[FIXED] Matplotlib.pyplot scatter-plot with numpy input different values makes separate points for each value

Issue

Normally the x and y input values are merged into a coordinate point. Using list, it's ok:

import matplotlib.pyplot as plt
import numpy as np
a = [5,6]
plt.scatter(a[0],a[1])
plt.show() # shows one point at 5,6. OK

Using numpy with same values in x and y:

b=np.array([[4],[4]])
plt.scatter(b[:,0],b[:,0])
plt.show() # shows one point at 4,4. OK

But using numpy with different values in x and y:

c=np.array([[5],[6]])
plt.scatter(c[:,0],c[:,0])
plt.show() # shows points at 5,5 and 6,6. Problem

Solution

With the column vector for c, calling c[:,0] gives:

print(c[:,0])  # array([5, 6])

When creating a scatterplot, the first argument gives the x-values and the second gives the y-values. So, you are setting the x-values to be [5, 6] and your y-values to be [5, 6]. The points are plotted matching one-to-one. Therefore, the first values of x and y are [5, 5] and the second values are [6, 6], hence the plot results.

To get a single point at (5, 6), you do what you did with a, namely,

plt.scatter(c[0], c[1])

Answered By - jared