Task_1.py

import pandas as pd
import matplotlib.pyplot as plt

# Create dataset
data = {
    "Name": ["Utkarsh", "Riya", "Tushar", "Ananya", "Om", "Isha", "Sahil", "Neha", "Umesh", "Simran"],
    "Age": [18, 23, 18, 24, 19, 21, 19, 23, 20, 22],
    "Gender": ["Male", "Female", "Male", "Female", "Male", "Female", "Male", "Female", "Male", "Female"]
}

df = pd.DataFrame(data)
print("Dataset:\n", df)

# ---------- Gender Distribution ----------
plt.figure(figsize=(6, 5))
gender_counts = df["Gender"].value_counts()

plt.bar(gender_counts.index, gender_counts.values, color=['skyblue', 'lightcoral'], edgecolor="black")

# Add labels above bars
for i, v in enumerate(gender_counts.values):
    plt.text(i, v + 0.05, str(v), ha='center', fontweight='bold')

plt.title("Gender Distribution - Created by Kunal", fontsize=14, fontweight='bold')
plt.xlabel("Gender")
plt.ylabel("Count")
plt.show()

# ---------- Age Distribution ----------
plt.figure(figsize=(7, 5))
plt.style.use('ggplot')  # different style

plt.hist(df["Age"], bins=6, color="mediumseagreen", edgecolor="black")

# Add mean line
mean_age = df["Age"].mean()
plt.axvline(mean_age, color='red', linestyle='dashed', linewidth=2, label=f'Mean Age: {mean_age:.1f}')
plt.legend()

plt.title("Age Distribution - Created by Kunal", fontsize=14, fontweight='bold')
plt.xlabel("Age")
plt.ylabel("Frequency")
plt.show()