How to Plot Numerical Values In Matplotlib?

2 minutes read

To plot numerical values in matplotlib, you need to first import the matplotlib library in your python script. Then, you can create a figure and axis object using the plt.subplots() function. Next, you can use the plot() function to plot your numerical values on the axis. You can customize the plot by adding labels, titles, legends, and changing the plot style and color. Finally, you can display the plot by calling the plt.show() function.


What is the default size of a matplotlib plot?

The default size of a matplotlib plot is 6.4 by 4.8 inches.


How to plot numerical values in matplotlib using a line plot?

To plot numerical values in matplotlib using a line plot, you can follow these steps:

  1. Import the necessary libraries:
1
import matplotlib.pyplot as plt


  1. Define your numerical values as lists or arrays:
1
2
x_values = [1, 2, 3, 4, 5]
y_values = [10, 12, 15, 18, 20]


  1. Create a line plot using the plot function:
1
plt.plot(x_values, y_values)


  1. Add labels to the plot:
1
2
3
plt.xlabel('X values')
plt.ylabel('Y values')
plt.title('Line Plot of Numerical Values')


  1. Display the plot:
1
plt.show()


This will create a line plot of the numerical values specified in x_values and y_values with the x-axis labeled as 'X values', the y-axis labeled as 'Y values', and the plot titled as 'Line Plot of Numerical Values'.


How to add data labels to a plot in matplotlib?

To add data labels to a plot in matplotlib, you can use the annotate function in matplotlib.


Here is an example code snippet:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [10, 20, 15, 25, 30]

# Create a plot
plt.plot(x, y)

# Add data labels
for i, txt in enumerate(y):
    plt.annotate(txt, (x[i], y[i]), textcoords="offset points", xytext=(0,10), ha='center')

plt.show()


In this code, we first create a plot using plt.plot. Then, we loop through the data points and use the annotate function to add data labels to each point. The textcoords argument specifies that the text is offset by 10 points from the data point, and the ha argument specifies that the text should be centered horizontally.


You can customize the appearance of the data labels by adjusting the arguments in the annotate function.

Facebook Twitter LinkedIn Telegram

Related Posts:

To plot dates in matplotlib, you can start by importing the necessary libraries such as matplotlib and datetime. Then, create a plot using the plot() function as you normally would, but instead of using numerical values on the x-axis, use datetime objects.You ...
To plot a numpy array with matplotlib, you first need to import the necessary libraries by using the following command: import numpy as np import matplotlib.pyplot as pltNext, you can create a numpy array with the data that you want to plot. For example, you c...
To add a label to a plot in Matplotlib, you can use the plt.xlabel() and plt.ylabel() functions to add labels to the x and y axes, respectively. You can also use the plt.title() function to add a title to the plot. Additionally, you can create a legend for the...
To plot asynchronously in matplotlib, you can use the asyncio library in Python. By running the plotting code in an asynchronous function, you can continue executing other tasks while the plot is being generated. This can be useful when you have long-running p...
In matplotlib, you can hide text when plotting by setting the visible attribute to False. This can be done when creating text elements on a plot using the text() function. By setting visible=False, the text will not be displayed on the plot when it is rendered...