Same questions, two languages. When to let the database do the work, when to pull data into Python, and how to stop downloading 40 million rows to compute one average.
Method chaining, query, assign, groupby with named aggregations and other small habits that turn messy notebooks into readable analysis.
Duplicates, missing values, five spellings of the same city and dates in three formats. The unglamorous work that decides whether your analysis is right.
Fancy algorithms get the headlines, but the features you give them decide most of the result. Practical examples with dates, ratios and categories.
No posts here yet.