Merge and Join

Code

import pandas as pd

left = pd.DataFrame({"id": [1, 2, 3], "name": ["A", "B", "C"]})
right = pd.DataFrame({"id": [2, 3, 4], "score": [80, 90, 70]})

# Database-style joins on a key
inner = pd.merge(left, right, on="id", how="inner")
left_join = pd.merge(left, right, on="id", how="left")
outer = pd.merge(left, right, on="id", how="outer")

# Different key names
pd.merge(left, right, left_on="id", right_on="id", suffixes=("_l", "_r"))

# Concatenate along rows or columns
a = pd.DataFrame({"x": [1, 2]})
b = pd.DataFrame({"x": [3, 4]})
rows = pd.concat([a, b], ignore_index=True)
cols = pd.concat([a, b], axis=1)

print(inner, left_join, rows)

Explanation

merge() performs SQL-style joins keyed on one or more columns, with how controlling inner, outer, left, or right behavior. suffixes disambiguate overlapping non-key columns. concat() stacks frames along either axis, and ignore_index resets the row labels.

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