2  s              [2015-01-01, 2015-03-01]
3  f  [2015-01-01, 2015-01-01, 2015-03-01]

然后使用pd.value_counts

pd.value_counts(pd.to_datetime(df.date.sum()).strftime('%Y-%m'))

2015-03    4
2015-01    3
2015-02    1
dtype: int64

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调试

您应该能够复制并粘贴此代码...请验证它是否按预期运行。

import pandas as pd

df = pd.DataFrame(dict(
        id=list('absf'),
        date=[
            ['2015-03-01', '2015-02-01'],
            ['2015-03-01'],
            ['2015-01-01', '2015-03-01'],
            ['2015-01-01', '2015-01-01', '2015-03-01']
        ]
    ))[['id', 'date']]

print(df.assign(date=df.date.apply(sorted, key=pd.to_datetime)))
print()
print(pd.value_counts(pd.to_datetime(df.date.sum()).strftime('%Y-%m')))

你应该期待看到

  id                                  date
0  a              [2015-02-01, 2015-03-01]
1  b                          [2015-03-01]
2  s              [2015-01-01, 2015-03-01]
3  f  [2015-01-01, 2015-01-01, 2015-03-01]

2015-03    4
2015-01    3
2015-02    1
dtype: int64