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Here's how to actually use AI for data science, not the toy version where you paste your data into a chatbot and hope the answer's right. Working in a Jupyter notebook in PyCharm, the Codex agent handles the data cleaning, but here's the trap with notebook data work: broken code doesn't crash. It runs fine and quietly hands you a wrong number.
So instead of printing head and squinting at five rows, I check the DataFrame viewer and Jupyter variable window to see every column, its data type, null counts, and distribution in one glance. That's how I caught a column that came back as a string when it should have been a number.
The AI transformation ran without a single error, but the data was wrong, and every calculation after it would have been wrong too. Speed up the transformation with AI, then validate the result before you trust it.
#techwithtim #python #ai #programming
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2026/07/21
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