Matplotlib scatter plot with array of y values for each x

Question

This is in the similar vein as Python Scatter Plot with Multiple Y values for each X ; that is, I have data which is:

data = [
  [1, [15, 16, 17, 18, 19, 20]],
  [2, [21, 22, 23, 24, 25, 26]],
  [3, [27, 28, 29, 30, 31, 32]],
]

... so first column (0) is x-coordinates, and second column (1) contains arrays of y values corresponding to the single x coordinate. And, I want to plot this as a scatter plot, and the best I could do is this (code below):

Same as in the linked post, I've had to use three ax.scatter plots, and hence we have three colours, one for each column.

So my question is:

Can I issue a single ax.scatter command to get a plot like the above (but with single color/marker) from the data I have (instead of having to issue three commands)?
Alternatively, can I somehow transform the data I have, so I to get a plot like the above (but with single color/marker) with a single ax.scatter command?

Here is the code:

#!/usr/bin/env python3

import sys
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
print("versions: Python {} matplotlib {} numpy {}".format(sys.version.replace('\n', ''), matplotlib.__version__, np.version.version))


data = [
  [1, [15, 16, 17, 18, 19, 20]],
  [2, [21, 22, 23, 24, 25, 26]],
  [3, [27, 28, 29, 30, 31, 32]],
]

ndata = np.asarray(data, dtype=object)

fig = plt.figure()

# Null formatter
ax = fig.add_subplot(1, 1, 1)

print()
print(ndata[1])
print(ndata[:,0].astype(float))
print(ndata[:,1])

datay_2D = np.stack(ndata[:,1], axis=0) # convert numpy array of lists to numpy 2D array
print()
print(datay_2D[:,0])
print(datay_2D[0])
print([ndata[:,0][0]]*len(datay_2D[0]))

ax.scatter([ndata[:,0][0]]*len(datay_2D[0]), datay_2D[0], marker="x")
ax.scatter([ndata[:,0][1]]*len(datay_2D[1]), datay_2D[1], marker="x")
ax.scatter([ndata[:,0][2]]*len(datay_2D[1]), datay_2D[2], marker="x")

plt.show()

Printout:

versions: Python 3.6.8 (default, Oct  7 2019, 12:59:55) [GCC 8.3.0] matplotlib 2.1.1 numpy 1.13.3

[2 list([21, 22, 23, 24, 25, 26])]
[ 1.  2.  3.]
[list([15, 16, 17, 18, 19, 20]) list([21, 22, 23, 24, 25, 26])
 list([27, 28, 29, 30, 31, 32])]

[15 21 27]
[15 16 17 18 19 20]
[1, 1, 1, 1, 1, 1]

ImportanceOfBeingErnest · Accepted Answer · 2019-10-19 20:56:53Z

4

I suppose all lists of y values have the same length? In that case

import numpy as np
import matplotlib.pyplot as plt

data = [
  [1, [15, 16, 17, 18, 19, 20]],
  [2, [21, 22, 23, 24, 25, 26]],
  [3, [27, 28, 29, 30, 31, 32]],
]

x, y = zip(*data)
y = np.array(y)

plt.scatter(np.repeat(x, y.shape[1]), y.flat)

plt.show()

answered Oct 19, 2019 at 20:56

ImportanceOfBeingErnest

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1 Comment

sdbbs Over a year ago

Thanks @ImportanceOfBeingErnest - yes, all lists of y values have the same lengths. Interesting approach, creating an x array long enough for the plot, and then flattening the y into a 1D array - good to have it as reference!

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