Date,Activity,Duration,Mood
2024-09-13,Work,3,5
2024-09-13,Exercise,1,4
2024-09-16,Work,3,4
2024-09-16,Exercise,1,5

import pandas as pd
import matplotlib.pyplot as plt

# Load the data
data = pd.DataFrame({
    'Date': ['2024-09-13', '2024-09-13', '2024-09-16', '2024-09-16'],
    'Activity': ['Work', 'Exercise', 'Work', 'Exercise'],
    'Duration': [3, 1, 3, 1],
    'Mood': [5, 4, 4, 5]
})

# Convert 'Date' column to datetime format
data['Date'] = pd.to_datetime(data['Date'])

# Display the first few rows of the dataset
print("Data Overview:")
print(data)

# Basic Statistics
print("\nBasic Statistics:")
print(data.describe(include='all'))

# Additional Statistics
mean_duration = data['Duration'].mean()
median_mood = data['Mood'].median()
print(f"\nAverage Duration: {mean_duration:.2f}")
print(f"Median Mood: {median_mood:.2f}")

# Plot Duration Over Time using Matplotlib
plt.figure(figsize=(12, 6))
for activity in data['Activity'].unique():
    subset = data[data['Activity'] == activity]
    plt.plot(subset['Date'], subset['Duration'], marker='o', linestyle='-', label=activity)
plt.title('Daily Duration of Activities')
plt.xlabel('Date')
plt.ylabel('Duration (hours)')
plt.legend(title='Activity')
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Histogram of Mood Ratings using Matplotlib
plt.figure(figsize=(8, 6))
plt.hist(data['Mood'], bins=5, color='skyblue', edgecolor='black')
plt.title('Distribution of Mood Ratings')
plt.xlabel('Mood Rating')
plt.ylabel('Frequency')
plt.show()