Load data from CSV, Excel, JSON, and SQL databases and save results with read_csv, read_sql, to_csv.
Loading Data into Pandas
import pandas as pd
# CSV
df = pd.read_csv('data.csv')
df = pd.read_csv('data.csv', index_col='id', parse_dates=['created_at'])
df = pd.read_csv('data.csv', dtype={'price': float}, nrows=1000)
# Excel
df = pd.read_excel('data.xlsx', sheet_name='Sales')
# JSON
df = pd.read_json('data.json')
df = pd.read_json('https://api.example.com/data')
# SQL
import sqlalchemy
engine = sqlalchemy.create_engine('mysql+pymysql://user:pass@host/db')
df = pd.read_sql('SELECT * FROM orders WHERE status = %s', engine, params=['paid'])
df = pd.read_sql_table('users', engine)
# Save
df.to_csv('output.csv', index=False)
df.to_excel('output.xlsx', index=False)
df.to_json('output.json', orient='records')