find_datetime_variables#
With find_datetime_variables()
you can automatically capture in a list
the names of all datetime variables in a dataset, whether they are parsed as datetime
or object.
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
The dataframe has 3 datetime variables, two of them are of type datetime and one of type object.
We can now use find_datetime_variables()
to capture all datetime variables
regardless of their data type. So let’s do that and then display the list:
from feature_engine.variable_handling import find_datetime_variables
var_date = find_datetime_variables(X)
var_date
Below we see the variable names in the list:
['date1', 'date2', 'date3']
Note that find_datetime_variables()
captures all 3 datetime variables.
The first 2 are of type datetime, whereas the third variable is of type object. But as it
can be parsed as datetime, it will be captured in the list as well.