Pandas interview questions (for data analyst):

What are the basic data structures in pandas?
How do you create a DataFrame in pandas?
How do you read a CSV file in pandas?
How can you select specific columns from a DataFrame in pandas?
How do you filter rows in a DataFrame based on a condition in pandas?
How do you handle missing values in a DataFrame using pandas?
How do you merge two DataFrames in pandas?
How do you perform groupby operation in pandas?
How do you rename columns in a DataFrame using pandas?
How do you sort a DataFrame by a specific column in pandas?
How do you aggregate data using pandas?
How do you apply a function to each element in a DataFrame in pandas?
How do you perform data visualization using pandas?
How do you handle duplicate data in a DataFrame using pandas?
How do you calculate descriptive statistics for a DataFrame using pandas?
How do you set the index of a DataFrame using pandas?
How do you reset the index of a DataFrame in pandas?
How do you concatenate multiple DataFrames in pandas?
How do you pivot a DataFrame in pandas?
How do you melt a DataFrame in pandas?
How do you calculate the correlation between columns in a DataFrame using pandas?
How do you handle outliers in a DataFrame using pandas?
How do you extract unique values from a column in a DataFrame using pandas?
How do you calculate cumulative sum in a DataFrame using pandas?
How do you convert data types of columns in a DataFrame using pandas?
How do you handle datetime data in a DataFrame using pandas?
How do you resample time-series data in pandas?
How do you merge and append DataFrames with different column names in pandas?
How do you handle multi-level indexing in pandas?
How do you drop columns from a DataFrame in pandas?
How do you create a pivot table in pandas?
How do you calculate rolling statistics in pandas?
How do you concatenate strings in a DataFrame column using pandas?
How do you create a cross-tabulation in pandas?
How do you handle categorical data in pandas?
How do you calculate cumulative percentage in a DataFrame column using pandas?
How do you handle data imputation in pandas?
How do you calculate percentage change in a DataFrame column using pandas?
How do you calculate the rank of values in a DataFrame column using pandas?
How do you calculate the difference between consecutive values in a DataFrame column using pandas?
How do you drop duplicate rows based on a specific column in pandas?
How do you calculate the mean, median, and mode of a DataFrame column using pandas?

I have curated the best interview resources to crack Python Interviews 👇👇
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this 👍❤️

🔟 Python resources to boost your resume 👇👇

https://whatsapp.com/channel/0029Vamhzk5JENy1Zg9KmO2g

If I were to learn Python for Data Analysis again I'd focus on:

- Python Programming fundamentals.

- Pandas, Numpy, and Matplotlib for data handling/visualisation.

- Seaborn for enhanced visualisation.

- Build projects with data from Kaggle/Google Datasets.

#python

Essential Python Concepts 👇👇
https://medium.com/@data_analyst/must-know-differences-in-python-with-real-examples-1224227f8d0b

Like for more ❤️

Official Python Docs
https://docs.python.org/3/

Tools:
https://docs.python-guide.org/en/latest/dev/virtualenvs/
https://www.pythonforbeginners.com/basics/python-pip-usage

Practice:
https://www.practicepython.org/
https://www.hackerrank.com
https://wiki.python.org/moin/PythonDecorators

Python GUI FAQ

https://docs.python.org/3/faq/gui.html

What Programming languages do you use on regular basis?

A study from 2018 with a 18,827 sample size voted Python (87%) as the top programming language for data analysis and data science, followed by SQL (44%) and R language (31%), respectively.

Do you think situation has changed by now?

Is Python Really Essential for Data Analysis as a Fresher?

Starting out in data analysis can be overwhelming, especially when everyone seems to say Python is a must-have. But here’s a fresher’s reality check: Python is not always required at the start!

💡 Why You Don’t Need to Worry About Python Right Away:
1️⃣ Excel, Power BI and SQL First! - Many entry-level roles prioritize skills in Excel and SQL. These tools alone can handle a lot of data tasks like cleaning, aggregating, and visualizing data.
2️⃣ Gradual Learning Path 📈 - Once you’re comfortable with the basics, Python is a powerful next step, especially for handling larger datasets or automating processes.
3️⃣ Value in Flexibility - Python’s libraries like Pandas and Matplotlib allow for more complex analysis, but they’re skills you can learn over time as you grow in your role.

🔑 Takeaway? Start with what’s essential—Excel, Power BI and SQL—and build your Python skills as you gain more experience.

Pandas basics to advanced.pdf

Python for Web3 and Smart Contracts Roadmap

Stage 1 – Python Basics (Syntax, OOP)
Stage 2 – Blockchain Fundamentals (Transactions, Ledgers)
Stage 3 – Web3(.)py and Ethereum Basics
Stage 4 – Smart Contracts with Solidity
Stage 5 – Decentralized Storage (IPFS)
Stage 6 – Integrate Wallets and MetaMask
Stage 7 – Decentralized Application (DApp) Development
Stage 8 – Deploy and Test Smart Contracts

🏆 – Python Web3 Developer

TOP 10 Python Concepts for Job Interview

1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming

2 Years of Python Experience in one article 👇👇
https://medium.com/@data_analyst/2-years-of-python-experience-in-one-article-71e855c143f3?sk=16e4684a4caea308f6cd08bca0a7dfde

⌨️ Data Types In NumPy

Many people pay too much to learn Python, but my mission is to break down barriers. I have shared complete learning series to learn Python from scratch.

Here are the links to the Python series

Complete Python Topics for Data Analyst: https://t.iss.one/sqlspecialist/548

Part-1: https://t.iss.one/sqlspecialist/562

Part-2: https://t.iss.one/sqlspecialist/564

Part-3: https://t.iss.one/sqlspecialist/565

Part-4: https://t.iss.one/sqlspecialist/566

Part-5: https://t.iss.one/sqlspecialist/568

Part-6: https://t.iss.one/sqlspecialist/570

Part-7: https://t.iss.one/sqlspecialist/571

Part-8: https://t.iss.one/sqlspecialist/572

Part-9: https://t.iss.one/sqlspecialist/578

Part-10: https://t.iss.one/sqlspecialist/577

Part-11: https://t.iss.one/sqlspecialist/578

Part-12:
https://t.iss.one/sqlspecialist/581

Part-13: https://t.iss.one/sqlspecialist/583

Part-14: https://t.iss.one/sqlspecialist/584

Part-15: https://t.iss.one/sqlspecialist/585

I saw a lot of big influencers copy pasting my content after removing the credits. It's absolutely fine for me as more people are getting free education because of my content.

But I will really appreciate if you share credits for the time and efforts I put in to create such valuable content. I hope you can understand.

You can refer these amazing resources for Python Interview Preparation.

Complete SQL Topics for Data Analysts: https://t.iss.one/sqlspecialist/523

Complete Power BI Topics for Data Analysts: https://t.iss.one/sqlspecialist/588

I'll continue with learning series on Excel & Tableau.

Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.

Hope it helps :)