How do you show multiple graphs in python?
In this Python Matplotlib tutorial, we’ll discuss the Matplotlib multiple plots in python. Here we will cover different examples related to the multiple plots using matplotlib. Moreover, we’ll also cover the following topics: Show
Matplotlib’s subplot() and subplots() functions facilitate the creation of a grid of multiple plots within a single figure. Multiple pots are made and arranged in a row from the top left in a figure. subplot() functionThe syntax for subplot() function is as given below:
The parameters are as follow:
In the first syntax, we pass three separate integers arguments describing the position of the multiple plots. In the second syntax, we pass a three-digit integer to specify the positional argument to define nrows, ncols, and index. subplots() functionThe syntax for subplots() function is as given below:
The parameters are as follow:
subplot() vs subplots()While using the subplots() function you can use just one line of code to produce a figure with multiple plots. On the other hand, the subplot() function only constructs a single subplot ax at a given grid position. Also, check Matplotlib subplots_adjust Matplotlib multiple plots exampleHere we’ll see an example of multiple plots using matplotlib functions subplot() and subplots(). Let’s see examples: Example #1 In this example, we’ll use the subplot() function to create multiple plots.
Example #2 In this example, we’ll use the subplots() function to create multiple plots.
Read: Matplotlib increase plot size Matplotlib multiple plots one titleHere we’ll learn to add one title or we can say that common title on multiple plots using matplotlib. The suptitle() function is used to add a centered title to the figure. Let’s see examples related to this: Example #1 In this example, we use the subplot() function to draw multiple plots, and to add one title use the suptitle() function.
Example #2 In this example, we use the subplots() function to draw multiple plots, and to add one title use the suptitle() function.
Read: What is add_axes matplotlib Matplotlib multiple plots one legendIn matplotlib, the legend is used to express the graph elements. We can set and adjust the legends anywhere in the plot. Sometimes, it is requisite to create a single legend with multiple plots. Let’s see an example:
Recommendation: Matplotlib scatter plot legend Matplotlib plot multiple rectanglesIn matplotlib, the patches module allows us to overlay shapes such as rectangles on top of a plot. The Rectangle() function in the patches module can be used to add a rectangle. The Rectangle function takes the width and height of the rectangle you need, as well as the left and bottom positions. The rectangle highlights the specific portion of the plot as we needed. The syntax to plot rectangle is given below:
The above-used parameters are defined below:
Let’s see examples related to this: Example #1 In this example, we plot multiple rectangles to highlight the highest and lowest weight and height.
We will use the weight-height dataset and load it directly from the CSV file. Click here to download the dataset: df.head()df.tail()
Example #2 In this example, we plot multiple rectangles to highlight the weight and height range according to the minimum and maximum BMI index.
Import necessary libraries for defining data coordinates and plotting graph and rectangle patches.
Next, we load the dataset using read_csv() function. Click here to download the dataset: df.head()
df.tail()
Here we use the rectangles to highlight the range of weight and height corresponding to the minimum and maximum index of BMI. Read: Matplotlib time series plot Matplotlib multiple plots one colorbarHere we’ll learn to add one colorbar for multiple plots in the figure using matplotlib. Let’s see examples: Example #1 In this example, we use a different dataset to plots multiple charts with one colorbar.
Example #2
Here we create 6 multiple plots with 3 rows and 2 columns with one colorbar. Also, check: Matplotlib scatter plot color Matplotlib multiple polar plotsHere we’ll learn to create multiple polar plots using matplotlib. To add an Axes to the figure as part of multiple plots, we use the add_subplot() method of the matplotlib library’s figure module. Let’s take an example:
Read: Matplotlib tight_layout – Helpful tutorial Matplotlib multiple boxplotHere we’ll learn to plot multiple boxplots with the help of an example using matplotlib. Let’s see an example:
Read: Matplotlib update plot in loop Matplotlib multiple violin plotsViolin plots combine the features of a box plot and a histogram. Data distributions are visualized using violin plots, which show the data’s range, median, and distribution. The following is the syntax:
Here we’ll see an example of multiple violin plots:
Read: Matplotlib Pie Chart Tutorial Matplotlib multiple circle plotsIn matplotlib, the patches module allows us to overlay shapes such as circles on top of a plot. The Circle() function in the patches module can be used to add a circle. The Circle function takes the center of the circle you need, as well as the radius. The circle patches are also used to highlights the specific portion of the plot as we needed. The following is the syntax:
Let’s see an example related to multiple circle plots:
Matplotlib multiple contour plotsContour plots, also known as level plots, are a multivariate analytic tool that allows you to visualize 3-D plots in 2-D space. Contour plots are commonly used in meteorological departments to illustrate densities, elevations, or mountain heights. The matplotlib contour() function is used to draw contour plots. The following is the syntax:
Let’s see an example:
Example #2 Here we will use the contourf() function which draws the filled contours. We use the same data set defined in the above example.
The only difference between this and the first example is that we call the contourf() method. Matplotlib multiple plots contourRead: Matplotlib multiple bar chart Matplotlib multiple plots histogramHere we’ll learn to plot multiple histogram graphs with the help of examples using matplotlib. Example:
Read: Stacked Bar Chart Matplotlib Matplotlib multiple plots seabornHere we’ll learn to draw multiple seaborn plots using matplotlib. Let’s see an example:
Also, take a look at some tutorials on Matplotlib.
In this Python tutorial, we have discussed the “Matplotlib multiple plots” and we have also covered some examples related to it. These are the following topics that we have discussed in this tutorial.
Python is one of the most popular languages in the United States of America. I have been working with Python for a long time and I have expertise in working with various libraries on Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… I have experience in working with various clients in countries like United States, Canada, United Kingdom, Australia, New Zealand, etc. Check out my profile. How do you display multiple plots in python?Matplotlib multiple contour plots. Import matplotlib. pyplot and numpy libraries.. To create multiple plots, we use subplots() function.. To define data coordinates, we use linspace(), meshgrid(), cos(), sin(), tan() functions.. To plot countor plots, we use contour() function.. To display the figure, we use show() function.. How do you plot multiple graphs on different figures in Python?Managing multiple figures in pyplot. import matplotlib.pyplot as plt import numpy as np t = np. arange(0.0, 2.0, 0.01) s1 = np. sin(2*np. pi*t) s2 = np. sin(4*np. ... . figure(1) plt. subplot(211) plt. plot(t, s1) plt. subplot(212) plt. plot(t, 2*s1). figure(1) plt. subplot(211) plt. plot(t, s2, 's') ax = plt. gca() ax.. How do you plot 3 graphs side by side in Python?To create multiple plots we use the subplot function of pyplot module in Matplotlib. Parameters: nrows is for number of rows means if the row is 1 then the plots lie horizontally. ncolumns stands for column means if the column is 1 then the plot lie vertically.
How do I show multiple figures in Matplotlib?Create a new figure, or activate an existing figure, with the window title “Welcome to figure 1”.. Draw a line using plot() method, over the current figure.. Create a new figure, or activate an existing figure, with the window title “Welcome to figure 2”.. Draw a line using plot() method, over the current figure.. |