Updated Pie Chart

import pandas as pd
import matplotlib.pyplot as plt

# Replace 'Line Plot.csv' with the actual CSV file path
df = pd.read_csv('Line Plot.csv')

# Extract data from the DataFrame
values1 = df['Raw Reads']
values2 = df['Trimmed Reads']
values3 = df['Aligned Reads']
values4 = df['Deduplicated Reads']
values5 = df['Stitched Reads']

# Calculate the total sum of values for each read type
total_values1 = values1.sum()
total_values2 = values2.sum()
total_values3 = values3.sum()
total_values4 = values4.sum()
total_values5 = values5.sum()

# Data for the pie chart
data = [total_values1, total_values2, total_values3, total_values4, total_values5]
labels = ['Raw Reads', 'Trimmed Reads', 'Aligned Reads', 'Deduplicated Reads', 'Stitched Reads']
colors = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0']
explode = (0.05, 0.05, 0.05, 0.05, 0.05)  # To explode a slice

# Create a pie chart with improved aesthetics
plt.figure(figsize=(8, 8))
plt.pie(data, labels=labels, autopct='%1.1f%%', startangle=140, colors=colors, pctdistance=0.85, explode=explode)

# Draw a circle in the center to make it a donut chart (optional)
center_circle = plt.Circle((0, 0), 0.70, fc='white')
fig = plt.gcf()
fig.gca().add_artist(center_circle)

# Customize the plot
plt.title('Distribution of Reads', fontsize=16, fontweight='bold')
plt.axis('equal')  # Equal aspect ratio ensures that the pie chart is circular
plt.legend(labels, loc='upper right', bbox_to_anchor=(0.85, 1))

# Move the legend to the left-hand side
plt.legend(labels, loc='upper left', bbox_to_anchor=(-0.25, 0.9))

# Show the plot
plt.tight_layout()
plt.show()