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. Introduction
If you start your data analyst career in Excel, raise your hand. Yes, me too. Excel is a powerful tool for data analysis and imagination. And you know it. Let’s have an Excel joke for another article. However, despite the improvement in handling major datases, there is a point where Excel begins to fall down.
At this point, you can think, “Ah, Excel screw, I should have learned.” You can still do. Û” These stages are reflected, think about Azgar as a natural expansion of your abilities.
. Step 1: Excel skill map for Azigar’s equals
Some Excel skills are able to transfer, though it is a programming language. You can think of it as “Excel without a grid”, as many functions make maps between the two tools. Here are some examples.
Although you still have to learn the basic principles of syntax and language, you are not starting from the beginning – you already understand the job analytics. Now it is about to do what you already do in Excel.
. Step 2: Learn the basic principles of Azigar
Before starting coding, familiarize yourself with the basic principles of language. I recommend to start with it:
- Basic syrup
- Variables, Types of dataFor, for, for,. LocksConditional
- Lists And Racing (They are similar to the designated range or folklore table)
- Functions of reusing the code (they are like reusable formulas in Excel)
Here are some resources to start you:
. Step 3: Set up your environment
You do not need a complicated environment. Install if you want to keep it locally Aneconda. It comes with azagar and key libraries that you need at the beginning (PandasFor, for, for,. nUmpyAnd Metaplatlib) It also includes Jupyter notebook; Think of it as a workbook where you write codes and text notes.
You can make it even easier. If you have a google account, you can use Coer. This jeepter is a Google version of the notebook and comes with more libraries than Anakonda.
. Step 4: Start with Pandas
Azagar is famous for his ecosystem, rich in libraries that enhance its capabilities. Is one of them PandasA library that is developed for data analysis and manipulation. In the data analysis, it is so common that it is practically not separate from itself. Once you start learning, you also learn Panda. Some things that you should follow are:
- Create Data frames From Excel or CSV files
- Filtering, sorting, merging, collecting
- Creating your Excel workflows: Axis tables, search, conditional calculations
Generally, try to translate whatever you do in Excel into the Code.
Once you get the hang of pandas start using nUmpyA library for numerical computing that reduces pandas.
. Step 5: Exercise on real data
The fastest way to learn. There are many options. You can solve Analytical questions on Stratscichch And Late code And practice the real interview questions. You find the problem of solving the data and the problem. All of you have to write a solution in Azar.
The second option is to use the available datases and solve the issues you think. There are some great dataset sources Kagal DatasisFor, for, for,. Data.govAnd Great public datasis.
If you need some suggestions for solutions to solutions, start with:
- Data cleaning (duplication, standardizing dates, filling lost values)
- Make easy reports you usually do in Excel
. Step 6: Start imagining data
The next step is to start to look at your analysis. An excellent start is that you already have to regenerate the chart in Excel. There are two most famous data vessels in the libraries:
- Metaplatlib – for basic plots (line, bars, scattered)
- Marine – With the minimum code of modern concepts.
. Step 7: Combine Excel and Azigar
You do not need to give up Excel. Even if you wanted, you couldn’t do because most of your surrounding stakeholders are Married to Excel.
The ideal combination is to use Open Pix Or xlwings Write back to Excel files. In other words, the heavy lifting in the background, but the last output goes to Excel for stakeholders. There is no need to stay there. Currently, Microsoft is testing it New Coopelot () Function This allows you to use AI in Excel.
. Conclusion
As you can see, the transfer from Excel to Azgar does not mean that you are starting to zero. If you analyze data in Excel, it already means that you have some basic knowledge. You know your data analysis. The only thing is to transfer this knowledge into programming language and make it more technically sophisticated.
Follow the steps of this article, and your transfer will be far more smooth than you think.
Net Razii A data is in a scientist and product strategy. He is also an affiliated professor of Teaching Analytics, and is the founder of Stratskrich, a platform that helps data scientists prepare for his interview with the real questions of high companies. The net carrier writes on the latest trends in the market, gives interview advice, sharing data science projects, and everything covers SQL.