clumpy | create or transform numpy images from the command line | Machine Learning library

I'd like to filter an array of objects based on multiple tests. For this example, I want to filter an array of objects if the values for the keys aren't null, and that one value for one key is less than 90. I'm currently doing this with a for loop like so:

I'm currently attempting to read a file, pass the contents and multiple arrays to the function; see if any of it matches using regex and then replace & finally update.

The code I've put together which looks ugly and clumpy is this:

Thanks for taking a look at my question. I have created a script using BeautifulSoup and Pandas which scrapes data on projections from the Federal Reserve's website. The projections come out once a quarter (~ 3 mos.). I'd like to write a script which creates a daily time series and checks the Federal Reserve website once a day, and if there has been a new projection posted, the script would add that to the time series. If there has not been an update, then the script would just append the time series with the last valid, updated projection.

From my initial digging, it seems there are outside sources I can use to "trigger" the script daily, but I would prefer to keep everything purely python.

The code I have written to accomplish the scraping is as so:

I have two corresponding lists:

I have a dictionary stat of size 3 x 5 (three variables a, b and c with five data points each) and get the following output using print(stat):