Types of Charts

Types of Charts in Data Science #

Charts help visualize data for better understanding, pattern detection, and decision making.

Line Chart #

• Purpose: Show trends over time
• Example: Stock prices over months
• Tools: Python (matplotlib), Excel
• Code Example:

import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [10,20,15,25]
plt.plot(x, y)
plt.title("Line Chart Example")
plt.show()

Bar Chart #

• Purpose: Compare categories
• Example: Sales of different products
• Tools: Python (matplotlib), Excel
• Code Example:

x = ['A','B','C']
y = [10,20,15]
plt.bar(x, y)
plt.title("Bar Chart Example")
plt.show()

Pie Chart #

• Purpose: Show proportions of a whole
• Example: Market share of companies
• Tools: Python (matplotlib), Excel
• Code Example:

labels = ['X','Y','Z']
sizes = [30,50,20]
plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.title("Pie Chart Example")
plt.show()

Histogram #

• Purpose: Show distribution of data
• Example: Age distribution of customers
• Tools: Python (matplotlib), Excel
• Code Example:

data = [22,25,22,30,28,30,25]
plt.hist(data, bins=5)
plt.title("Histogram Example")
plt.show()

Scatter Plot #

• Purpose: Show relationship between two variables
• Example: Height vs Weight
• Tools: Python (matplotlib, seaborn), Excel
• Code Example:

x = [1,2,3,4]
y = [10,20,15,25]
plt.scatter(x, y)
plt.title("Scatter Plot Example")
plt.show()