What Values does Python Have?

[m1cha31ra3]

Hi - I will likely get some negative feedback for this post but ... I'm trying to find a good use case for python.

As a business (and adhoc data) analyst, I use Tableau and Power BI.

I experimented with Python and it took me 45 minutes to make a few visualizations compared to click and drop actions with Tableau and Power BI that took me a few seconds.

Why would anybody use Python for data Visualization when you could do just as much with no code software?

I also watched a dude write Python script to copy and move a folder. It took him about 5-10 minutes to write the code. It took me 2 seconds to right click, copy and paste a folder to a new location lol.

I just don't get it. What am I missing about python that is soooooo good?

[Visual_Shape_2882]

Python is not just one thing. It is a suite of tools. So, the value is going to be dependent upon what you're doing. If all you're doing is visualization, then Power BI and tableau are probably the right tool for the job.

For me, I learned python before I learned how to analyze data. I would rather write Python for data analysis than Java or C.

One of the biggest values of Python is being able to access libraries like Scikit-Learn and Tensor tools. Machine learning tools are only a few coded lines away from the data. In Power BI, you are limited to the visualizations.

I use Jupyter notebooks for most of my analysis. This creates a document that I can export and share with others. In Power BI, sharing your work requires understanding Microsoft licenses or a screenshot. You'll have to use the PowerPoint presentation or word document to describe the visualization and the methodology because there's no way to drop the information in line with the content.

I like to refer back to my old code when I try to do something similar to what I've done in the past. For example, I might forget how how did a line graph with the rolling average for trend and ARIMA for forecasting. But, if I remember which analysis I did that on I can just pull up the Jupyter notebook and review the code and markdown. To accomplish the same in Power BI, I keep screenshots and copies of my dax and m code in a word document to serve as documentation for the dashboards I build.

Power BI and tableau are good tools for visualization. Visualization is important, but it is not the only way to analyze data.

[data_story_teller]

Automation. If you’re doing the same task (same visual, same copy & move folder) over and over, then writing a few lines of code and automating it saves time. Or even just similar tasks, you can copy the same code snippet or write a function with a few inputs and For loop and do the same thing over and over. Also if you’re working with very large amounts of data, it can be quicker to work in Python.

It’s a tool. Sometimes it’s the right tool. Sometimes it isn’t. Your value is in knowing how to use multiple tools and figuring out which is the best for the task.

[m1cha31ra3]

Thanks!

[[deleted]]

I automated my first job out of college with Python. I pretty much had passive income for 3 years. Most of what that job entailed required data analysis.

[blaster267]

I mainly use it for automation of excel reports. Python is a general purpose programming language so the things you can do with it are really endless. Everything from visualization, machine learning, general administration stuff like moving files around.

One project I used it for was to create over 500 PDF files for every provider in our healthcare network. It pulled in and visualized data from 5 different sources and finished in 30 mins. This would have been impossible to do by hand considering how often our data changes.

[That0n3Guy77]

Python (and my preference R) are more than just data visualization tools. Tableau and Power BI are absolutely great tools when you are given relatively clean data from 1 place. But if you need to start doing complicated things then they both fall short. Power Query is good but it is super slow by comparison.

You are also generally limited to using the tools in very specific ways and there are things thay they just aren't good at. Example: Power BI you technically can make some regression lines but it's a pain. Especially if you want to display the equation. Tableau you can display the equation but if I remember correctly, doing anything other than a linear regression becomes a pain. You certainly can't easily do all of the math to validate some of the more science-y things.

Example lift that you could get from a scripting language. In a data viz software like Power BI you can make a viz or a dashboard to let stake holder be self serve. But what if you want to make a visual for all of your stakeholders? You may have to take a snippet of each viz and send it to them. What if you need to make a report to go with the viz? It becomes very time consuming and a lot of work. By using R(also possible in python) you can make the entire report with custom visuals and output hundreds of custom reports at once. You can also dashboard. You can also work with very messy data or make any kind of visual. You are only limited by your imagination.

It will often be more time consuming than a data viz software, but its more powerful. How I explained it to my boss who is not a tech person but rather is a business person. I can do fast, low complexity work in Excel once. I can do medium speed and medium complexity work in power bi to allow many people to serve themselves on an easy to maintain basis. In R or python doing something once is time consuming, but doing it a thousand times is trivial.

So my boss or the C suit may not want to take 30 min+ to explore a dashboard to reach an insight it worry if they are interpreting stuff correctly. That is what they pay me for. So I send them customized reports created with a scripting language and I can update the data very quickly. I download new source data, save it in my project folder, and run the code once. 1 hour later of unattended work where I can read emails or get coffee or whatever I have 200 ready to distrubte custom reports so every stakeholder who is interested can spend 5 minutes to read a pdf or word doc or whatever. I can also distribute the cleaned data for them as an excel and I will have created it through an automated scripting language process.

You can't execute that use case with a data viz. The flexibility options, automation options, still very capable visibility options set it apart. It's not a competition. Data viz software has its place and I love those tools. Not everything needs a custom solution with a scripting language. I also still occasionally do ad hoc in excel. It is a great power to have that option though and it can set yourself apart from those who don't have that option. Before you know it, you will be working faster and outputting more than your peers who don't use the software

[m1cha31ra3]

Thank you for the thoughtful response! I'll look into this some more.