CODEWITHSUNDEEP
pythonmatplotlibmplot3dmatplotlib-3dbar3d
Romain Lombardi
Romain Lombardi

Reputation: 21

How to plot a 3D bar chart with categorical variable

today I have tried to plot a 3D bar chart with python. For that I used my dataset containing 3 numeric variables and convert 2 in categorical variable, 'fibrinogen' and 'RR__root_mean_square' (by interval; 4 in total) with pd.cut().

An example of the first row of my dataset:

    Fibrinogen  RR__root_mean_square  Weight gain
2         5.15             26.255383         -2.0
3         0.99             20.934106          0.5
7         2.12             24.252434         -1.0
11        1.64             17.004289          3.0
12        3.06             21.201716          0.0

This is my own code :

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# sample data
data = {'Fibrinogen': [5.15, 0.99, 2.12, 1.64, 3.06],
        'RR__root_mean_square': [26.255383, 20.934106, 24.252434, 17.004289, 21.201716],
        'Weight gain': [-2.0, 0.5, -1.0, 3.0, 0.0]}

X_success = pd.DataFrame(data)

x1 = pd.cut(X_success['Fibrinogen'], [0,2,4,10]).cat.codes
y1 = pd.cut(X_success['RR__root_mean_square'], [15,25,32.5,40]).cat.codes
z1 = X_success['Weight gain']

# cat.codes to don't have the 'float() argument must be a string or a number, not 'pandas._libs.interval.Interval'' error
# But I loose the label...

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

ax.bar(x1, y1, z1, zdir='y', alpha=0.8)
plt.show()

With this code I have this unreadable type of graph : enter image description here

In my hope, I would like to have this type of graph : enter image description here

How can I plot a 3D bar chart with python?

This answer is very functional. But, I have some negative value in weight gain (because patient can lose weight). I don't no know if I can modify the color or the visibility for the negative value ? and if can I replace the x and y axes to zero.

enter image description here

Upvotes: 1

Views: 843

Answers (1)

Corralien
Corralien

Reputation: 120559

A bar plot is not intended to display individual values, you have to aggregate your values (Weight gain) with mean for example:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.DataFrame({'Fibrinogen': np.random.uniform(0, 10, 100),
                   'RR__root_mean_square': np.random.uniform(15, 40, 100),
                   'Weight gain': np.random.uniform(0, 10, 100)})

x1 = pd.cut(X_success['Fibrinogen'], [0,2,4,10]).cat.codes
y1 = pd.cut(X_success['RR__root_mean_square'], [15,25,32.5,40]).cat.codes
z1 = X_success['Weight gain']
out = (pd.DataFrame({'Fibrinogen': x1,
                     'RR__root_mean_square': y1,
                     'Weight gain': z1})
         .groupby(['Fibrinogen', 'RR__root_mean_square'], as_index=False)['Weight gain'].mean())

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
lgth = len(out)
ax.bar3d(out['Fibrinogen'], out['RR__root_mean_square'], np.zeros(lgth), np.ones(lgth)-0.5, np.ones(lgth)-0.5, out['Weight gain'])

Output:

enter image description here

Upvotes: 0

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