Matplotlib Tutorial
Matplotlib Useful Resources
Selected Reading
- Matplotlib - Transforms
- Matplotlib - Working with Images
- Mathematical Expressions
- Matplotlib - Working With Text
- Matplotlib - 3D Surface plot
- Matplotlib - 3D Wireframe plot
- Matplotlib - 3D Contour Plot
- Three-dimensional Plotting
- Matplotlib - Violin Plot
- Matplotlib - Box Plot
- Matplotlib - Quiver Plot
- Matplotlib - Contour Plot
- Matplotlib - Scatter Plot
- Matplotlib - Pie Chart
- Matplotlib - Histogram
- Matplotlib - Bar Plot
- Matplotlib - Twin Axes
- Setting Ticks and Tick Labels
- Matplotlib - Setting Limits
- Matplotlib - Formatting Axes
- Matplotlib - Grids
- Matplotlib - Subplot2grid() Function
- Matplotlib - Subplots() Function
- Matplotlib - Multiplots
- Matplotlib - Axes Class
- Matplotlib - Figure Class
- Object-oriented Interface
- Matplotlib - PyLab module
- Matplotlib - Simple Plot
- Matplotlib - Pyplot API
- Matplotlib - Jupyter Notebook
- Matplotlib - Anaconda distribution
- Matplotlib - Environment Setup
- Matplotlib - Introduction
- Matplotlib - Home
Matplotlib Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Matplotlib - Subplots() Function
Matplotpb - Subplots() Function
Matplotpb’spyplot API has a convenience function called subplots() which acts as a utipty wrapper and helps in creating common layouts of subplots, including the enclosing figure object, in a single call.
Plt.subplots(nrows, ncols)
The two integer arguments to this function specify the number of rows and columns of the subplot grid. The function returns a figure object and a tuple containing axes objects equal to nrows*ncols. Each axes object is accessible by its index. Here we create a subplot of 2 rows by 2 columns and display 4 different plots in each subplot.
import matplotpb.pyplot as plt fig,a = plt.subplots(2,2) import numpy as np x = np.arange(1,5) a[0][0].plot(x,x*x) a[0][0].set_title( square ) a[0][1].plot(x,np.sqrt(x)) a[0][1].set_title( square root ) a[1][0].plot(x,np.exp(x)) a[1][0].set_title( exp ) a[1][1].plot(x,np.log10(x)) a[1][1].set_title( log ) plt.show()
The above pne of code generates the following output −
Advertisements