The 3 Steps to Start Learning Python for Data Analysis

Data analytics has been as crossword puzzles for different companies. It required a different technique and skills to solve this puzzle. Simply data analytics is extracting data from different sources and categorizing it in a meaningful format. Analyzed data can enhance the productivity and business gain for any business. It becomes an essential task for any successful business.

There are different ways to analyze data. Big projects require an advanced approach to preparing huge data for analysis, conduct simple statistical analyses, perform meaningful data visualization, and take crucial decisions based on analyzed data. All of this can be done using Python which is one of the most important requirements for the data scientist to have. According to TIOBE Index, Python is one of the top 5 popular programming languages of 2019. In this article, I will explain in a simple way how to learn Python to analyze data.

  • Learn Python principles

Before you start writing an advanced Python command to analyze data, the first thing you need to know is the Python programming fundamentals. There a lot of online courses you can take to learn Python such as DataCamp. Simultaneously you need to download Jupyter Notebook to start implementing what you have learned. Python is not like other languages, Python’s syntax is human readable and much easier to learn it than other languages.

  • Build small projects 

You can’t learn Python if you do not write the code by yourself. Practicing is an essential step after you learn the Python principles. Building small projects like a program that brings the climate from Google in your city, or time series analysis datasets will help in learning Python and solve challenges.

  • Explore Python Libraries

Python library is a group of methods and functions that you can use to execute many actions without writing code. For data, the best libraries you can use are pandas, numpy, Matplotlib and scipy. Pandas and numpy provide you with amazing tools to work with data in multiple dimensions, and when it comes to data visualization Matplotlib is the best. Those libraries can do a lot of functions and ease your life in terms of data transformation.

Congratulations, you are now a Python data analyst! (joke). This is only a guide for beginners and remember that practice makes perfect. Follow us for more articles on how to learn Python for data analysis.  If you have any questions you can drop us a message on the below channels. Wishing you a successful journey!