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NumPy and Pandas Basics

Learning Objectives

• Compute mean, median, standard deviation, and variance using NumPy.
• Create DataFrames from list and dictionary.
• Access rows/columns with loc and iloc.

Example

import numpy as np
import pandas as pd

arr = np.array([72, 85, 90, 68, 85])
print(np.mean(arr), np.median(arr), np.std(arr), np.var(arr))

data = {"name": ["Asha", "Ravi"], "marks": [88, 92]}
df = pd.DataFrame(data)
print(df.loc[0])
print(df.iloc[:, 1])

Dry Run

• NumPy computes numeric summaries quickly.
• loc uses labels, iloc uses positions.

Common Mistakes

• Mixing label index and integer index in selection.
• Forgetting to install/import required libraries.

Practice

1. Read a CSV and print top 5 rows.
2. Filter students with marks > 80.