Python Pandas 'DataFrame' 对象没有属性 'unique'
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/29244549/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas 'DataFrame' object has no attribute 'unique'
提问by thesebeth
I'm working in pandas doing pivot tables and when doing the groupby (to count distinct observations)
aggfunc={"person":{lambda x: len(x.unique())}}gives me the following error:
'DataFrame' object has no attribute 'unique'any ideas how to fix it?
我正在使用 Pandas 做数据透视表，并且在执行 groupby（计算不同的观察值）时
aggfunc={"person":{lambda x: len(x.unique())}}出现以下错误：
'DataFrame' object has no attribute 'unique'任何想法如何解决它？
回答by Alexander
DataFrames do not have that method; columns in DataFrames do:
DataFrames 没有那个方法；DataFrame 中的列执行以下操作：
df['A'].unique()
Or, to get the names with the number of observations (using the DataFrame given by closedloop):
或者，获取具有观察次数的名称（使用闭环给出的数据帧）：
>>> df.groupby('person').person.count()
Out[80]:
person
0 2
1 3
Name: person, dtype: int64
回答by closedloop
Rather than removing duplicates during the pivot table process, use the df.drop_duplicates()function to selectively drop duplicates.
与其在数据透视表过程中删除重复项，不如使用该df.drop_duplicates()函数有选择地删除重复项。
For example if you are pivoting using these index='c0'and columns='c1'then this simple step yields the correct counts.
例如，如果您使用这些进行旋转index='c0'，columns='c1'那么这个简单的步骤会产生正确的计数。
In this example the 5th row is a duplicate of the 4th (ignoring the non-pivoted c2column
在此示例中，第 5 行是第 4 行的副本（忽略非透视c2列
import pandas as pd
data = {'c0':[0,1,0,1,1], 'c1':[0,0,1,1,1], 'person':[0,0,1,1,1], 'c_other':[1,2,3,4,5]}
df = pd.DataFrame(data)
df2 = df.drop_duplicates(subset=['c0','c1','person'])
pd.pivot_table(df2, index='c0',columns='c1',values='person', aggfunc='count')
This correctly outputs
这正确输出
c1 0 1
c0
0 1 1
1 1 1
