Python 3D plot for multiple dataframes

Question

Assuming that I have three Python pandas DataFrames:

df_sale = pd.DataFrame([[20,30,10], [30,20,20], [20,40,40]], columns=list("ABC"))

    A   B   C
0   20  30  10
1   30  20  20
2   20  40  40

df_people = pd.DataFrame([[2,3,1], [3,2,2], [2,4,4]], columns=list("ABC"))

    A   B   C
0   2   3   1
1   3   2   2
2   2   4   4

df_department = pd.DataFrame([[1,2,1], [1,1,2], [2,1,1]], columns=list("ABC"))

    A   B   C
0   1   2   1
1   1   1   2
2   2   1   1

How do I plot a 3D bar chart with all these 3 dataframes in the same place?

I want the X axis to be ['A', 'B', 'C'], Y axis to be the name of dataframes ['df_sale', 'df_people', 'df_department'], and Z axis to show the numbers.

Maximilian Peters · Accepted Answer · 2017-01-12 18:09:35Z

2

You could use matplotlib's 3D bars.

import pandas as pd
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

columns = ['A', 'B', 'C']
df_names = ['sale', 'people', 'department']
df = [pd.DataFrame([[20,30,10], [30,20,20], [20,40,40]], columns=columns), pd.DataFrame([[2,3,1], [3,2,2], [2,4,4]], columns=columns), pd.DataFrame([[1,2,1], [1,1,2], [2,1,1]], columns=columns)]

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

#make sure x and y axis get the right tick labels
plt.xticks([i for i in range(len(columns))], columns)
plt.yticks([i for i in range(len(df_names))], df_names)

#define a list for x positions
xs = list()
for i in range(len(df)):
    for j in range(len(columns)):
         xs.append(i + j * 0.1)

for c1, c in enumerate(['r', 'g', 'b']):
    ys = list()
    for i in range(len(columns)):
        ys.extend(df[c1].ix[:,i:i+1].unstack().tolist())
    cs = [c] * len(xs)    
    ax.bar(xs, ys, zs=c1, zdir='y', color=cs, alpha=0.5, width=0.1)

plt.show()

Multicolors and legend

import matplotlib
colors = ['r', 'g', 'b', 'c', 'm', 'y', '#eeefff', '#feefff', '#aeefff']
for c1 in range(3):
    ys = list()
    for i in range(len(columns)):
        ys.extend(df[c1].ix[:,i:i+1].unstack().tolist())
    ax.bar(xs, ys, zs=c1, zdir='y', color=colors, alpha=0.5, width=0.1)

legend = list()
for i, c in enumerate(colors):
    legend.append(matplotlib.patches.Patch(color=c, label='value {0} of column {1}'.format(i % 3, columns[i // 3])))
plt.legend(handles=legend, loc=4, bbox_to_anchor=(.9, 0), mode="expand")
plt.show()

edited Jan 12, 2017 at 18:09

answered Jan 11, 2017 at 23:56

Maximilian Peters

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2 Comments

DanZimmerman Over a year ago

Hi Max, thanks for your answer and this solves most of my questions. But I wonder what if the index names are not number [0,1,2,3...]. df[c1].ix[:,i:i+1] this part only works with numbers. Also, is there a way to color the three bars together with different colors? e.g. the bars fall under 'A', 'Sales'. What if we want to color them as red, green blue. Since they may represent time (Jan, Feb, Mar). And the same colors apply to people and department. And in the end we add legend for the colors. Is this doable? Thanks!

Maximilian Peters Over a year ago

pandas ix documentation: "A primarily label-location based indexer, with integer position fallback", i.e. you are good.

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