In linear regression, including logistic regression, it is straightforward to fit a regression model when the feature variables are continuous, as it just needs to find a linear combination of feature variables with numerical values for estimating the output variables. In order to fit a regression model with continuous variables, let's first take a look at how to get the data types of the columns in a pandas DataFrame. Take a look at the following:
As you can see from this Jupyter Notebook screenshot, the dtype attribute of a pandas Series object tells you what type of data it contains. As you can see from this snapshot, ...
