find_all_variables#
With find_all_variables()
you can automatically capture in a list the names of
all the variables in the dataset.
Let’s create a toy dataset with numerical, categorical and datetime variables:
import pandas as pd
from sklearn.datasets import make_classification
X, y = make_classification(
n_samples=1000,
n_features=4,
n_redundant=1,
n_clusters_per_class=1,
weights=[0.50],
class_sep=2,
random_state=1,
)
# transform arrays into pandas df and series
colnames = [f"num_var_{i+1}" for i in range(4)]
X = pd.DataFrame(X, columns=colnames)
X["cat_var1"] = ["Hello"] * 1000
X["cat_var2"] = ["Bye"] * 1000
X["date1"] = pd.date_range("2020-02-24", periods=1000, freq="T")
X["date2"] = pd.date_range("2021-09-29", periods=1000, freq="H")
X["date3"] = ["2020-02-24"] * 1000
print(X.head())
We see the resulting dataframe below:
num_var_1 num_var_2 num_var_3 num_var_4 cat_var1 cat_var2 \
0 -1.558594 1.634123 1.556932 2.869318 Hello Bye
1 1.499925 1.651008 1.159977 2.510196 Hello Bye
2 0.277127 -0.263527 0.532159 0.274491 Hello Bye
3 -1.139190 -1.131193 2.296540 1.189781 Hello Bye
4 -0.530061 -2.280109 2.469580 0.365617 Hello Bye
date1 date2 date3
0 2020-02-24 00:00:00 2021-09-29 00:00:00 2020-02-24
1 2020-02-24 00:01:00 2021-09-29 01:00:00 2020-02-24
2 2020-02-24 00:02:00 2021-09-29 02:00:00 2020-02-24
3 2020-02-24 00:03:00 2021-09-29 03:00:00 2020-02-24
4 2020-02-24 00:04:00 2021-09-29 04:00:00 2020-02-24
We can now use find_all_variables()
to capture all the variable names in a list.
So let’s do that and then display the items in the list:
from feature_engine.variable_handling import find_all_variables
vars_all = find_all_variables(X)
vars_all
We see the variable names in the list below:
['num_var_1',
'num_var_2',
'num_var_3',
'num_var_4',
'cat_var1',
'cat_var2',
'date1',
'date2',
'date3']
We have the option to return the name of the variables of type categorical, object and numerical only, or in other words, to exclude datetime variables. We can do so as follows:
vars_all = find_all_variables(X, exclude_datetime=True)
vars_all
In the list below, we can see that variables of type datetime were ignored:
['num_var_1',
'num_var_2',
'num_var_3',
'num_var_4',
'cat_var1',
'cat_var2',
'date3']