Importing and Exporting Files in Python

Real datasets rarely start out as Python code - they usually live in files such as CSV, Excel, or JSON. Pandas provides simple, consistent functions for reading these files into a DataFrame and writing a DataFrame back out.

Reading a CSV File

import pandas as pd

df = pd.read_csv("students.csv")
print(df.head())   # first 5 rows

Reading Excel and JSON Files

df_excel = pd.read_excel("students.xlsx", sheet_name="Sheet1")
df_json = pd.read_json("students.json")

Useful Arguments While Reading

df = pd.read_csv(
    "students.csv",
    usecols=["Name", "Score"],   # only load specific columns
    index_col="Name",             # use a column as the index
    nrows=100                     # read only the first 100 rows
)

Exporting a DataFrame

df.to_csv("output.csv", index=False)
df.to_excel("output.xlsx", index=False)
df.to_json("output.json", orient="records")

Passing index=False while exporting is a habit worth building early - without it, Pandas writes the DataFrame's row index as an extra unwanted column in your output file.

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