How should I select rows of a pandas dataframe whose entries start with a certain string?

Question

Apologies if this is contained in a previous answer but I've read this one: How to select rows from a DataFrame based on column values? and can't work out how to do what I need to do:

Suppose have some pandas dataframe X and one of the columns is 'timestamp'. The entries are formatted like '2010-11-03 09:44:05'. I want to select just those rows that correspond to a specific day, for example, select just those rows for which the actual string in timestamp column starts with '2010-11-03'. Is there a neat way to do this? Can I do it with a mask or Boolean indexing? Or should I just write a separate line to peel off the day from each entry and then select the rows? Bear in mind the dataframe is large if it helps.

i.e. I want to write something like

X.loc[X['timestamp'].startswith('2010-11-03')]

or

mask = '2010-11-03' in X["timestamp"]

but these don't actually make any sense.

What makes you think it does not make any sense ?

sushanth
– sushanth

2020-06-12 16:53:12 +00:00
Commented Jun 12, 2020 at 16:53 — sushanth
– sushanth, Commented Jun 12, 2020 at 16:53

Dhaval Taunk · Accepted Answer · 2020-06-12 16:22:11Z

1

This should work:-

X[X['timestamp'].str.startswith('2010-11-03')]

answered Jun 12, 2020 at 16:22

Dhaval Taunk

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1 Comment

SBK Over a year ago

This seems to be exactly what I was missing; thank you

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