Understanding Matplotlib’s Bar Plot Ordering: A Deep Dive

Introduction

Matplotlib is a powerful Python library used for creating high-quality 2D and 3D plots, charts, and graphs. One of its most commonly used plots is the bar chart, which is used to display categorical data with numerical values. However, in our experience, many users have encountered an issue where the bars seem to automatically order themselves by the x-axis, rather than being sorted by their corresponding y-values.

In this article, we will explore the reasons behind this behavior and provide a step-by-step solution to fix it.

Understanding Bar Plot Order

Before diving into the solution, let’s first understand how bar plots work. In a bar plot, each bar represents a category or group, and the height of the bar corresponds to the value of that category. The x-axis typically represents the categories, while the y-axis represents the values.

When creating a bar plot using matplotlib, the order in which the bars are displayed is determined by the index of the data series used to create the plot. This means that if you use df.index as the x-values for your bar plot, it will display the bars in the same order as the index (i.e., 0, 1, 2, etc.).

However, when sorting the data before creating the plot, matplotlib does not automatically sort the index. Instead, it uses the original index values from the DataFrame.

The Problem: Sorting by Y-Values

Now that we understand how bar plots work and how matplotlib sorts the data, let’s explore why our plot is displaying bars in the wrong order (i.e., sorted by x-axis instead of y-values).

When sorting a Series using df.sort_values(by="values", ascending=False), we are reordering the values based on their magnitude. However, this only changes the internal ordering of the Series; it does not affect how the index is used to display the bars.

To fix this issue, we need to reset the index after sorting the data. This will update the index to reflect the new order of the values, ensuring that the bars are displayed in the correct order (i.e., sorted by y-values).

The Solution: Resetting the Index

Here’s how you can modify your code to fix this issue:

ids = [1,7,5]
values = [3.0, 9000.0, 2.7]

df = pd.DataFrame(
    {
        "ids": ids,
        "values" : values
    }
)

# Sort the data by y-values (i.e., "values")
df = df.sort_values(by="values", ascending=False)

# Reset the index to update its order
df= df.reset_index(inplace=False)

In this modified code, we first sort the data by the values column in descending order. Then, we reset the index using the reset_index method with inplace=False. This updates the index to reflect the new order of the values.

By resetting the index, we ensure that the bars are displayed in the correct order (i.e., sorted by y-values). The x-axis will display the categories as before, but now they will be paired correctly with their corresponding y-values.

Conclusion

In this article, we explored why matplotlib’s bar plot seems to automatically order itself by the x-axis and provided a step-by-step solution to fix it. By understanding how bar plots work and how matplotlib sorts data, we can modify our code to sort the data correctly before creating the plot.

With this solution, you should now be able to create bar plots with correct ordering, regardless of whether you’re working with categorical or numerical data.

Last modified on 2023-11-06