Python Pandas & Matplotlib: Creating Parallel Coordinates Plots with Data Visualization

Python Pandas & Matplotlib: Creating Parallel Coordinates Plots with Data Visualization

This code demonstrates how to create a parallel coordinates plot using Python's Pandas and Matplotlib libraries, visualizing data from an Excel spreadsheet.

import pandas as pd
import matplotlib.pyplot as plt

# Read data from Excel file
data = pd.read_csv(r'D:\Echarts\Hollywood Movie Dataset\Most Profitable Hollywood Stories - US 2011.csv')
data = data.astype(str)

# Create parallel coordinates plot
pd.plotting.parallel_coordinates(data, 'Genre')

# Add title and axis labels
plt.title('Parallel Coordinates Plot')
plt.xlabel('Features')
plt.ylabel('Values')
plt.xticks(rotation=90)

# Display the plot
plt.show()

Addressing Large Datasets in the Y-Axis:

If the data on the y-axis is overwhelming, you can try these solutions:

• Data Sampling or Filtering: Select a subset of data to visualize, focusing on specific ranges or representative samples.
• Y-Axis Scaling or Grouping: Adjust the scale of the y-axis or group data points into categories for clearer representation.
• Plot Size and Tick Interval Adjustments: Increase the plot size or adjust the tick interval on the y-axis for improved readability.

This guide provides a basic foundation for creating parallel coordinates plots. Experiment with different data sets, visualization parameters, and techniques to tailor the plots to your specific needs and data characteristics.