【问题标题】:Pandas dataframe group by order [duplicate]Pandas数据框按顺序分组[重复]
【发布时间】:2019-03-20 01:40:15
【问题描述】:

我有输入数据框:

df1 = pandas.DataFrame( { 
    "Name" : ["Alice", "Bob", "Mallory", "Mallory","Mallory", "Bob" ,"Bob", "Mallory", "Alice"] , 
    "City" : ["Seattle", "Seattle", "Portland", "Seattle", "Seattle", "Portland", "Portland", "Seattle", "Seattle"] } )

我想按名称分组,但不是唯一的,所以输出应该是:

["Alice","Bob","Mallory","Bob","Mallory", "Alice"]

我找不到任何有效的方法 - 有没有不迭代所有行的方法?

【问题讨论】:

  • df1.groupby(df1.Name.ne(df1.Name.shift()).cumsum()).Name.first()

标签: python pandas dataframe pandas-groupby data-science


【解决方案1】:

您可以执行以下操作:

df1.groupby((df1['Name'] != df1['Name'].shift()).cumsum()).first()

产量:

         Name      City
Name                   
1       Alice   Seattle
2         Bob   Seattle
3     Mallory  Portland
4         Bob  Portland
5     Mallory   Seattle
6       Alice   Seattle

如果您只想要'Name' 列:

df1.groupby((df1['Name'] != df1['Name'].shift()).cumsum())['Name'].first().values

产量:

['Alice' 'Bob' 'Mallory' 'Bob' 'Mallory' 'Alice']

【讨论】:

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