Import Data (Excel, CSV and API/JSON) with Pandas into Python
⌗ In this video on data analysis, you will learn how to import data from various file formats, using pandas, to verify filter and merge that data in your python code.
This help you to easily import and process data files in your code. Pandas introduce two new data structures to Python for this purpose.
A series, which is a one-dimensional array, similar to a column in a spreadsheet, and a dataframe which is a two-dimensional array made up of multiple series and looks very like a typical spreadsheet with rows and columns.
We’ll be working mostly with dataframes in this video
The thing that makes these structures so powerful in your code is the index object, which can be used to identify, filter and select entries with your code.
I’ll be working in PyCharm as usual but will be using the Python Console instead of the editor window. The code in the python console is interactive, meaning that you get immediate feedback as you type your commands. The console a great way to work with dataFrames because you can verify and view the data in real time.
Jupyter Notebook is another popular IDE among data scientists for doing this, but for the sake of consistency, we’ll use Pycharm. The console has everything we need for our data analysis and more.
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