如果两列中的值相同，则合并熊猫中的单元格

Question

I have the following data in terms of dataframe

data = pd.DataFrame({'colA': ['a', 'c', 'a', 'e', 'c', 'c'], 'colB': ['b', 'd', 'b', 'f', 'd', 'd'], 'colC':['SD100', 'SD200', 'SD300', 'SD400', 'SD500', 'SD600']})

I want the output as attached [enter image description here][2]

I want to achieve this using pandas dataframe in python Can somebody help me?

Answer 1

You can try:

  Column A Column B Column C
0        a        b    SD100
1        c        d    SD200
2        a        b    SD300
3        e        f    SD400
4        c        d    SD500
5        c        d    SD600

---

>>> df.groupby(['Column A', 'Column B']).agg(list)
                                Column C
Column A Column B
a        b                [SD100, SD300]
c        d         [SD200, SD500, SD600]
e        f                       [SD400]

Answer 2

I don't know why you want to make multindex, but you can simply sort_values or use groupby .

import pandas as pd
df = pd.DataFrame({"ColumnA":['a','c','a','e','c','c'],
                 "ColumnB":['b','d','b','f','d','d'],
                 "ColumnC":['SD100','SD200','SD300','SD400','SD500','SD600']})
print(df)

      ColumnA ColumnB ColumnC
    0       a       b   SD100
    1       c       d   SD200
    2       a       b   SD300
    3       e       f   SD400
    4       c       d   SD500
    5       c       d   SD600

df = df.sort_values(by=['ColumnA','ColumnB'])
df.set_index(['ColumnA', 'ColumnB','ColumnC'], inplace=True)
df

Answer 3

这会将您的数据更新为您想要的

data=data.groupby(['colA','colB']).agg(list)