Plotting multiple pandas DataFrames in one 3D scatterplotplot

Question

I want to plot two dataframes in one 3D scatterplot.

This is the code I have for one dataframe:

import seaborn as sns
from mpl_toolkits.mplot3d import Axes3D

...

sns.set(style = "darkgrid")

fig = plt.figure()
ax = fig.add_subplot(111, projection = '3d')
x = df['xitem']
y = df['yitem']
z = df['zitem']

ax.set_xlabel("X Label")
ax.set_ylabel("Y Label")
ax.set_zlabel("Z Label")

ax.scatter(x, y, z)

plt.show()

I can't figure out how to adjust this so I have two different dataframes plotted on the same plot but with different colors. How can I do this?

Edit: I'm looking for how to use two dataframes for a 3D plot specifically.

PieCot · Accepted Answer · 2021-02-13 12:18:55Z

1

Assuming that you have two DataFrame called df1 and df2, both containing columns 'xitem', 'yitem', 'zitem', you can plot them in this way:

for curr_df, c in zip((df1, df2), ('b', 'r')):
    ax.scatter(*curr_df[['xitem', 'yitem', 'zitem']].values.T, color=c)

Here a complete example:

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

sns.set(style = "darkgrid")

df1 = pd.DataFrame(
    data=np.random.random((100, 3)) + np.array([1, 1, 1]),
    columns=['xitem', 'yitem', 'zitem'],
)

df2 = pd.DataFrame(
    data=np.random.random((100, 3)),
    columns=['xitem', 'yitem', 'zitem'],
)

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

for curr_df, c in zip((df1, df2), ('b', 'r')):
    ax.scatter(*curr_df[['xitem', 'yitem', 'zitem']].values.T, color=c)

ax.set_xlabel("X Label")
ax.set_ylabel("Y Label")
ax.set_zlabel("Z Label")

plt.show()

edited Feb 13, 2021 at 12:18

answered Feb 13, 2021 at 0:35

PieCot

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2 Comments

Mr. T Over a year ago

Since heavily importing into the global namespace may result in unexpected behavior, the use of pylab is strongly discouraged. Use matplotlib.pyplot instead.

PieCot Over a year ago

@Mr. T thanks, I didn't know that. I've updated the answer

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