Manipulate time-range in a pandas Dataframe

问题

Need to clean up a csv import, which gives me a range of times (in string form). Code is at bottom; I currently use regular expressions and replace() on the df to convert other chars. Just not sure how to:

select the current 24 hour format numbers and add :00
how to select the 12 hour format numbers and make them 24 hour.

Input (from csv import):

   break_notes
0        15-18
1  18.30-19.00
2      4PM-5PM
3          3-4
4     4-4.10PM
5      15 - 17
6      11 - 13

So far I have got it to look like (remove spaces, AM/PM, replace dot with colon):

   break_notes
0          15-18
1    18:30-19:00
2            4-5
3            3-4
4         4-4:10
5          15-17
6          11-13

However, I would like it to look like this ('HH:MM-HH:MM' format):

   break_notes
0    15:00-18:00
1    18:30-19:00
2    16:00-17:00
3    15:00-16:00
4    16:00-16:10
5    15:00-17:00
6    11:00-13:00

My code is:

data = pd.read_csv('test.csv')
data.break_notes = data.break_notes.str.replace(r'([P].|[ ])', '').str.strip()
data.break_notes = data.break_notes.str.replace(r'([.])', ':').str.strip()

回答1:

Here is the converter function that you need based on your requested input data. convert_entry takes complete value entry, splits it on a dash, and passes its result to convert_single, since both halfs of one entry can be converted individually. After each conversion, it merges them with a dash.

convert_single uses regex to search for important parts in the time string. It starts with a some numbers \d+ (representing the hours), then optionally a dot or a colon and some more number [.:]?(\d+)? (representing the minutes). And after that optionally AM or PM (AM|PM)? (only PM is relevant in this case)

import re


def convert_single(s):
    m = re.search(pattern="(\d+)[.:]?(\d+)?(AM|PM)?", string=s)
    hours = m.group(1)
    minutes = m.group(2) or "00"
    if m.group(3) == "PM":
        hours = str(int(hours) + 12)
    return hours.zfill(2) + ":" + minutes.zfill(2)


def convert_entry(value):
    start, end = value.split("-")
    start = convert_single(start)
    end = convert_single(end)
    return "-".join((start, end))


values = ["15-18", "18.30-19.00", "4PM-5PM", "3-4", "4-4.10PM", "15 - 17", "11 - 13"]

for value in values:
    cvalue = convert_entry(value)
    print(cvalue)

来源：https://stackoverflow.com/questions/57127264/manipulate-time-range-in-a-pandas-dataframe

标签

python

python-3.x

pandas

dataframe

date-range