~/learn/Pandas · Merging & reshaping
Merging and reshaping
Joins, pivots and melts.
9 min readlesson 5 of 13mergepivot_tablemelt
why this matters
Your data rarely lives in one file. merge joins tables the same way SQL JOIN does.
merge is the pandas join: name the key and the kind of join you want. left keeps every row on the left, inner keeps only matches.
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pivot_table reshapes long data into a matrix, aggregating duplicates as it goes.
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melt does the reverse, turning wide columns back into rows.
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Watch the row count
Check row counts before and after a merge. If it grows unexpectedly, your key has duplicates.
key takeaways
- pd.merge(a, b, on="key") joins tables.
- how="left" keeps all rows from a.
- concat stacks tables on top of each other.
check your understanding
What's the SQL equivalent of pd.merge(orders, customers, on="customer", how="left")?
free practice
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