Today, I practiced using CSS locators to extract data from websites, not just clicking around, but pinpointing exactly what I want from a forest of HTML tags.
I practiced using classes and IDs to extract contents from Selectors.
It felt like telling a website: "Look, I know you're busy, but show me exactly what I asked for." And it listened. Beautiful !
I also looked into Normal distribution using Python and explored business-like questions such as:
How many sales deals can Amir expect per week?
What's the least number of deals Amir is likely to close in the bottom 25% of weeks?
I used tools like: scipy.stats.norm(), mean and standard deviation, to visualize and understand real-life randomness in measurable ways.
If I Had to Show You Exactly What I Did Today…
Here are 4 visuals that capture my day:
A website's HTML tree showing how CSS selectors navigate the structure
A highlighted CSS selector pinpointing one tiny piece of data
A Normal distribution curve for sales deals
Python code calculating probabilities
Together, these visuals show what I actually do on this journey.
Every dataset tells a story.
Every selector reveals a clue.
Every distribution explains a pattern.
And I'm enjoying the process way more than I expected.
Still learning.
Still building.
Still curious.
And still very much in love with the journey.
-SP
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