Reading and Inspecting Data with pandas

What is pandas?

pandas is a Python library for working with labelled tabular data.

Reading data from different sources:

Example

import pandas as pd
df = pd.read_csv('sales.csv')
print(df.head()) # first 5 rows
print(df.shape) # (rows, columns)
df.info() # prints directly; wrapping it in print() also outputs "None"

How it works

These checks help you understand the dataset before analysing it.

Other useful checks

Common mistakes

• Assuming correct types:
  • Dates often load as text (object). Use parse_dates=['order_date'] in read_csv or pd.to_datetime().
  • Numbers with commas or currency symbols ('₹1,200') load as text and need cleaning.
• Only looking at head()****: problems often sit further down the file.
• Wrong delimiter or encoding: use sep=';' or encoding='utf-8' / 'latin-1' if the file looks garbled.