[FIXED] How to select columns which contain non-duplicate from a pandas data frame

Issue

I want to select columns which contain non-duplicate from a pandas data frame and use these columns to make up a subset data frame. For example, I have a data frame like this:

   x  y  z
a  1  2  3
b  1  2  2
c  1  2  3
d  4  2  3

The columns "x" and "z" have non-duplicate values, so I want to pick them out and create a new data frame like:

   x  z
a  1  3
b  1  2
c  1  3
d  4  3

The can be realized by the following code:

import pandas as pd
df = pd.DataFrame([[1,2,3],[1,2,2],[1,2,3],[4,2,3]],index=['a','b','c','d'],columns=['x','y','z'])
df0 = pd.DataFrame()
for i in range(df.shape[1]):
    if df.iloc[:,i].nunique() > 1:
        df1 = df.iloc[:,i].T
        df0 = pd.concat([df0,df1],axis=1, sort=False)

However, there must be more simple and direct methods. What are they?

Solution

df[df.columns[(df.nunique()!=1).values]]

Maybe you can try this one-liner.

Answered By - Justice_Lords