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()
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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 :
In my hope, I would like to have this type of graph :
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.
source https://stackoverflow.com/questions/76323398/how-to-plot-a-3d-bar-chart-with-categorical-variable
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