pandas 高级分组依据和按日期过滤 [英] Pandas advanced groupby and filter by date

问题描述

通过输入创建输出数据帧，如何在每个ID首次目标== 1时如何过滤行，或者按顺序删除目标为1的每个ID的连续出现，但是在目标之前将全0保持在目标之前= 1.

Create the output dataframe from input, how to filter for rows when target == 1 for the first time for each id, or in order words removing consecutive occurrence for each ids where target is 1 however keep all 0s in target before target = 1.

输入

ID   date         target
a1   2019-11-01   0
a1   2019-12-01   0
a1   2020-01-01   1
a1   2020-02-01   1
a1   2020-03-01   0
a2   2019-11-01   0
a2   2019-12-01   1
a2   2020-03-01   0
a2   2020-04-01   1

输出

ID   date         target
a1   2019-11-01   0
a1   2019-12-01   0
a1   2020-01-01   1
a2   2019-11-01   0
a2   2019-12-01   1

推荐答案

from io import stringIO

data = StringIO("""
uid,  date,         target
a1,   2019-11-01,   0
a1,   2019-12-01,   0
a1,   2020-01-01,   1
a1,  2020-02-01,   1
a1,   2020-03-01,   0
a2,   2019-11-01,   0
a2,   2019-12-01,   1
a2,   2020-03-01,   0
a2,   2020-04-01,   1
"""
)

df = pd.read_csv(data).rename(columns=lambda x: x.strip())

def filter_in_group(df: pd.DataFrame):
  ind = np.argmax(df.target)
  return df.loc[:, ['date', 'target']].iloc[:ind+1]

df_filtered = (
df
.groupby('uid')
.apply(lambda x: filter_in_group(x))
.reset_index()
.drop('level_1', axis=1)
)

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