DS - Plotting Linear Functions:

Let us use this Sports - Watch - Data - Set



Now that you have seen the Data,
let us Plot the Existing Data in Python
you can first plot the values of:
Average_Pulse against Calorie_Burnage
using the matplotlib library.
you can use the plot() function to make
a 2D hexagonal binning plot of points x,y:

Example:
import matplotlib.pyplot as plt
health_data.plot
(x ='Average_Pulse', y='Calorie_Burnage', kind='line'),
plt.ylim(ymin=0)
plt.xlim(xmin=0)
plt.show()

Result:


Now, we can Explain the Example:
-Import the pyplot module of the matplotlib library.
-Plot the data from Average_Pulse against Calorie_Burnage
-kind='line' tells us which type of plot we want.
here, we want to have a straight line.
-plt.ylim() and plt.xlim() tells us-
what value we want the axis to start on.
here, we want the axis to begin from zero
-plt.show() shows us the output

the programm Code above will output this Result


here we can see that-
there is a relationship between:
Average_Pulse and Calorie_Burnage.
as Calorie_Burnage increases proportionally, Average_Pulse also increases.
meaning that we can use Average_Pulse to predict Calorie_Burnage.

yes you are right when you ask the question:
Why is The Line Not Fully Drawn Down to The y-axis?

This is because we do not have observations
where Average_Pulse or Calorie_Burnage are equal to zero.
80 is the first observation of Average_Pulse and 240 is the first
observation of Calorie_Burnage.



Pls. take a look at the line,
What happens to calorie burnage if average pulse increases from 80 to 90?


now you can use the diagonal line to
find the mathematical function to predict calorie burnage.

This it what it turns out be:

-If the average pulse is 80, the calorie burnage is 240.
-If the average pulse is 90, the calorie burnage is 260.
-If the average pulse is 100, the calorie burnage is 280.

At last as you can see, There is a pattern.
this means that if average pulse increases by 10,
the calorie burnage increases by 20.

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