Random selection of columns from a data frame
My question is pretty simple: Is there a way to randomly select columns from a dataframe in Pandas? To be clear, I want to randomly select n columns with attached values. I know there is a method like this to randomly select rows:
import pandas as pd df = pd.read_csv(filename, sep=',', nrows=None) a = df.sample(n = 2)
So the question is, is there an equivalent method for finding random columns?
source to share
sample
also takes an axis parameter:
df = pd.DataFrame(np.random.randint(1, 10, (10, 5)), columns=list('abcde'))
df
Out:
a b c d e
0 4 5 9 8 3
1 7 2 2 8 7
2 1 5 7 9 2
3 3 3 5 2 4
4 8 4 9 8 6
5 6 5 7 3 4
6 6 3 6 4 4
7 9 4 7 7 3
8 4 4 8 7 6
9 5 6 7 6 9
df.sample(2, axis=1)
Out:
a d
0 4 8
1 7 8
2 1 9
3 3 2
4 8 8
5 6 3
6 6 4
7 9 7
8 4 7
9 5 6
source to share
You can just do df.columns.to_series.sample(n=2)
to randomly select columns, you first need to convert to Series
by calling to_series
, after which you can call sample
as before
In[24]:
df.columns.to_series().sample(2)
Out[24]:
C C
A A
dtype: object
Example:
In[30]:
df = pd.DataFrame(np.random.randn(5,3), columns=list('abc'))
df
Out[30]:
a b c
0 -0.691534 0.889799 1.137438
1 -0.949422 0.799294 1.360521
2 0.974746 -1.231078 0.812712
3 1.043434 0.982587 0.352927
4 0.462011 -0.591438 -0.214508
In[31]:
df[df.columns.to_series().sample(2)]
Out[31]:
b a
0 0.889799 -0.691534
1 0.799294 -0.949422
2 -1.231078 0.974746
3 0.982587 1.043434
4 -0.591438 0.462011
source to share