Reading Data

Lesson in the Python for Data Analysis Roadmap · Stage 7: Reading Local Files

Last updated 14 September 2026

What is Reading Data?

Pandas provides functions to load data from many formats: pd.read_csv(), pd.read_excel(), pd.read_json(), pd.read_parquet(), pd.read_sql(), and others. Each function returns a DataFrame and accepts parameters for handling headers, delimiters, encoding, and data types. Reading data is always the first step in a Pandas workflow.

Study this in the interactive course See the whole Python for Data Analysis roadmap

Free resources to learn Reading Data

Official docsHow do I read and write tabular data?
ArticlePandas 101: How to Read Data from Multiple Sources
VideoReading in Files in Pandas | Python Pandas Tutorials

Reading Data: common questions

Can I learn Reading Data in Hindi?

This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Reading Data in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.

Is this Reading Data tutorial for beginners?

It is lesson 53 of 112 in the free Python for Data Analysis roadmap, in stage 7, Reading Local Files. If you are new to Python for Data Analysis, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.