How do I learn data analysis with Python?

Here are some tips on how to learn data analysis with Python:

1. Learn the basics of Python. This includes learning about variables, data types, functions, loops, and conditional statements. There are many online resources and tutorials that can help you learn the basics of Python.
2. Learn about data analysis libraries in Python. There are many popular data analysis libraries in Python, such as NumPy, Pandas, Matplotlib, and Seaborn. These libraries can be used to perform a variety of data analysis tasks, such as data cleaning, data wrangling, data visualization, and machine learning.
3. Practice data analysis with real-world datasets. The best way to learn data analysis is to practice with real-world datasets. There are many datasets available online that you can use to practice data analysis.
4. Contribute to open source data analysis projects. Contributing to open source data analysis projects is a great way to learn from other data analysts and get feedback on your work. There are many open source data analysis projects on GitHub that you can contribute to.
5. Attend data analysis meetups and conferences. Attending data analysis meetups and conferences is a great way to learn about new data analysis techniques and meet other data analysts.

With time and effort, you can learn data analysis with Python and become a proficient data analyst.

Here are some additional resources that you may find helpful:

• Python for Data Analysis: This book by Wes McKinney is a great resource for learning data analysis with Python.
• Data Analysis with Python: This course by Coursera is a great introduction to data analysis with Python.
• Dataquest: This online learning platform offers courses on data analysis with Python.
• Kaggle: This website hosts data science competitions that you can participate in to practice your data analysis skills.

You can learn data analytics with python using various libraries specifically built to support data processing and analysis. The most important aspect of data analysis is how you put the data to the code and what you expect as an outcome. Rest everything is achievable and will motivate you to excel in this field.