Datetime comparisons in python

问题

I have a file with two different dates: one has a timestamp and one does not. I need to read the file, disregard the timestamp, and compare the two dates. If the two dates are the same then I need to spit it to the output file and disregard any other rows. I'm having trouble knowing if I should be using a datetime function on the input and formatting the date there and then simply seeing if the two are equivalent? Or should I be using a timedelta?

I've tried a couple different ways but haven't had success.

df = pd.read_csv("File.csv", dtype={'DATETIMESTAMP': np.datetime64, 'DATE':np.datetime64})

Gives me : TypeError: the dtype < M8 is not supported for parsing, pass this column using parse_dates instead

I've also tried to just remove the timestamp and then compare, but the strings end up with different date formats and that doesn't work either.

df['RemoveTimestamp'] = df['DATETIMESTAMP'].apply(lambda x: x[:10])
df = df[df['RemoveTimestamp'] == df['DATE']]

Any guidance appreciated.

Here is my sample input CSV file:

"DATE", "DATETIMESTAMP"

"8/6/2014","2014-08-06T10:18:38.000Z"
"1/15/2013","2013-01-15T08:57:38.000Z"
"3/7/2013","2013-03-07T16:57:18.000Z"
"12/4/2012","2012-12-04T10:59:37.000Z"
"5/6/2014","2014-05-06T11:07:46.000Z"
"2/13/2013","2013-02-13T15:51:42.000Z"

回答1:

import pandas as pd
import numpy as np


# your data, both columns are in string
# ================================================
df = pd.read_csv('sample_data.csv')

df

        DATE             DATETIMESTAMP
0   8/6/2014  2014-08-06T10:18:38.000Z
1  1/15/2013  2013-01-15T08:57:38.000Z
2   3/7/2013  2013-03-07T16:57:18.000Z
3  12/4/2012  2012-12-04T10:59:37.000Z
4   5/6/2014  2014-05-06T11:07:46.000Z
5  2/13/2013  2013-02-13T15:51:42.000Z


# processing
# =================================================
# convert string to datetime
df['DATE'] = pd.to_datetime(df['DATE'])
df['DATETIMESTAMP'] = pd.to_datetime(df['DATETIMESTAMP'])

# cast timestamp to date
df['DATETIMESTAMP'] = df['DATETIMESTAMP'].values.astype('<M8[D]')

        DATE DATETIMESTAMP
0 2014-08-06    2014-08-06
1 2013-01-15    2013-01-15
2 2013-03-07    2013-03-07
3 2012-12-04    2012-12-04
4 2014-05-06    2014-05-06
5 2013-02-13    2013-02-13


# compare
df['DATE'] == df['DATETIMESTAMP']

0    True
1    True
2    True
3    True
4    True
5    True
dtype: bool

回答2:

How about:

import time
filename = dates.csv
with open(filename) as f:
    contents = f.readlines()

for i in contents:
    date1, date2 = i.split(',')
    date1 = date1.strip('"')
    date2 = date2.split('T')[0].strip('"')
    date1a = time.strftime("%Y-%m-%d",time.strptime(date1, "%m/%d/%Y"))
    print i if date1a == date2 else None

来源：https://stackoverflow.com/questions/31577280/datetime-comparisons-in-python

标签

python

numpy

pandas