Python Articles

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How do you just show the text label in a plot legend in Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 1K+ Views

When creating matplotlib plots with legends, you might want to display only the text labels without the colored lines or markers. This can be achieved using specific parameters in the legend() method to hide the legend handles. Basic Approach To show only text labels in a plot legend, use the legend() method with these key parameters: handlelength=0 − Sets the length of legend handles to zero handletextpad=0 − Removes padding between handle and text fancybox=False − Uses simple rectangular legend box Example Here's how to create a plot with text-only legend labels ? ...

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Box plot with min, max, average and standard deviation in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 6K+ Views

A box plot is an effective way to visualize statistical measures like minimum, maximum, average, and standard deviation. Matplotlib combined with Pandas makes it easy to create box plots from calculated statistics. Creating Sample Data and Statistics First, let's create random data and calculate the required statistics − import numpy as np import pandas as pd from matplotlib import pyplot as plt # Set figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Create random dataset of 5x5 dimension data = np.random.randn(5, 5) print("Sample data shape:", data.shape) print("First few rows:") print(data[:3]) ...

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Adding a scatter of points to a boxplot using Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 5K+ Views

To add a scatter of points to a boxplot using Matplotlib, we can combine the boxplot() method with scatter() to overlay individual data points. This technique helps visualize both the distribution summary and actual data points. Steps Set the figure size and adjust the padding between and around the subplots. Create a DataFrame using DataFrame class with sample data columns. Generate boxplots from the DataFrame using boxplot() method. Enumerate through DataFrame columns to get x and y coordinates for scatter points. Add scatter points with slight horizontal jitter for better visibility. Display the figure using show() method. ...

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How to center labels in a Matplotlib histogram plot?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 7K+ Views

To place the labels at the center in a histogram plot, we can calculate the mid-point of each patch and place the ticklabels accordingly using xticks() method. This technique provides better visual alignment between the labels and their corresponding histogram bars. Steps Set the figure size and adjust the padding between and around the subplots. Create a random standard sample data, x. Initialize a variable for number of bins. Use hist() method to make a histogram plot. ...

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Show tick labels when sharing an axis in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 1K+ Views

When creating subplots that share an axis in Matplotlib, you might want to show tick labels on all subplots instead of hiding them on shared axes. By default, Matplotlib hides tick labels on shared axes to avoid redundancy, but you can control this behavior. Default Behavior with Shared Y-Axis When using sharey parameter, Matplotlib automatically hides y-axis tick labels on the right subplot to avoid duplication ? import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [10, 4] plt.rcParams["figure.autolayout"] = True # Create first subplot ax1 = plt.subplot(1, 2, 1) ax1.plot([1, 4, 9]) ax1.set_title('Left Plot') # ...

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How to extract data from a Matplotlib plot?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 16K+ Views

To extract data from a plot in matplotlib, we can use get_xdata() and get_ydata() methods. This is useful when you need to retrieve the underlying data points from an existing plot object. Basic Data Extraction The following example demonstrates how to extract x and y coordinates from a matplotlib plot ? import numpy as np from matplotlib import pyplot as plt # Configure plot appearance plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Create sample data y = np.array([1, 3, 2, 5, 2, 3, 1]) # Create plot and store line object curve, ...

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How to plot complex numbers (Argand Diagram) using Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 774 Views

Complex numbers can be visualized using an Argand diagram, where the real part is plotted on the x-axis and the imaginary part on the y-axis. Matplotlib provides an excellent way to create these plots using scatter plots. Basic Argand Diagram Let's start by plotting a simple set of complex numbers ? import numpy as np import matplotlib.pyplot as plt # Create complex numbers complex_numbers = [1+2j, 3+1j, 2-1j, -1+3j, -2-2j] # Extract real and imaginary parts real_parts = [z.real for z in complex_numbers] imag_parts = [z.imag for z in complex_numbers] # Create the ...

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Plotting multiple line graphs using Pandas and Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 25-Mar-2026 4K+ Views

To plot multiple line graphs using Pandas and Matplotlib, we can create a DataFrame with different datasets and use the plot() method to visualize multiple lines on the same graph. This approach is useful for comparing trends across different data series. Basic Setup First, let's set up the required libraries and configure the plot settings ? import pandas as pd import matplotlib.pyplot as plt # Set figure size for better visualization plt.rcParams["figure.figsize"] = [10, 6] plt.rcParams["figure.autolayout"] = True Creating Sample Data We'll create a DataFrame with data for three different mathematical functions ...

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Program to change the root of a binary tree using Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 980 Views

Suppose we are given a binary tree and need to change its root to a specific leaf node. This transformation involves restructuring the tree by following specific rules to maintain the binary tree structure while making the leaf node the new root. Transformation Rules To change the root of a binary tree, we follow these rules − If a node has a left child, it becomes the right child. A node's parent becomes its left child. In this process, the parent node's link to that node becomes null, so it will have only one child. ...

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Program to fix a erroneous binary tree using Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 287 Views

When a binary tree has an erroneous connection where a node's right child pointer incorrectly points to another node at the same level, we need to identify and fix this error. The solution involves detecting the problematic node and removing it along with its descendants, except for the node it erroneously points to. Consider this example where node 4's right child incorrectly points to node 6: 5 3 7 ...

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