🎗 Join function in pandas 🎗

DataFrame — join() function

3 min readApr 18, 2022

🎗 The join() function is used to join columns of another DataFrame.

🎗 Join columns with other DataFrame either on index or on a key column. Efficiently join multiple DataFrame objects by index at once by passing a list.

Syntax:

DataFrame.join(self, other, on=None, how='left', lsuffix='', rsuffix='', sort=False)

Parameters:

🎗 other

🎗 on

🎗 how

🎗 lsuffix

🎗 rsuffix

🎗 sort

☝🏻other

→ Index should be similar to one of the columns in this one.

→ If a Series is passed, its name attribute must be set, and that will be used as the column name in the resulting joined DataFrame.

Type/Default Value

DataFrame, Series, or list of DataFrame

🤞🏻On

→ Column or index level name(s) in the caller to join on the index in other, otherwise joins index-on-index.

→ If multiple values given, the other DataFrame must have a MultiIndex.

→ Can pass an array as the join key if it is not already contained in the calling DataFrame. Like an Excel VLOOKUP operation.

Type/Default Value

str, list of str, or array-like

👌🏻how

→ How to handle the operation of the two objects.

left: use calling frame’s index (or column if on is specified)
right: use other’s index.
outer: form union of calling frame’s index (or column if on is specified) with other’s index, and sort it. lexicographically.
inner: form intersection of calling frame’s index (or column if on is specified) with other’s index, preserving the order of the calling’s one.