reading notes for code fellows
Pandas is a framework that is easily as important as NumPy, and it will be a great asset for data analysis going forward.
Pandas is a library with tools for data analysis data science and machine learning. Pandas structures your data into dataframes. You can get rid of some parts of data using .drop(. Ifyou use value_counts() you can take that data and make it into a bargraph. You can use mean() to get the mean of data and compare the average data between sections. .plot() will give you a graph of your data. If you have a date time index, you can sort it by year. Joining dataframes will change how they are plotted to be readable between the two.
Pandas has some similarity to the uses of the external graphing library we were using in javascript, but with the added benefit of also being able to move around and change the data all within itself.