CODEWITHSUNDEEP
pythonmatplotlibseaborn
Mixalis
Mixalis

Reputation: 542

Heatmap with Categorical value as label

Given the following subset of my data

import matplotlib.pyplot as plt
import numpy as np
data = np.array([['Yes', 'No', 'No', 'Maybe', 'Yes', 'Yes', 'Yes'],
                    [0.21, 0.62, 0.56, 0.48, 0.32, 0.71, 0.01],
                    [1.1053, 1.5412, 1.4333, 1.1433, 1.1098, 1.1003, 1.2032]])

I want to plot a heatmap of the 2nd and 3rd row, and use the 1st row as labels in each box. I've tried using the plt.imshow() but it nags once I use the full dataset and I can't find a way to incorporate the categorical values as labels in each box.

On the other hand, if I do:

data1 = np.array([[0.21, 0.62, 0.56, 0.48, 0.32, 0.71, 0.01],
                    [1.1053, 1.5412, 1.4333, 1.1433, 1.1098, 1.1003, 1.2032]])

plt.imshow(data1, cmap='hot', interpolation='nearest')

I get a heatmap, but it's not very descriptive of what I want, because labels and axises are missing. Any suggestions?

enter image description here

The column names are 'Decision', 'Percentage', 'Salary multiplier'

Upvotes: 0

Views: 1077

Answers (2)

JohanC
JohanC

Reputation: 80339

First off, an np.array needs all elements to be of the same type. As your array also contains strings, this will be made the common type. So, best not to have the array as a np.array, or use a separate array for the strings.

As your data seem to be x,y positions, it makes sense to use them as a coordinate in a scatter plot. You can color the x,y position depending on the Yes/Maybe/No value, for example assigning green/yellow/red to them. Additionally, you could add a text, as you have very few data. With more data, you'd better create a legend to connect labels with their coloring.

from matplotlib import pyplot as plt
import numpy as np

data = [['Yes', 'No', 'No', 'Maybe', 'Yes', 'Yes', 'Yes'],
        [0.21, 0.62, 0.56, 0.48, 0.32, 0.71, 0.01],
        [1.1053, 1.5412, 1.4333, 1.1433, 1.1098, 1.1003, 1.2032]]

answer_to_color = {'Yes': 'limegreen', 'Maybe': 'gold', 'No': 'crimson'}
colors = [answer_to_color[ans] for ans in data[0]]
plt.scatter(data[1], data[2], c=colors, s=500, ls='-', edgecolors='black')

for label, x, y in zip(data[0], data[1], data[2]):
    plt.text(x+0.01, y+0.03, label)
plt.show()

result

To use your column names to label the graph, you could add:

plt.title('Decision')
plt.xlabel('Percentage')
plt.ylabel('Salary multiplier')

Upvotes: 1

Zaraki Kenpachi
Zaraki Kenpachi

Reputation: 5730

You need to setup new axis with ax2.

import matplotlib.pyplot as plt
import numpy as np

data = np.array([[0.21, 0.62, 0.56, 0.48, 0.32, 0.71, 0.01],
                    [1.1053, 1.5412, 1.4333, 1.1433, 1.1098, 1.1003, 1.2032]])

fig, ax1 = plt.subplots()
ax1.pcolor(data, cmap='hot')

# set top axis
ax2 = ax1.twiny()
ax2.set_xlim(ax1.get_xlim())
ax2.set_xticks(np.linspace(0.5, 6.5, num=7))
ax2.set_xticklabels(['Yes', 'No', 'No', 'Maybe', 'Yes', 'Yes', 'Yes'])

# change ticks for bottom axis
ax1.set_xticks(np.linspace(0.5, 6.5, num=7))
ax1.set_xticklabels(np.linspace(0, 6, num=7, dtype = int))

plt.show()

Output:

enter image description here

Upvotes: 0

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