Creating 3D Plots with Dates on the X and Y Axes Using Matplotlib

Understanding 3D Plots with Matplotlib

Matplotlib is a powerful plotting library for Python, capable of creating high-quality 2D and 3D plots. In this article, we will explore how to create a 3D plot where the x-axis represents two different dates, the y-axis also represents these dates, and the z-axis represents a measurement.

Prerequisites

Before diving into the solution, it’s essential to have a good understanding of the following concepts:

NumPy: The NumPy library is used for efficient numerical computation in Python. It provides support for large, multi-dimensional arrays and matrices.
Matplotlib: Matplotlib is a plotting library that can be used to create high-quality 2D and 3D plots. We will use it extensively throughout this article.
Pandas: The Pandas library is used for data manipulation and analysis in Python.

Creating a 3D Plot with Dates on the X and Y Axes

To create a 3D plot where the x-axis represents two different dates, we need to ensure that the date1 and date2 columns are of type datetime64[ns]. We can do this by using the pd.to_datetime() function.

import pandas as pd
import numpy as np

# Create a DataFrame with date columns
df = pd.DataFrame({
    'date1': pd.date_range(start='2018-01-05', end='2018-04-15', freq='1D'),
    'date2': pd.date_range(start='2018-01-19', end='2018-04-29', freq='1D')
})

# Convert the date columns to datetime type
df['date1'] = pd.to_datetime(df['date1'])
df['date2'] = pd.to_datetime(df['date2'])

print(df.head())

Formatting Dates on the X and Y Axes

Once we have the date columns in datetime format, we can use the FuncFormatter from Matplotlib’s ticker module to format the dates on the x-axis and y-axis.

import matplotlib.ticker as ticker

# Define a function to format dates
def format_date(x, pos=None):
    return x.strftime('%Y-%m-%d')

# Create a figure and axis
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Plot the data
ax.plot_trisurf(df['date1'], df['date2'], df['mydata'], cmap=cm.coolwarm, linewidth=0.2)

# Set the x-axis tick labels to dates
ax.set_xticks([i for i in range(len(df))])
ax.set_xticklabels(df['date1'][ax.get_xticks()], rotation=45)
ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))

# Set the y-axis tick labels to dates
ax.set_yticks([i for i in range(len(df))])
ax.set_yticklabels(df['date2'][ax.get_yticks()], rotation=45)
ax.yaxis.set_major_formatter(ticker.FuncFormatter(format_date))

Resolving the `RuntimeError: Error in qhull Delaunay triangulation calculation` Issue

The error message you provided indicates that there was an issue with the Delaunay triangulation calculation. This is likely due to the fact that the input data for plot_trisurf() is not numerical.

To resolve this issue, we need to convert the date columns to a numerical format that can be used by plot_trisurf(). We can do this by using the np.arange() function to create an array of dates, and then converting these dates to a numerical representation using the datetime.date class.

import numpy as np

# Create an array of date indices
date_indices = np.arange(len(df))

# Convert the date columns to datetime objects
dates = df['date1'].values + (df['date2'].values - df['date1'].values) * np.arange(1, len(df))

# Plot the data
ax.plot_trisurf(date_indices, date_indices, df['mydata'], cmap=cm.coolwarm, linewidth=0.2)

Creating a 3D Plot with Dates on the X and Y Axes Using Triangulation

Another approach to create a 3D plot where the x-axis represents two different dates is to use triangulation.

import matplotlib.pyplot as plt
from scipy.spatial import Delaunay

# Create a figure and axis
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Define the date data
date_data = np.array([i for i in range(len(df))]).reshape(-1, 2)

# Perform triangulation on the date data
triangulation = Delaunay(date_data)

# Plot the data using triangulation
for simplex in triangulation.simplices:
    ax.plot_trisurf(date_data[simplex, 0], date_data[simplex, 1], df['mydata'][simplex], cmap=cm.coolwarm, linewidth=0.2)

Conclusion

In this article, we explored how to create a 3D plot where the x-axis represents two different dates, and the y-axis also represents these dates. We discussed various approaches to achieve this goal, including using plot_trisurf() with numerical data, triangulation, and formatting dates on the x-axis and y-axis using FuncFormatter.

Last modified on 2023-10-15