Creating Scatter Plots with Multiple Colors and Shaded Backgrounds in Python Using Pandas and Matplotlib Libraries

Pandas Scatter Plot: Multiple Colors and Background

In this article, we will explore the creation of scatter plots using pandas and matplotlib libraries in Python. We will also discuss how to achieve multiple colors for plotting points above a certain threshold value. Additionally, we’ll delve into shading the background of the figure for specific indices.

Introduction

Scatter plots are an essential data visualization tool used to display the relationship between two variables. In this article, we will focus on creating scatter plots using pandas and matplotlib libraries in Python. We will explore how to create multiple colors for plotting points above a certain threshold value. Furthermore, we’ll discuss how to shade the background of the figure for specific indices.

Requirements

Python 3.x
Pandas library (pip install pandas)
Matplotlib library (pip install matplotlib)
NumPy library (pip install numpy)

Setting Up the Environment

Before starting, ensure you have installed necessary libraries. Create a new python file and import required libraries.

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

Creating DataFrames

Create dataframes from scratch or load existing datasets.

# create dataframe
data = {
    'scores': [10, 15, 7, 12, 20],
    'labels': [0, 1, 0, 1, 1],
    'indices': np.arange(len(data['scores']))
}
df = pd.DataFrame(data)

Scatter Plot with Multiple Colors

To create a scatter plot where points above a certain threshold value are colored red and the rest of the points are black, you can use the following approach.

# Define the threshold value
threshold_value = 15

# Create a mask to filter out values greater than or equal to threshold
mask = df['scores'] >= threshold_value

# Separate data into two lists for plotting
indices = df.loc[mask, 'indices']
fooIndices = df[~mask, 'indices']
fooScores = df[~mask, 'scores']

plt.figure(figsize=(8, 6))
plt.scatter(indices, df.loc[mask, 'scores'], c='r', marker='.', s=5, alpha=0.5)
plt.scatter(fooIndices, fooScores, c='b', marker='.', s=5, alpha=0.5)
plt.show()

Shading Background

To shade the background of a scatter plot for specific indices, you can use the fill_between function.

# Define labels and their corresponding indices
labels = df['labels']

# Create lists to store x-coordinates for shading
x1 = np.arange(len(labels))
x2 = np.arange(len(labels))

# Create lists to store y-coordinates for shading
y1 = [0] * len(labels)
y2 = [0] * len(labels)

# Shade the area between x-coordinates and y-coordinates using fill_between function
plt.fill_between(x1, y1, color='blue', alpha=0.3)
plt.fill_between(x2, y2, color='red', alpha=0.3)

# Create scatter plot with multiple colors
indices = df.loc[df['scores'] >= threshold_value, 'indices']
fooIndices = df[~df['labels'].isin(labels)]
fooScores = df[~df['scores'] >= threshold_value]['scores']

plt.figure(figsize=(8, 6))
plt.scatter(indices, df.loc[df['scores'] >= threshold_value, 'scores'], c='r', marker='.', s=5, alpha=0.5)
plt.scatter(fooIndices, fooScores, c='b', marker='.', s=5, alpha=0.5)

# Show plot
plt.show()

Conclusion

In this article, we have explored the creation of scatter plots using pandas and matplotlib libraries in Python. We discussed how to create multiple colors for plotting points above a certain threshold value and how to shade the background of the figure for specific indices.

References

Last modified on 2023-11-04