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# How to use the matplotlibs pyplot.scatter() function in Python Onyejiaku Theophilus Chidalu

### Overview

The pyplot.scatter() function in matplotlib is used to create a scatter plot. For further understanding, the pyplot module has a function called scatter(), among many other functions, which helps to create or draw a scatter plot.

A scatter plot is a type of plot that uses a dot to graphically represent two variables for a set of data. The scatter plot is used to show a relationship between two numeric variables. The dots in a scatter plot also represent a pattern from which certain data analysis conclusions can be made.

### Creating a scatter plot

As mentioned earlier, we make use of the pyplot.scatter() function in matplotlib, which creates a scatter plot. The pyplot.scatter() function must contain two (x and y-axis) arrays of the same length.

### Code

import matplotlib.pyplot as plt
import numpy as np

x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
y = np.array([10, 50, 30, 40, 50, 25, 70, 15, 90, 65])

plt.scatter(x, y)
plt.show()

### Output

The output of the code

### Explanation

• Line 1: In the matplotlib we imported the pyplot module, which will help us to create plots.
• Line 2: We imported the numpy module, which helps us create arrays.
• Line 4 and 5: We created the arrays, x and y for both the x-axis and y-axis. They are both of equal length.
• Line 7: Here, we used the pyplot.scatter() method to create a scatter plot of x and y.
• Line 8: Using the pyplot.show() function, we told pyplot to show us the plot.

### Multiple scatter plots

Interestingly, we can create multiple scatter plots on the same figure. This is usually done by data analysts to compare different data variables.

### Code

import matplotlib.pyplot as plt
import numpy as np

# the first scatter plot
x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
y = np.array([10, 50, 30, 40, 50, 25, 70, 15, 90, 65])

plt.scatter(x, y)

# the second scatter plot
x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
y1 = np.array([5, 35, 40, 45, 80, 20, 95, 55, 70, 10])

plt.scatter(x,y1)

plt.show()



### Output

The two colors present in the plot are that of the first and second scatter plots. By default, pyplot returned blue and orange colors.

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python
scatter
communitycreator

CONTRIBUTOR Onyejiaku Theophilus Chidalu
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