Understanding Pandas Boxplots and Creating a Multilevel X Axis

Introduction

Pandas is a powerful library for data manipulation and analysis in Python. One of its most useful visualization tools is the boxplot, which provides a compact representation of the distribution of a dataset. In this article, we will explore how to create a pandas boxplot with a multilevel x axis, where the climate types are grouped by soil types.

Problem Statement

The provided code snippet uses seaborn’s factorplot function to create a boxplot, but it does not handle the multilevel x-axis requirement. The resulting plot has overlapping x-axis labels and lacks the desired ordering of climates and soil types.

Solution Using Seaborn

Seaborn is a visualization library built on top of matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics. In this section, we will use seaborn’s factorplot function to create a boxplot with a multilevel x-axis.

import seaborn as sns
import matplotlib.pyplot as plt

# Load the data
cbg = pd.read_clipboard()
cbg.columns = ['Climate','Soil','Crop','irr']

# Define the order of the x-axis labels
x_order_soil = ['Zcg', 'Scg', 'Pcg']
col_order_climate = ['Temperate', 'Subtropical', 'Continental']

# Create the boxplot with a multilevel x-axis
sns.factorplot('Soil', x_order=x_order_soil,
               col='Climate', col_order=col_order_climate,
               row='Crop', y='irr', kind='box', data=cbg)

# Show the plot
plt.show()

Understanding Seaborn’s Factorplot Function

The factorplot function in seaborn allows us to create a boxplot with a multilevel x-axis. The main arguments of this function are:

• x: The column name of the categorical variable to use on the x-axis.
• x_order: A list of values that defines the order of the x-axis labels.
• col or column_order: The column names of the categorical variables to use for grouping the data.
• row: The column name of the categorical variable to use for labeling the rows.
• y: The column name of the numerical variable to plot.
• kind: The type of plot to create (in this case, a boxplot).

Handling Non-Alphabetical Order

When defining the x-axis labels using the x_order argument, we can specify values in any order. Seaborn will automatically sort them for us.

# Define the order of the x-axis labels
x_order_soil = ['Scg', 'Pcg', 'Zcg']

However, when defining the column labels using the col argument, we must specify values in alphabetical order if we want a non-alphabetical order on the x-axis.

# Define the order of the climate types for grouping
col_order_climate = ['Temperate', 'Subtropical', 'Continental']

Conclusion

In this article, we explored how to create a pandas boxplot with a multilevel x axis using seaborn’s factorplot function. By defining the order of the x-axis labels and column labels separately, we can achieve the desired ordering of climates and soil types while avoiding overlapping x-axis labels.

Last modified on 2024-01-18