How To Plot Float Values In Python

Float values are numbers that include a decimal point, also known as floating-point numbers. In Python, we can plot these values using various libraries like Matplotlib, Seaborn, Plotly, etc.

Plotting allows us to visualize the data, and understand the patterns, trends, and relationships among different variables. In this tutorial, we will explore how to plot float values in Python using Matplotlib.

Steps to Plot Float Values in Python using Matplotlib

Step 1: Importing the Required Libraries

Before plotting, we need to import the required libraries. We will use the Matplotlib library for data visualization.

Step 2: Creating the Data

To plot a graph, we need data. Let’s create some data using Numpy and Pandas libraries.

This will generate 100 random float values and store them in a Pandas DataFrame.

Step 3: Plotting the Data

Now, we are ready to plot our data using Matplotlib. We will use the ‘plot’ function to create a line plot.

This will generate a line plot of the float values.

Step 4: Customizing the Plot

We can customize our plot by adding labels, titles, colors, etc. Let’s add some labels to our plot.

This will generate a line plot with a title, an x-axis label, and a y-axis label.

Step 5: Other Types of Plots

Apart from line plots, we can also create scatter plots, bar plots, box plots, histogram, density plots, etc. using the Matplotlib library. Here’s an example of creating a scatter plot.

This will generate a scatter plot of the float values.


In this tutorial, we learned how to plot float values in Python using the Matplotlib library. We also learned how to create line plots, and scatter plots, and customize the plots. Plotting is an essential tool for data analysis, and using Matplotlib makes it easier and more efficient.


Line Plot

Scatter Plot

Full Code


0  1.376030
1 -0.039227
2 -0.626623
3 -1.050990
4  0.891572