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Test case variables

print(f"input_vars: {input_vars}")
print(f"original_input_vars: {original_input_vars}")
print(f"returned_output_vars: {returned_output_vars}")
print(f"true_output_vars: {true_output_vars}")

Python Dictionary

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Notes on AI Fundamentals

Let us start by creating some experiences

https://platform.openai.com/chat/edit?models=gpt-5.4

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Renaming Columns & DataFrames in Pandas

---

1. Rename Specific Columns — rename()

import pandas as pd

df = pd.DataFrame({

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Changing Data Types with astype() in Pandas

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WHY IT MATTERS

Pandas often reads data with wrong types — numbers as strings, booleans as objects, categories as plain strings. Wrong types cause silent errors in math, filtering, and groupby operations.

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.apply() with a Function in Pandas

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WHY IT MATTERS

apply() lets you run any Python function row-by-row or column-by-column. Use it when built-in pandas methods aren't enough — custom logic, multi-column calculations, or complex transformations.

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Creating New Columns & Selecting Specific Columns in Pandas

---

SETUP

import pandas as pd
import numpy as np

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Boolean Filters and Masks in Pandas

---

SETUP

import pandas as pd
import numpy as np

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Merges / Joins in Pandas

---

SETUP

import pandas as pd

students = pd.DataFrame({

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SQLite CASE Statements, Aggregation & GROUP BY

---

SETUP — Table Used

-- Preview what we're working with
SELECT * FROM netflix_titles LIMIT 5;
PRAGMA table_info(netflix_titles);

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Number Operations — COUNT, SUM, ROUND in SQLite

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SETUP — Table Used

SELECT * FROM netflix_titles LIMIT 5;
PRAGMA table_info(netflix_titles);