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使用下面的 df,我正在尝试使用 dateutil.relativedelta.relativedelta 确定新日期,但想通过 df['freq'] 和 df['time_int'] 作为 **kwargs 和 *args 进行迭代

In [1]: df
Out[1]: 
        date  time_int    freq
0 2021-11-16        -5    days
1 2021-11-16        -1   weeks
2 2021-11-16        -2   weeks
3 2021-11-16        -3   weeks
4 2021-11-16        -3   weeks
5 2021-11-16        -1  months
6 2021-11-16        -1  months

下面,我尝试创建一个 dict 来传递 **kwargs,但 dict 只包含每个键的最后一个值。我需要它遍历所有键、值组合。

time_dict  = dict(zip(df.freq,df.time_int))
df['new_date'] = df['date'].dt.date + relativedelta(**time_dict)

所需的输出:

test
Out[170]: 
        date  time_int    freq new_date
0 2021-11-16        -5    days 2021-11-11
1 2021-11-16        -1   weeks 2021-11-09
2 2021-11-16        -2   weeks 2021-11-02
3 2021-11-16        -3   weeks 2021-10-26
4 2021-11-16        -3   weeks 2021-10-26
5 2021-11-16        -1  months 2021-10-16
6 2021-11-16        -1  months 2021-10-16
4

1 回答 1

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pandas已经包含relativedelta-like 对象,pandas.DateOffset

您可以使用Series.apply

def compute_new_date(row):
    return row['date'] + pd.DateOffset(**{row['freq']: row['time_int']})

# apply compute_new_date row-wise
df['new_date'] = df.apply(compute_new_date, axis=1)

输出:

>>> df

        date  time_int    freq   new_date
0 2021-11-16        -5    days 2021-11-11
1 2021-11-16        -1   weeks 2021-11-09
2 2021-11-16        -2   weeks 2021-11-02
3 2021-11-16        -3   weeks 2021-10-26
4 2021-11-16        -3   weeks 2021-10-26
5 2021-11-16        -1  months 2021-10-16
6 2021-11-16        -1  months 2021-10-16
于 2021-11-18T22:34:53.143 回答