The second great tool I would recommend for data analysis with Python is GGPlot.py. Any scientist who has experience in

Although the financial side of things is certainly not where most of my domain knowledge falls, Plot.ly has great support for several financial visualizations. This goes to show Plot.ly’s versatility as well, as visualizations rely both in and out of many scientist’s domain. Like everything in Plot.ly, financial charts are easy to use and beautiful — a while ago I worked on a project where we tracked the value of currencies and created a full web-app with an LSTM model that would retrain itself and predict new data based on what it had learnt. Plot.ly really came in handy with its easy to use and Javascript integrated visualizations for candlestick data in this circumstance.

To add to the unreasonable power of Plot.ly, Plot.ly also supports several different types of statistical plots. Furthermore, Plot.ly’s statistical plotting is incredibly mature and makes things like plotting distributions relatively simple and easy.

Thank you for reading! I hope you found this article both interesting and useful. Feel free to comment down below some of the similarities and differences you have found or experienced between Data Science and Business Analytics.

Of course, Python is also the most popular programming language used today for data science. While most scientists working with the language might be familiar with a lot of well-known and widely used packages such as Scipy, Sklearn, and Matplotlib, there are some packages which most data scientists have never even heard of that are also quite awesome!

The most popular general purpose programming language on planet Earth right now is the Python programming language. This is not only because Python is incredibly easy, and relatively fast, but also that Python has a killer ecosystem with tools to fit every discipline from business to finance and science. One area that this is certainly proven to be true is in the wonderful world of data science.

Plot.ly comes preloaded with all of the fantastic tools that your average data scientist or even just computer programmer might expect. Scatter plots, bar charts, and line charts are all staples of the Plot.ly module. While Matplotlib can accomplish similar goals, Plot.ly has the same functionality while also having default styling and Java-script interactivity that makes it a lot more fun and a lot easier to explore data. On top of that, presentations are certainly a thing that could be served a benefit from using Plot.ly over many of its competitors.

It is hard to argue with Plot.ly’s beautiful approach to maps, as well. Plot.ly’s clorepleths in particular are an absolute joy to use and can make compelling visualizations in a matter of seconds.

On top of the beautiful styling for basic plots, Plot.ly comes with a fully-featured 3D visualization system that rivals some of the best available with modern technology. One great advantage to the way that Plot.ly handles 3D is performance. Although 3D visualizations are of course quite complex and intensive, Plot.ly seems to handle a lot of these applications with relative ease. 3D visualizations are also awesome because the new axis allows for a greater amount of understanding by exploring data’s positional values in 3D space. Furthermore, the Z axis can also represent a variety of features — making it possible to view several different correlations at once.

One thing that has become surprising in the recent development of technology is geo-data. Geo-data has evolutionized with FIPS to such an extent primarily because of smart-phones and global positioning systems (GPS,) and this has given way to a strong foundation for data science to build on top of. This is of course because data is now more readily available than it ever has been for free with geo-data included.

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you’re scared of deep emotion. And so instead of reacting to things in a consistent way, you shove emotions down. Not just bad ones, like sadness or anxiety, but even happy ones, like joy or excitement. You use your own coping mechanisms — which can be alcohol, but also TV shows, social media, obsessions with exercise — to repress them. You feel like you don’t deserve the happy ones or like they may be taken away at any moment, and you can’t deal with the unhappy ones.

Another great thing about Plot.ly is that it is written in C. As a result, it uses the LLVM compiler libraries and is compatible with a whole array of programming languages with just a simple API. Not only is Plot.ly available for Python users, but also R users, C users, and any other language’s user base that is willing to implement it. There is even an implementation for the Julia language using the Plots.jl package.

On top of all of that, Plot.ly also has some lesser-known charts and graphs that you would be hard-pressed to find in most other data visualization packages. Funnel charts, pie charts, violin charts, and tree maps are just a few examples of some unique and fun ways to explore data using the Plot.ly library.

Thank you for reading! I hope you found this article both interesting and useful. Feel free to comment down below some of the similarities and differences you have found or experienced between Data Science and Business Analytics.

To start us off, I am going with a library for data visualization that is pretty well-known, but some might have never heard of. Plot.ly is a graphing library that takes interactivity to a whole new level. I would genuinely advise using Plot.ly over something like Matplotlib or Seaborn. This is because Plot.ly comes with a multitude of different tools that most scientists can certainly come to appreciate. Just how much is in Plot.ly?

The last great thing about Plot.ly is that it is open-source. While this isn’t as big of a benefit to some, being able to make changes if required or understand how code is being ran on your machine is always a plus. Being open-source software also means that Plot.ly can be used in practical business applications, making it valuable not only to those who program as a hobby, but also for real-world professionals.