Pandas groupby多条件及日期差计算

Question

我无法理解要使用的方法。我有以下数据框：

df = {'CODE': ['BBLGLC70M','BBLGLC70M','ZZTNRD77', 'ZZTNRD77', 'AACCBD', 'AACCBD', 'BCCDN', 'BCCDN', 'BCCDN'],
      'DATE': ['16/05/2019','25/09/2019', '16/03/2020', '27/02/2020', '16/07/2020', '21/07/2020', '13/02/2020', '23/07/2020', '27/02/2020'],
      'TYPE': ['PRI', 'PRI', 'PRI', 'PRI', 'PUB', 'PUB', 'PUB', 'PRI', 'PUB'],
      'DESC' : ['KO', 'OK', 'KO', 'KO', 'KO', 'OK', 'KO', 'OK', 'OK']
       }

df = pd.DataFrame(df)
df['DATE'] = pd.to_datetime(df['DATE'], format = '%d/%m/%Y')
df

我需要：

groupby相同'CODE',
检查 'DESC' 是否不一样
检查 'TYPE' 是否相同
计算满足前两个命令的日期之间的月差

预期输出如下：

Answer 1

以下代码使用 .drop_duplicates() and .duplicated() 保留或丢弃数据框中具有重复值的行。

你如何计算一个月的差异？一个月可以是 28、30 或 31 天。您可以将最终结果除以 30，得到月数差异的指示。所以我暂时保留了几天。

import pandas as pd

df = {'CODE': ['BBLGLC70M','BBLGLC70M','ZZTNRD77', 'ZZTNRD77', 'AACCBD', 'AACCBD', 'BCCDN', 'BCCDN', 'BCCDN'],
      'DATE': ['16/05/2019','25/09/2019', '16/03/2020', '27/02/2020', '16/07/2020', '21/07/2020', '13/02/2020', '23/07/2020', '27/02/2020'],
      'TYPE': ['PRI', 'PRI', 'PRI', 'PRI', 'PUB', 'PUB', 'PUB', 'PRI', 'PUB'],
      'DESC' : ['KO', 'OK', 'KO', 'KO', 'KO', 'OK', 'KO', 'OK', 'OK']
       }

df = pd.DataFrame(df)
df['DATE'] = pd.to_datetime(df['DATE'], format = '%d/%m/%Y')

# only keep rows that have the same code and type 
df = df[df.duplicated(subset=['CODE', 'TYPE'], keep=False)]

# throw out rows that have the same code and desc
df = df.drop_duplicates(subset=['CODE', 'DESC'], keep=False)

# find previous date
df = df.sort_values(by=['CODE', 'DATE'])
df['previous_date'] = df.groupby('CODE')['DATE'].transform('shift')

# drop rows that don't have a previous date
df = df.dropna()

# calculate the difference between current date and previous date
df['difference_in_dates'] = (df['DATE'] - df['previous_date'])

这导致以下 df:

CODE        DATE        TYPE    DESC    previous_date   difference_in_dates
AACCBD      2020-07-21  PUB     OK      2020-07-16      5 days
BBLGLC70M   2019-09-25  PRI     OK      2019-05-16      132 days
BCCDN       2020-02-27  PUB     OK      2020-02-13      14 days

Pandas groupby多条件及日期差计算

Pandas groupby multi conditions and date difference calculation

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