python - Filtering out csv rows by column data -

python - Filtering out csv rows by column data -

i'm not sure how phone call have csv data:

...|address | date |... ...|abraham st.| 01/01/2008 |... ...|abraham st.| 02/02/2007 |... ...|abraham st.| 03/03/2011|...

so want maintain newest entry(in case row4), i'm having problem bending mind around this.

my initial thought read info csv list of rows , then:

to convert date strings datetime object and go through every row, it's name , comparing every other row find highest date , save date's row.

is there improve way approach this?

just utilize max builtin key function extracts , converts date field datetime object. assume dates mm/dd/yyyy.

import csv datetime import datetime date_column = 1 open('input.csv') f: reader = csv.reader(f, delimiter='|') next(reader) # skip on csv header row most_recent = max(reader, key=lambda x : datetime.strptime(x[date_column].strip(), '%d/%m/%y')) >>> print most_recent ['abraham st.', ' 03/03/2011']

i think intent grouping "address" column , select recent date "date" column, in case can utilize itertools.groupby() this:

import csv itertools import groupby datetime import datetime address_column = 0 date_column = 1 most_recent = [] open('input.csv') f: reader = csv.reader(f, delimiter='|') next(reader) # skip on csv header row k, g in groupby(sorted(reader), lambda x : x[address_column]): most_recent.append(max(g, key=lambda x : datetime.strptime(x[date_column].strip(), '%d/%m/%y'))) >>> print most_recent [['abraham st.', ' 03/03/2011'], ['moses rd.', ' 10/12/2013'], ['smith st.', ' 01/01/1999']]

assuming input.csv contains this:

address |date abraham st.| 01/01/2008 abraham st.| 02/02/2007 abraham st.| 03/03/2011 moses rd.| 10/12/2013 moses rd.| 11/11/2011 smith st.| 01/01/1999

python csv filter