Find the Correlation | Extract Data

# Find the Correlation

Finally, let's move to the last function of this section called `.corr()`. It helps out a lot to find the relationship between numerical data. Imagine that you have a dataset on houses:

Price USD Number of Rooms Distance from the City Center in km
329000 4 25
8739000 6 3
1268000 6 2
987000 4 10
103000 2 30

Let's examine the output of the `data.corr()` in our case:

Price USD Number of Rooms Distance from the City Center in km
Price USD 1.000000 0.625651 -0.589396
Number of Rooms 0.625651 1.000000 -0.908600
Distance from the City Center in km -0.589396 -0.908600 1.000000

So, let's do it step by step: You have vertical and horizontal values; each pair overlaps. In each overlap, we can receive a value from -1 to 1.

• 1 means that two values depend on each other in a directly proportional way (if one value increases, the other increases too);
• -1 means that two values depend on each other in an inversely proportional way (if one value increases, the other decreases);
• 0 means that the two dependent values aren't proportional.

Завдання

You'll end this section with an effortless task: apply the `.corr()` function to the dataset. Then, try to analyze the numbers you get.

Все було зрозуміло?

Секція 3. Розділ 7

Зміст курсу

# Find the Correlation

Finally, let's move to the last function of this section called `.corr()`. It helps out a lot to find the relationship between numerical data. Imagine that you have a dataset on houses:

Price USD Number of Rooms Distance from the City Center in km
329000 4 25
8739000 6 3
1268000 6 2
987000 4 10
103000 2 30

Let's examine the output of the `data.corr()` in our case:

Price USD Number of Rooms Distance from the City Center in km
Price USD 1.000000 0.625651 -0.589396
Number of Rooms 0.625651 1.000000 -0.908600
Distance from the City Center in km -0.589396 -0.908600 1.000000

So, let's do it step by step: You have vertical and horizontal values; each pair overlaps. In each overlap, we can receive a value from -1 to 1.

• 1 means that two values depend on each other in a directly proportional way (if one value increases, the other increases too);
• -1 means that two values depend on each other in an inversely proportional way (if one value increases, the other decreases);
• 0 means that the two dependent values aren't proportional.

Завдання

You'll end this section with an effortless task: apply the `.corr()` function to the dataset. Then, try to analyze the numbers you get.

Все було зрозуміло?

Секція 3. Розділ 7