Sorted data while plotting heatmap

Question

I've been trying to plot a heatmap with on the x-axis a timespan (with 5 minute increments) and on the y-axis a certain video that has been watched on the internet.

Everything is going well, and the data is good. For instance, a dataset might look like this:

[[0.5, 0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 
[0.5, 0.0, 0.0, 1.5, 0.0, 0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]

This means there are two rows and 22 columns (0:00:00 - 1:45:00).

I am using this code to plot the heatmap:

def printheatmap(title,names,data):
    data = np.array(data)
    fig, ax = plt.subplots()
    fig = plt.gcf()
    fig.set_size_inches(8, 11)
    heatmap = ax.pcolormesh(data, cmap=plt.cm.Blues, edgecolors='black')
    ax.set_title(title)
    ax.set_xticks(np.arange(data.shape[1])+0.5, minor=False)
    ax.set_yticks(np.arange(data.shape[0])+0.5, minor=False)
    ax.xaxis.tick_bottom()
    ax.set_xticklabels(times, minor=False,  weight='ultralight', rotation=40, ha='right')
    ax.set_yticklabels(names, minor=False)
    ax.grid(False)
    plt.colorbar(heatmap)
    plt.show()

But for some reason, the second row gets plotted first in the heatmap:

As you can see, the one that starts with (0.5;0;0;1.5) is at the top of the chart with the correct label. Is there any way in which I can 'preserve' the sorting I am doing manually?

The y-axis isn't inverted. With a larger data set, the plot seems to be completely random (but, apparently, the highest scores are at the bottom), while the last row should be:

[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

Here's another picture. I sorted the data set by date, but it just scrambles it up:

EDIT: Fixed it. Apparently using custom XPath-functions to sort your data isn't really working well with matplotlib. Sorting it manually seemed to do the trick.

Answer 1

use list slicing to reverse your data:

data = np.array(data[::-1])

or invert the Y-axis:

ax.invert_yaxis()