Pandas 'DataFrame' object has no attribute 'unique'
Solution 1
DataFrames do not have that method; columns in DataFrames do:
df['A'].unique()
Or, to get the names with the number of observations (using the DataFrame given by closedloop):
>>> df.groupby('person').person.count()
Out[80]:
person
0 2
1 3
Name: person, dtype: int64
Solution 2
Rather than removing duplicates during the pivot table process, use the df.drop_duplicates()
function to selectively drop duplicates.
For example if you are pivoting using these index='c0'
and columns='c1'
then this simple step yields the correct counts.
In this example the 5th row is a duplicate of the 4th (ignoring the non-pivoted c2
column
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
c1 0 1
c0
0 1 1
1 1 1
Solution 3
One very easy solution to get the unique combinations of >1 columns from a DF is the following:
unique_A_B_combos = df[['A', 'B']].value_counts().index.values
Solution 4
df[['col1', 'col2']].nunique()
Try this instead of separate function
jwzinserl
Updated on October 04, 2021Comments
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jwzinserl over 2 years
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? -
Eliethesaiyan over 7 yearswhat about df.describe,info? fillna?
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Duck Ling about 2 yearsjust a note: this returns a numpy array as opposed to a dataframe.