How To Find The Start Time And End Time Of An Event In Python?

I have a data frame consists of column 1 i.e event and column 2 is Datetime: Sample data Event Time 0 2020-02-12 11:00:00 0 2020-02-12 11:30:00 2 2020-02-12 1

Solution 1:

Here is a method that can get the results without a for loop. I assume that the input data is read into a dataframe called df:

# Initialize the output df
dfout = pd.DataFrame()
dfout['Event'] = df['Event']
dfout['EventStartTime'] = df['Time']

Now, I create a variable called 'change' that tells you whether the event changed.

dfout['change'] = df['Event'].diff()

This is how dfout looks now:

EventEventStartTimechange002020-02-12 11:00:00     NaN102020-02-12 11:30:00     0.0222020-02-12 12:00:00     2.0312020-02-12 12:30:00    -1.0402020-02-12 13:00:00    -1.0502020-02-12 13:30:00     0.0602020-02-12 14:00:00     0.0712020-02-12 14:30:00     1.0802020-02-12 15:00:00    -1.0902020-02-12 15:30:00     0.0

Now, I go on to remove the rows where the event did not change:

dfout = dfout.loc[dfout['change'] !=0 ,:]

This will now leave me with rows where the event has changed.

Next, the event end time of the current event is the start time of the next event.

dfout['EventEndTime'] = dfout['EventStartTime'].shift(-1)

The dataframe looks like this:

EventEventStartTimechangeEventEndTime002020-02-12 11:00:00     NaN2020-02-12 12:00:00222020-02-12 12:00:00     2.02020-02-12 12:30:00312020-02-12 12:30:00    -1.02020-02-12 13:00:00402020-02-12 13:00:00    -1.02020-02-12 14:30:00712020-02-12 14:30:00     1.02020-02-12 15:00:00802020-02-12 15:00:00    -1.0NaN

You may chose to remove the 'change' column and also the last row if not needed.

Solution 2:

Assuming the dataframe is data:

current_event =Noneresult= []
for event, timein zip(data['Event'], data['Time']):
    if event != current_event:
        if current_event isnotNone:
            result.append([current_event, start_time, time])
        current_event, start_time = event, time
data = pandas.DataFrame(result, columns=['Event','EventStartTime','EventEndTime'])

The trick is to save your event number; if the next event number is not the same as the saved one, the saved one has to be ended and a new one started.

Solution 3:

Use group by and agg to get the output in desired format.

df =pd.DataFrame([['0',11],['1',12],['1',13],['0',15],['1',16],['3',11]],columns=['Event','Time'] )
df.groupby(['Event']).agg(['first','last']).rename(columns={'first':'start-event','last':'end-event'})

Output:

Event start-eventend-event011151121631111