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Sample CSV File can be viewed here

What I have: My python code does the checking for work duration based on the Current Values. 

import csv
from datetime import date,time,datetime 
import pandas as pd
import matplotlib.pyplot as plt

def print_output(df):
    worktime = len(df.loc[df['AC_Input_Current'] >= 4.9])
    noworktime = len(df) - worktime

    print ('Daily record: \n')
    print ('Start: ', df.index.min(), ' - ', 'End:', df.index.max())
    print ('%.2f' %(worktime/60),'[in Mins]',' or ','%.2f' %(worktime/3600),'[Hrs]',' of work') 
    print ('%.2f' %(noworktime/60),'[in Mins]',' or ','%.2f' %(noworktime/3600),'[Hrs]',' of no work done')
    print ('Total duration recorded: ','%.2f' %((noworktime + worktime)/60),'[Mins]',' or ','%.2f' %((noworktime + worktime)/3600),'[Hrs]\n')

dateparse = lambda x: pd.datetime.strptime(x, '%d/%m/%Y %H:%M:%S')

Data = pd.read_csv('MainD2.csv', parse_dates=['Time_Stamp'], date_parser = dateparse, index_col='Time_Stamp')


Data.resample('D').apply(lambda x: print_output(x))

The results are below after running the codes: The result I have for the duration in mins is what I want to adjust a little but I'm not sure how. For example: the first result from below starts from 2017-06-21 01:09:21 to 2017-06-21 23:15:04

What I want to get but do not know how to: - For e.g. based on the first result; Instead of getting the 1 result from the whole timeline of the day from 01:09:21 to 23:15:04, I need to get the results from 08:00:00 to 12:30:00,12:31:00 to 13:12:00,13:12:01 to 18:30:00,19:30:00 to 23:59:59 - If there is no values from 00:00:00 to 01:09:20, ignore them and continue getting results based on the time that is wanted ( above statement ).

Start:  2017-06-21 01:09:21  -  End: 2017-06-21 23:15:04
43.75 [in Mins]  or  0.73 [Hrs]  of work
161.63 [in Mins]  or  2.69 [Hrs]  of no work done
Total duration recorded:  205.38 [Mins]  or  3.42 [Hrs]

Start:  2017-06-22 00:38:54  -  End: 2017-06-22 05:47:29
30.25 [in Mins]  or  0.50 [Hrs]  of work
271.40 [in Mins]  or  4.52 [Hrs]  of no work done
Total duration recorded:  301.65 [Mins]  or  5.03 [Hrs]

Start:  2017-06-23 00:39:50  -  End: 2017-06-23 23:10:15
44.23 [in Mins]  or  0.74 [Hrs]  of work
263.35 [in Mins]  or  4.39 [Hrs]  of no work done
Total duration recorded:  307.58 [Mins]  or  5.13 [Hrs]

Start:  2017-06-24 00:38:10  -  End: 2017-06-24 13:33:49
77.83 [in Mins]  or  1.30 [Hrs]  of work
120.00 [in Mins]  or  2.00 [Hrs]  of no work done
Total duration recorded:  197.83 [Mins]  or  3.30 [Hrs]

Start:  2017-06-25 09:54:25  -  End: 2017-06-25 20:16:05
75.62 [in Mins]  or  1.26 [Hrs]  of work
131.28 [in Mins]  or  2.19 [Hrs]  of no work done
Total duration recorded:  206.90 [Mins]  or  3.45 [Hrs]

Start:  2017-06-26 00:51:32  -  End: 2017-06-26 01:05:55
9.18 [in Mins]  or  0.15 [Hrs]  of work
4.92 [in Mins]  or  0.08 [Hrs]  of no work done
Total duration recorded:  14.10 [Mins]  or  0.23 [Hrs]
Sancta Ignis
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1 Answers1

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Since you're using datetime, it appears this solution should work for you:

https://stackoverflow.com/a/35203658/2805387

e.g.

df[(df['date']>datetime.date(year=2017,month=6,day=24,hour=8,min=0)) & (df['date']<datetime.date(year=2017,month=6,day=24,hour=12,min=30))]

df[(df['date']>datetime.date(year=2017,month=6,day=24,hour=12,min=31)) & (df['date']<datetime.date(year=2017,month=6,day=24,hour=13,min=12))]

and so on, for all your required ranges

Note that in that answer the column for the date in the dataframe is simply 'date', if your date column has a different name you will have to use that name instead of course.

fullStackChris
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