performing multiple string operations on a pandas Series/DataFrame

Question

I would like to perform several operations on a particular Series. Is there a way to chain them without continually writing .str? ie if my series is called s and i want to do

s.str.replace("hi", "bye").str.strip().str.lower()

Is that the right way to do things? Seems verbose relative to R so I thought maybe there was a better syntax for this.

piRSquared · Accepted Answer · 2018-05-23 17:38:22Z

2

comprehension

Yes (sorta). Use a comprehension

[x.replace('hi', 'bye').strip().lower() for x in s]

Wrap that up into a series again.

pd.Series([x.replace('hi', 'bye').strip().lower() for x in s], s.index)

`map`

s.map(lambda x: x.replace('hi', 'bye').strip().lower())

answered May 23, 2018 at 17:38

piRSquared

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4 Comments

user2285236 Over a year ago

It's also worth mentioning that vectorized string operations don't always outperform regular Python loops. Even when they do, the difference is not that much. Pandas handles labels/NaNs for you though.

Alex Over a year ago

@piRSquared side q: when you iterate over s in the list comp, the iterator returns each row one at a time?

piRSquared Over a year ago

The way you wrote s implies that it is a Series. In that case, yes, the comprehension iterates one element of the series' values at a time.

MSS Over a year ago

@piRSquared I am late but is there more efficient way to do the same ?

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