Today we will run through a few experiments to work with data
We will be using a library created by bnia among others
Lets start from where we left off last time
https://seaborn.pydata.org/examples/horizontal_boxplot.html
What we want is 1 record for every year and every CSA as a column. To do this, transpose the dataset. Set the CSA labels (first row) as our columns, relabel the index (for clarity) and cast our datatypes.
What we want is 1 record for every year and every CSA as a column. To do this, transpose the dataset. Set the CSA labels (first row) as our columns, relabel the index (for clarity) and cast our datatypes.
We want to create a linear regression for each CSA using {X: year, Y: value} for a given indicator
We may need to normalize the data for this to be useable
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.hist.html