Excel, JSON & SQL

Reading Excel, JSON & SQL

CSV files are great, but they're not the only game in town. Let me show you how to read other formats — because let's be honest, not everything lives in a CSV.

Reading Excel Files

Yes, you can read Excel files directly with Pandas. No more copy-pasting from spreadsheets:

import pandas as pd

df = pd.read_excel('data.xlsx', sheet_name='Sheet1')
print(df.head())
    

You might need to install openpyxl first: `pip install openpyxl`. The `sheet_name` parameter lets you pick which sheet to read. You can even pass a list of sheet names to read multiple sheets at once.

Reading JSON

JSON is everywhere — APIs, config files, web data. Pandas handles it beautifully:

df = pd.read_json('data.json')
print(df.head())
    

Reading from SQL

If you work with databases, this one's for you:

import sqlite3

conn = sqlite3.connect('database.db')
df = pd.read_sql('SELECT * FROM users', conn)
print(df.head())
    

Think of it like this — Pandas is a universal translator for data. CSV, Excel, JSON, SQL — it reads them all and gives you the same familiar DataFrame to work with.

Key Takeaways

• `pd.read_excel()` reads Excel files (needs openpyxl installed)
• `pd.read_json()` reads JSON files directly
• `pd.read_sql()` reads from SQL databases using a connection
• All these methods return the same DataFrame format