We can help understand data by building mathematical models, this is key to machine learning.
One of such models is linear regression, in which we fit a line to (x,y) data.
There are many modules for Machine Learning in Python, but scikitlearn is a popular one.
Related course: Complete Machine Learning Course with Python
Linear Regression
You may want to predict continous values. That is a regression problem. Linear Regression is one of the methods to solve that.
All kinds of values are continous: temperature, salary, numbers and many more. Regression is not always linear, as shown in the image below:
But there are many data points on which linear regression can be applied. Like tay fare, where hours driven is directly correlated with the price to pay.
Modules
Install the required modules;

linear regression example
Then we start with a basic plot:

This will create a bunch of random data, which follows a linear path.
In a real life situation, you would use real world data instead of random numbers
We then use the model linear regression from the scikitlearn module.

then we define the linear space and predict the y values using the model.

finally we plot the data, summarizing with this code:
# pythonprogramminglanguage.com 
Then we find the fitting line.