Based on this question about heatmaps in matplotlib, I wanted to move the x-axis titles to the top of the plot.
import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4,4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=plt.cm.Blues)
# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[0])+0.5, minor=False)
ax.set_yticks(np.arange(data.shape[1])+0.5, minor=False)
# want a more natural, table-like display
ax.invert_yaxis()
ax.xaxis.set_label_position('top') # <-- This doesn't work!
ax.set_xticklabels(row_labels, minor=False)
ax.set_yticklabels(column_labels, minor=False)
plt.show()
However, calling matplotlib's set_label_position (as notated above) doesn't seem to have the desired effect. Here's my output:
What am I doing wrong?
With matplotlib version 3.3. 0, the matplotlib functions set_xlabel and set_ylabel have a new parameter “loc” that can help adjust the positions of axis labels. For the x-axis label, it supports the values 'left', 'center', or 'right' to place the label towards left/center/right.
mpl_axes_aligner. shift expands or shifts the plotting range of a matplotlib axis to align the origin with the given position.
Matplotlib x-axis label overlap In matplotlib, we have a method setp() that is used to set the rotation and alignment attributes of tick labels to avoid overlapping. To get ticklabels, we use the plt. setp() and get.
Use
ax.xaxis.tick_top()
to place the tick marks at the top of the image. The command
ax.set_xlabel('X LABEL')
ax.xaxis.set_label_position('top')
affects the label, not the tick marks.
import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=plt.cm.Blues)
# 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(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)
plt.show()
You want set_ticks_position
rather than set_label_position
:
ax.xaxis.set_ticks_position('top') # the rest is the same
This gives me:
tick_params is very useful for setting tick properties. Labels can be moved to the top with:
ax.tick_params(labelbottom=False,labeltop=True)
You've got to do some extra massaging if you want the ticks (not labels) to show up on the top and bottom (not just the top). The only way I could do this is with a minor change to unutbu's code:
import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=plt.cm.Blues)
# 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.xaxis.set_ticks_position('both') # THIS IS THE ONLY CHANGE
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)
plt.show()
Output:
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