Best Matplotlib Guides to Buy in October 2025
Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python
Python GUI Programming with Tkinter: Design and build functional and user-friendly GUI applications, 2nd Edition
Python Data Cleaning Cookbook: Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI
Python for Engineering and Scientific Computing: Practical Applications with NumPy, SciPy, Matplotlib, and More (Rheinwerk Computing)
Python Data Analytics: With Pandas, NumPy, and Matplotlib
Data Visualization in Python with Pandas and Matplotlib
Effective Visualization: Exploiting Matplotlib & Pandas (Treading on Python)
Python Data Analytics: With Pandas, NumPy, and Matplotlib
Matplotlib 2.x By Example: Multi-dimensional charts, graphs, and plots in Python
To remove the area under the curve in Matplotlib, you can simply plot the desired curve without filling it in. By default, Matplotlib will fill in the area under a curve when using the plot function. To prevent this, you can use the plot function with the fillstyle='none' parameter, which will plot the curve without filling in the area underneath. Additionally, you can use the fill_between function with the alpha=0 parameter to fill the area with a transparent color, effectively removing the filled area under the curve. This will allow you to display only the curve without any filled area underneath in your Matplotlib plot.
How to add grid lines to a matplotlib plot?
You can add grid lines to a matplotlib plot by using the grid() method in the Axes object. Here is an example of how to add grid lines to a plot:
import matplotlib.pyplot as plt
Create some data
x = [1, 2, 3, 4, 5] y = [2, 3, 5, 7, 11]
Create a plot
plt.plot(x, y)
Add grid lines
plt.grid(True)
Show the plot
plt.show()
In this example, plt.grid(True) adds grid lines to the plot. You can also customize the grid lines by passing in additional parameters to the grid() method. For example, plt.grid(True, linestyle='--', color='gray', linewidth=0.5) would add dashed gray grid lines with a line width of 0.5.
What is the significance of the xlim() and ylim() functions in matplotlib?
The xlim() and ylim() functions in matplotlib are used to set the limits of the x and y axes, respectively. This allows the user to specify the range of values that will be displayed on each axis, controlling the size and scale of the plot.
These functions are particularly useful when plotting multiple datasets on the same axes, as they allow the user to ensure that all data points are displayed within the desired range. Additionally, they can be used to zoom in on a particular section of the plot or to remove outliers that may skew the visualization.
Overall, the xlim() and ylim() functions provide control over the presentation of data in a plot, enabling users to customize the appearance of their visualizations to best communicate their intended message.
How to change the size of a matplotlib plot?
You can change the size of a matplotlib plot by setting the size explicitly using the figsize parameter when creating a figure using plt.subplots(). Here's an example:
import matplotlib.pyplot as plt
Create a figure with a specific size
fig, ax = plt.subplots(figsize=(8, 6))
Plot your data
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
Show the plot
plt.show()
In the above code snippet, the figsize=(8, 6) parameter passed to plt.subplots() specifies the size of the plot to be 8 inches in width and 6 inches in height. You can adjust these values to suit your needs.