When creating software, application designers must make a number of choices. Among them is what language to use for the user interface? When onboarding new customers, we always make the Customer First.
Install numpy, matplotlib, pandas, pandas-datareader, quandl, and sklearn Need help installing packages with pip? Pandas is a Python module, and Python is the programming language that we're going to use. The Pandas module is a high performance, highly efficient, and high level data analysis library.
At its core, it is very much like operating a headless version of a spreadsheet, like Excel. Most of the datasets you work with will be what are called dataframes.
You may be familiar with this term already, it is used across other languages, but, if not, a dataframe is most often just like a spreadsheet. Columns and rows, that's all there is to it!
From here, we can utilize Pandas to perform operations on our data sets at lightning speeds. Pandas is also compatible with many of the other data analysis libraries, like Scikit-Learn for machine learning, Matplotlib for Graphing, NumPy, since it uses NumPy, and more.
It's incredibly powerful and valuable to know. If you're someone who finds themselves using Excel, or general spreadsheets, for various computational tasks, where they might take a minute, or an hour, to run, Pandas is going to change your life.
I've even seen versions of Machine learning like K-Means clustering being done on Excel.
That's really cool, but my Python is going to do that for you way faster, which will also allow you to be a bit more stringent on parameters, have larger datasets and just plain get more done. Another bit of good news? You can easily load in, and output out in the xls or xlsx format quickly, so, even if your boss wants to view things the old way, they can.
Pandas is also compatible with text files, csv, hdf files, xml, html, and more with its incredibly powerful IO. If you're just now joining us with Python, you should be able to follow along without already having mastered Python, and this could even be your intro to Python in general.
Most importantly, if you have questions, ask them! If you seek out answers for each of the areas of confusion, and do this for everything, eventually you will have a full picture.
Most of your questions will be Google-able as well. Don't be afraid to Google your questions, it wont laugh at you, I promise. I still Google a lot of my goals to see if someone has some example code doing what I want to do, so don't feel like a noob just because you do it.
If I have not sold you yet on Pandas, the elevator pitch is: Assuming you've got Python installed. Next, go to your terminal or cmd. Did you get a "pip is not a recognized command" or something similar?
No problem, this means pip is not on your PATH.busy thinking about lightning and its effects. Furthermore, I would especially like to thank Riduan Ahmed, Mona Riza, Pasan Hettiarachchi, and Muzafar Ismail for providing helpful feedback on the draft version of this book.
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