.. _find_cat_vars: .. currentmodule:: feature_engine.variable_handling find_categorical_variables ========================== With :class:`find_categorical_variables()` you can 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: .. code:: python 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: .. code:: python 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 use :class:`find_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: .. code:: python from feature_engine.variable_handling import find_categorical_variables var_cat = find_categorical_variables(X) var_cat We see the variable names in the list below: .. code:: python ['cat_var1', 'cat_var2'] Note that :class:`find_categorical_variables()` will not return variables cast as object or categorical that could be parsed as datetime. That's why, the variable `date3` was excluded from the returned list. If there are no categorical variables in the dataset, this function will raise an error.