Daily Post #4 - 6/11/2024

Howdy!

I think I'm fully embracing the aggie in me. It's probably scaring my UT friends a little bit but that's the price they pay for going to UT.

Anyways, today I dedicated more of my time to learning SAS, but I made a mistake in that I started writing this post after I finished my work, so I can't fully recall each and every single one of the commands I did. This may be a good oppurtunity to review however....

I learned how to do more if then statements in SAS, as well as learning more about the data step.

data <name of new data set>;
	set <data set you want to take values from>;
	keep <whatever columns you want to keep>
	<new variable column that requires formula>= <column>*<column or number>
	if <old variable>=<specific value 1> then <new column>=<value you want>
	else if <old variable>=<value 1> then do <whatever command you want>;
	else if <old variable>=<value2> then do <whatever command you want>;
 end;
else if <old variable>=<specific value 2> then do <whatever command you want>;
	else if <old variable>=<value 1> then do <whatever command you want>;
	else if <old variable>=<value2> then do <whatever command you want>;
 end;
run;

The nested if then loops were fun to do. You only use the nested if then loops when you want multiple commands to happen in the first if then statement as SAS can't recognize two commands in one line and sees it as a syntax error. Something I'm continuing to see as I learn more programming is how easy the logic is, but how difficult it can be to apply that logic. I spent a majority of my time just practicing and debugging which was quite nice. Once I'm finished with this course, I'm going to continue to use these commands to clean data. I should be starting sooner, but I don't have as much time as I want and I think it would be more prudent to learn it all before I start so progress on those data cleaning projects will be faster.

I wanted to learn more Python today, but I wasn't able to learn as much as I wanted to. I did some quick learning on random forests and learned about it's use as a model.

from sklearn.ensemble import RandomForestRegressor

model=RandomForestRegressor()

I need to do more practice on this topic, but I at least wanted to see it in action. Tomorrow, I'll dedicate more time to learning about these methods and whether all of these ML algorithms are functions in Python. If so, then learning the code would be easy, while learning the methodology would be where I would spend most of my time.

I also didn't get a chance to read through the statistics textbook, so I'll have to do some of that in the morning tomorrow.

Goals for tomorrow:

Read the statistics textbook and answer problems

Continue learning SAS and learn more about making reports themselves

Learn more Python with list comprehension and dictionary comprehension

Continue learning from Kaggle and work to submit to a competition