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12 Easy Steps to the Python Data Analysis, Beginners Guide
Why Learn Python for Data Analysis?My name is Paulius. I have been working as Business & Data Analyst for multiple years in various international organisations. The amount of data these organisations are facing increases exponentially. So, I have decided that I need to know how to analyse, process and transform large sets of data. I could no longer entirely rely on Excel. It would crash anytime the data size grows larger. Then, why Learn Python For Data Analysis? Well, Python is excellent for beginners because it has a simple syntax. Therefore, you will be quick to write programmes, make meaningful analysis, get those insights you need and start having some fun. Plus, Python has an extensive collection of libraries such as pandas, NumPy or matplotlib. They include tools that allow you to pull in powerful functionality like complex data analysis, machine learning and visualisations into your programs. In some cases, you will need only a single line of code. One essential aspect of Python is a large community of users who are willing to help. It is crazy, what obscure data analysis problems I was able to solve using their assistants. Plus, the biggest companies like Google, Dropbox, Reddit and Instagram are using Python as well and with a good reason. Course Prepared Using My ExperienceThree years ago, I started my journey in learning Python. Picking up multiple tutorials and even building a fully functional online store. However, I have found that tutors in those courses almost always assume some level of programming experience. Even when the level is identified as a beginner, they would either not explain some concepts or start with detail explanations but by the end of the course, begin skipping. I believe this is because they learned basics some time ago and forgot what it takes and what would be unclear for a beginner. Hence, I would have to watch multiple video courses to gain a suitable basis for picking up more complex libraries. For example, simple question how exactly index works in lists. Some reason courses I have seen would not dive into detail explanation, and I would have to find answers in online forums.I have decided enough is enough, I need to help others, who want to learn data analysis with Python and want to do it smartly. Thus, I have created a Python Beginners Course to expedite your learning and generate value faster by going straight to the point of learning Python for Data Analysis. Through the course, I include my tips & tricks as well as lessons learned. After you complete the course, you will be ready and equipped to handle more complicated libraries like pandas and know with confidence how Python works. Do not need to create appsOk, you have decided to go with Python. But how to be smart about learning it? Various courses teach you basics that apply to the development of apps. Yet, when you analyse data, you may not need all that functionality. Say, take my personal experience, I frequently need to create a one-off project with insights for my management. I would need to take several sets of data, transform and clean it. Then I would prepare insights reports or visualisations. But that does not require creating an app with complex functionality, error handling pr complicated UI. Concentrate on what you needTherefore, for data analysis, creating fully completed apps could become a distraction. Even though you may use some of the other complex capabilities of Python in the future, it is not a requirement to start doing data analysis. Ultimately, you will realise that there is so much functionality available for Python that you cannot learn everything. You will need to find a balance. If your goal is to analyse data, you should go more in-depth in data specific libraries and not try to learn a bit of every single library available for Python. Future TrainingWhy should you care about pandas, I hear you ask? Pandas is a genuine workhorse for data analysis. It allows you to analyse, transform, clean data and do much more in python. It is a fast, powerful, flexible and easy to use open-source data analysis and manipulation tool, built on top of the Python programming language. If you want to be great at data analysis pandas is what you need. I have tried to include all the required basics in the course for you to be ready to handle pandas. So, let’s start! So, brew a nice cup of coffee, get some desserts and dig into Python Beginners Guide To The Data Analysis Galaxy Volume 1.Enjoy and do not forget to have some fun! Exercise Files: Downloadable content as part of Introduction. Included Final Class File in each video so you can easily follow videos. Also, the same exercises available after each training video.
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