Do you want to learn python development but lack prior programming experience? Are you still confused about what all you need to learn about python development?

No need to think more as we’ve got the perfect answer for you!

The Starting Process

To being with Python development, you need to learn five Python libraries. This will effectively solve a broad set of data analysis issues and will help you to be able to efficiently perform data analysis.

Steps to Learn Python Development for Efficient Data Analysis

Pick Specified Python Learning Resources

The first important step is to pick specific python learning resources and avoid considering generic ones. There are numerous excellent Python online courses and books. You need to pick one that focuses more on performing data analysis using Python.

Pick books that are geared towards numerous topics that are mathematical – oriented and about statistics and data analysis. Don’t waste your time by taking generic online courses or going through books, which are meant for general audience.

The Learning Pathway

You need to start with the code academy and complete all exercises mentioned there. You can complete these exercises investing time every day. This will help you know in detail about basic Python concepts.

Once you complete this, then you need to go through I Python notebook. This will cover topics not mentioned in the code academy and help you start with learning Python libraries.

Learning Numpy Tutorial

You can start with Numpy fundamental package for scientific computing with Python. A better understanding of this will help you use tools such as Pandas more effectively.

You need to explore the basic concepts of Numpy. Its tutorial illustrates most frequently performed Numpy operations like indexing, working with N-dimensional, slicing of arrays, data processing with arrays, using integer arrays, universal functions, various statistical methods, and more.

Learning Pandas Basic Tutorial

Pandas include a high level of data manipulation and structure tools that can make data analysis an easy and fast process in Python.

The Panda tutorials include working with data frames, series, missing values, dropping entries from an axis, and more.

Learning Matplotlib

It is a 4 part tutorial.

  • The first part introduces the basic functionalities and figures types of Matlpotlib.
  • The second part tells you the ways to control the color and style of a figure, like line patterns, line thickness, markers and using color maps.
  • Part 3 of Matplotlib is about annotation of a figure including numerous figures, controlling the axis range, coordinate system, and aspect ratio.
  • The 4th part talks about various complex figures.


A common mistake that you can make while learning Python is attempting to learn numerous libraries at the same time. This can make things confusing and the overall process frustrating and challenging.

So, focus on one step at a time and soon you will learn python development needed for data analysis. If still you have queries, just ask me!