I have a numpy array that I need to plot as a heatmap. The numpy array would also contain NaN values which I need to exclude from plotting. I was told in other posts that numpy automatically masks the NaN values in the plot, but its somehow not working for me. Here is a sample code
column_labels = list('ABCDEFGH')
row_labels = list('WXYZ')
fig, ax = plt.subplots()
data = np.array([[ 0.96753494, 0.52349944, 0.0254628 , 0.5104103 ],
[ 0.07320069, 0.91278731, 0.97094436, 0.70533351],
[ 0.30162006, 0.49068337, 0.41837729, 0.71139215],
[ 0.19786101, 0.15882713, 0.59028841, 0.06242765],
[ 0.51505872, 0.07798389, 0.58790067, 0.44782683],
[ 0.68975694, 0.53535385, 0.15696023, 0.35641951],
[ 0.66481995, 0.03576846, 0.9623601 , 0.96006395],
[ 0.45865404, 0.50433582, 0.18182575, 0.35126449],])
data[3,:] = np.nan
heatmap = ax.pcolor(data, cmap=plt.cm.seismic)
fig.colorbar(heatmap)
# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[1])+0.5, minor=False)
ax.set_yticks(np.arange(data.shape[0])+0.5, minor=False)
# want a more natural, table-like display
ax.invert_yaxis()
ax.xaxis.tick_top()
ax.set_xticklabels(row_labels, minor=False)
ax.set_yticklabels(column_labels, minor=False)
plt.show()
The plots looks like
Clearly this is very different from the plot without the Nan which looks like 
I want to avoid the NaN values completely from the legend and preferably mark it with some symbol such as X. How can I achieve the same?