Printing column/variable names after feature selection

user_2998077 0
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I am trying feature selection on the Iris dateset.

I'm referencing from Feature Selection with Univariate Statistical Tests

I am using below lines and I want to find out the significant features:

import pandas
from pandas import read_csv
from numpy import set_printoptions
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_classif

dataframe = pandas.read_csv("C:\\dateset\\iris.csv"]))
array = dataframe.values
X = array[:,0:4]
Y = array[:,4]

test = SelectKBest(score_func=f_classif, k=2)
fit = test.fit(X, Y)

set_printoptions(precision=2)
arr = fit.scores_

print (arr)

# [ 119.26   47.36 1179.03  959.32]

To show the indexes of the top 2 by its score, I added:

idx = (-arr).argsort()[:2]
print (idx)

# [2 3]

Further, how can I have the column/variable names (instead of their indexes)?

feature-selection pandas dataframe python
2 Answers

Use indexing, here is possible use columns names, because selected first 4 columns:

#first 4 columns
X = array[:,0:4]

cols = dataframe.columns[idx]

If selection is different for X variable is necessary also filter by position DataFrame:

#e.g. selected 3. to 7. column
X = array[:,2:6]

cols = dataframe.iloc[:, 2:6].columns[idx]
user_29010020 
import pandas
from pandas import read_csv
from numpy import set_printoptions
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_classif

dataframe = pandas.read_csv("iris.csv")
array = dataframe.values
X = array[:,0:4]
Y = array[:,4]

test = SelectKBest(score_func=f_classif, k=2)
fit = test.fit(X, Y)

set_printoptions(precision=2)
arr = fit.scores_

idx = (-arr).argsort()[:2]
print (idx)

print (arr)
#names=[dataframe.columns[j] for j in X]

names = dataframe.columns[idx]
print(names)

Output

[2 3]
[ 119.26   47.36 1179.03  959.32]
Index(['petal_length', 'petal_width'], dtype='object')
user_43916970
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