#  Load necessary libraries
import matplotlib.pyplot as plt
import seaborn as sns

# Data
samples = ['S1', 'S2', 'S3', 'S4', 'S5']
Percentage = [55, 70, 43, 78, 23]

# Generate distinct colors for each bar
colors = sns.color_palette("husl", len(samples))

# Create bar plot
plt.figure(figsize=(8, 5))
plt.bar(samples, Percentage, color=colors, edgecolor='black')

# Labels and title
plt.xlabel("Studied plants")
plt.ylabel("Polyphenols Content (%)")
plt.title("Total Polyphenols Percentages Among Studied Plants")
# Show plot
plt.show()

# Load necessary libraries
import matplotlib.pyplot as plt
import seaborn as sns

# Data
Drugs = ['D1', 'D2', 'D3', 'D4', 'D5']
Contamination = [55, 12, 18, 10, 5]

# Generate distinct colors
colors = sns.color_palette("pastel", len(Drugs))

# Create pie chart
plt.figure(figsize=(7, 7))
plt.pie(Contamination, labels=Drugs, autopct='%1.1f%%', colors=['#FF5733', '#33FF57', '#3357FF', '#F4C542', '#A833FF'], startangle=120, 
wedgeprops={'edgecolor': 'black', 'linewidth': 1})

# Add title
plt.title("Total Contamination Percentage Among Evaluated Drugs")

# Show plot
plt.show()