Question

我有以下数据框

import pandas as pd

compnaies = ['Microsoft', 'Google', 'Amazon', 'Microsoft', 'Facebook', 'Google','Google']
products = ['OS', 'Search', 'E-comm', 'X-box', 'Social Media', 'Android','Search']

df = pd.DataFrame({'company' : compnaies, 'product':products })

我执行以下操作：

 df.groupby('company').product.agg([('count', 'count'), ('product', ', '.join)])



        count   product
company     
Amazon      1   E-comm
Facebook    1   Social Media
Google      3   Search, Android, Search
Microsoft   2   OS, X-box

如何在上述代码之后而不是数量和产品上命名列：

预期输出：

company     Number   Product List.
Amazon      1        E-comm
Facebook    1        Social Media
Google      3        Search, Android, Search
Microsoft   2        OS, X-box

预期的输出2：

预期输出：

 company        Number   Product List.            uniquecount uniquevalues
    Amazon      1        E-comm                       1         E-comm
    Facebook    1        Social Media                 2         Social Media
    Google      3        Search, Android, Search      2         Search, Android,
    Microsoft   2        OS, X-box, Search            3         OS, X-box,Search

Answer 1

import pandas as pd


def remove_dup(string):
    temp=string.split(',')
    temp=[x.strip() for x in temp]
    return ','.join(set(temp))

compnaies = ['Microsoft', 'Google', 'Amazon', 'Microsoft', 'Facebook', 'Google','Google']
products = ['OS', 'Search', 'E-comm', 'X-box', 'Social Media', 'Android','Search']

df = pd.DataFrame({'company' : compnaies, 'product':products })

new_df=df.groupby('company').product.agg([('Number', 'count'), ('Product list', ', '.join)]).reset_index()

#create uniquevalues
new_df['uniquevalues']=new_df['Product list'].apply(remove_dup)

#create uniquecount
new_df['uniquecount']=new_df['uniquevalues'].str.split(',').str.len()

Answer 2

这是标准答案：

df.groupby('company').product.agg([('count', 'count'), ('product', ', '.join)]).rename(columns={"count":"number","product":"product lists"})

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