Why can't I index row by datetime index in pandas?

Question

I can't seem to index rows using datetime index with pandas. Information on my dataframe shows that the index is datetimeindex:

<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 223 entries, 2013-10-29 to 2017-05-29
Data columns (total 6 columns):
Unnamed: 0    223 non-null float64
company       223 non-null object
date          223 non-null object
date_conv     223 non-null object
text          223 non-null object
title         223 non-null object
dtypes: float64(1), object(5)
memory usage: 17.2+ KB

But when I do this it returns 'key error'

df['2017-02-04']

Should I have index series name as "index" to make this work? Although the my df is using datetimeindex, the column name of the index is not 'index' it's 'date_conv'.

use df.loc['2017-02-04']

run-out
– run-out

2019-03-28 19:09:02 +00:00
Commented Mar 28, 2019 at 19:09 — run-out
– run-out, Commented Mar 28, 2019 at 19:09
@run-out Ok, that worked! thank you

Asteroid098
– Asteroid098

2019-03-28 19:09:47 +00:00
Commented Mar 28, 2019 at 19:09 — Asteroid098
– Asteroid098, Commented Mar 28, 2019 at 19:09

Poe Dator · Accepted Answer · 2019-12-10 19:52:30Z

1

In your example '2017-02-04' is string. You have to refer to the row by datetime:

df.loc[datetime.datetime.strptime('2017-2-4', '%Y-%m-%d'),:]

answered Dec 10, 2019 at 19:52

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Comments

Jpsy · Accepted Answer · 2022-11-01 10:09:25Z

0

You CAN use a string to address a row in a DataFrame, but you need to do it using the loc property:

df_row = df.loc['2017-02-04']

answered Nov 1, 2022 at 10:09

Jpsy

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