CODEWITHSUNDEEP
pythonmatplotlibmatplotlib-3dbar3d
Martina Lazzarin
Martina Lazzarin

Reputation: 169

How to make 3D bar plot from dataframe

This is how my df looks like:

hr    slope  value   
8      s_1     6     
10     s_1     2     
8      s_2     4     
10     s_2     8

I would like to make a 3D bar plot with 'hr' in the x-axis, 'value' in the y-axis, and 'slopes' in the z-axis.

xpos = df['hr']
ypos = df['value']
xpos, ypos = np.meshgrid(xpos+0.25, ypos+0.25)
xpos = xpos.flatten()
ypos = ypos.flatten()
zpos=np.zeros(df.shape).flatten()

dx=0.5 * np.ones_like(zpos)
dy=0.5 * np.ones_like(zpos)
dz=df.values.ravel()

ax.bar3d(xpos,ypos,zpos,dx,dy,dz,color='b', alpha=0.5)
plt.show()

I get the following error messages:

ValueError: shape mismatch: objects cannot be broadcast to a single shape

Any help is very welcome, thank you in advance

Upvotes: 4

Views: 6090

Answers (1)

Ynjxsjmh
Ynjxsjmh

Reputation: 30032

The documentation of bar3d() can be found at https://matplotlib.org/mpl_toolkits/mplot3d/api.html#mpl_toolkits.mplot3d.axes3d.Axes3D.bar3d. Here is an explanation of it. Official demo can be found at https://matplotlib.org/3.1.1/gallery/mplot3d/3d_bars.html.

import matplotlib.pyplot as plt

xpos = [1, 2, 3]  # x coordinates of each bar
ypos = [0, 0, 0]  # y coordinates of each bar
zpos = [0, 0, 0]  # z coordinates of each bar
dx = [0.5, 0.5, 0.5]  # Width of each bar
dy = [0.5, 0.5, 0.5]  # Depth of each bar
dz = [5, 4, 7]        # Height of each bar

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

ax.bar3d(xpos,ypos,zpos,dx,dy,dz, color='b', alpha=0.5)

plt.show()

enter image description here

The problem why you got this error is that the length of xpos, ypos, zpos, dx, dy, dz is not the same. Besides, the element of dz contains string.

Here is how I reproduce your example

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

df = pd.read_csv('1.csv')

xpos = df['hr']
ypos = df['value']

xpos, ypos = np.meshgrid(xpos+0.25, ypos+0.25)
xpos = xpos.flatten()
ypos = ypos.flatten()

zpos = np.zeros(df.shape).flatten()

dx = 0.5 * np.ones_like(zpos)
dy = 0.5 * np.ones_like(zpos)
dz = df[['hr', 'value']].values.ravel()

print(xpos)
print(ypos)
print(zpos)
print(dx)
print(dy)
print(dz) # [8 's_1' 6 10 's_1' 2 8 's_2' 4 10 's_2' 8]

print(len(xpos))  # 16
print(len(ypos))  # 16
print(len(zpos))  # 12
print(len(dx))    # 12
print(len(dy))    # 12
print(len(dz))    # 12

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

ax.bar3d(xpos,ypos,zpos,dx,dy,dz,color='b', alpha=0.5)

plt.show()

The content of 1.csv is

hr,slope,value
8,s_1,6
10,s_1,2
8,s_2,4
10,s_2,8

Upvotes: 2

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