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pythondataframesplitextract
Renaldo Moon
Renaldo Moon

Reputation: 165

Splitting/ Extracting part of Column in a Dataframe - python

I am trying to split/extract a portion of the "Time" column so it will only show the hours and minutes e.g. 18:15 as opposed to 18:15:34.

I've seen alot of examples online that use the .str.split() function with highlighting the colon as the delimiter. But that would split the Time column into three columns: hours, minutes, seconds.

Input Dataframe:

df = 

Index   Time
0       18:15:21
1       19:15:21
2       20:15:21
3       21:15:21
4       22:15:21

Output Dataframe

df = 

Index   Time
0       18:15
1       19:15
2       20:15
3       21:15
4       22:15

Thanks :)

Upvotes: 1

Views: 2609

Answers (3)

Karn Kumar
Karn Kumar

Reputation: 8816

You have fair choices here either replace , extract or split with pandas.series.str

First, this is just case based solution..

Below solution with which does replace the last two number along with : across Time column.

>>> df['Time'] = df['Time'].str.replace(':\d{2}$', '')
>>> df
    Time
0  18:15
1  19:15
2  20:15
3  21:15
4  22:15

Second approach with str.extract with regex..

>>> df['Time'] = df['Time'].str.extract('(\d{2}:\d{2})')
>>> df
    Time
0  18:15
1  19:15
2  20:15
3  21:15
4  22:15
  • \d{2} to hold initial two numbers
  • : next to match this immediately after first match
  • \d{2} again next two number followed by colon
  • $ asserts position at the end of a line

Upvotes: 1

John Zwinck
John Zwinck

Reputation: 249143

You can use a regex:

df.Time.str.replace(':\d\d$', '')

Or reverse-split:

df.Time.str.rsplit(':', 1).str[0]

Upvotes: 2

Sam Comber
Sam Comber

Reputation: 1293

You could use:

df['Time'].apply(lambda x : ':'.join(x.split(':')[0:2]))

Upvotes: 1

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