find_or_check_categorical_variables#
With find_or_check_categorical_variables()
you can automatically capture in a list
the names of all the variables of type object or categorical 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_or_check_categorical_variables()
to capture the names of all
variables of type object or categorical in a list.
So let’s do that and then display the list:
from feature_engine.variable_handling import find_or_check_categorical_variables
var_cat = find_or_check_categorical_variables(X)
var_cat
We see the variable names in the list below:
['cat_var1', 'cat_var2']
Note that when using the default parameters, find_or_check_categorical_variables()
will not return variables cast as object or categorical that could be parsed as datetime.
Therefore, the variable date3
was excluded from the returned list.
We can force the function to select datetime variables cast as object as follows:
var_cat = find_or_check_categorical_variables(X, ["cat_var1", "date3"])
var_cat
In this case, both variables, if object or categorical, will be in the resulting list:
['cat_var1', 'date3']
If we pass a variable that is not of type object or categorical, find_or_check_categorical_variables()
will return an error:
find_or_check_categorical_variables(X, ["cat_var1", "num_var_1"])
Below we see the error message:
TypeError: Some of the variables are not categorical. Please cast them as categorical
or object before using this transformer.