I have the following dataframe (df):
SERV_OR_IOR_ID IMP_START_TIME IMP_CLR_TIME IMP_START_TIME_BIN IMP_CLR_TIME_BIN
0 -1447310116 23:59:00 00:11:00 47 0
1 1673545041 00:00:00 00:01:00 0 0
2 -743717696 23:59:00 00:00:00 47 0
3 58641876 04:01:00 09:02:00 8 18
I want to duplicate the rows for which IMP_START_TIME_BIN is less than IMP_CLR_TIME_BIN as many times as the absolute difference of IMP_START_TIME_BIN and IMP_CLR_TIME_BIN and then append (at the end of the data frame) or preferable append below that row while incrementing the value of IMP_START_TIME_BIN.
For example, for row 3, the difference is 10 and thus I should append 10 rows in the data frame incrementing the value in the IMP_START_TIME_BIN from 8(excluding) to 18(including).
The result should look like this:
SERV_OR_IOR_ID IMP_START_TIME IMP_CLR_TIME IMP_START_TIME_BIN IMP_CLR_TIME_BIN
0 -1447310116 23:59:00 00:11:00 47 0
1 1673545041 00:00:00 00:01:00 0 0
2 -743717696 23:59:00 00:00:00 47 0
3 58641876 04:01:00 09:02:00 8 18
4 58641876 04:01:00 09:02:00 9 18
... ... ... ... ... ...
13 58641876 04:01:00 09:02:00 18 18
For this I tried to do the following but it didn't work :
for i in range(len(df)):
if df.ix[i,3] < df.ix[i,4]:
for j in range(df.ix[i,3]+1, df.ix[i,4]+1):
df = df.append((df.set_value(i,'IMP_START_TIME_BIN',j))*abs(df.ix[i,3] - df.ix[i,4]))
How can I do it ?
You can use this solution, only necessary index values has to be unique:
#first filter only values for repeating
l = df['IMP_CLR_TIME_BIN'] - df['IMP_START_TIME_BIN']
l = l[l > 0]
print (l)
3 10
dtype: int64
#repeat rows by repeating index values
df1 = df.loc[np.repeat(l.index.values,l.values)].copy()
#add counter to column IMP_START_TIME_BIN
#better explanation http://stackoverflow.com/a/43518733/2901002
a = pd.Series(df1.index == df1.index.to_series().shift())
b = a.cumsum()
a = b.sub(b.mask(a).ffill().fillna(0).astype(int)).add(1)
df1['IMP_START_TIME_BIN'] = df1['IMP_START_TIME_BIN'] + a.values
#append to original df, if necessary sort
df = df.append(df1, ignore_index=True).sort_values('SERV_OR_IOR_ID')
print (df)
SERV_OR_IOR_ID IMP_START_TIME IMP_CLR_TIME IMP_START_TIME_BIN \
0 -1447310116 23:59:00 00:11:00 47
1 1673545041 00:00:00 00:01:00 0
2 -743717696 23:59:00 00:00:00 47
3 58641876 04:01:00 09:02:00 8
4 58641876 04:01:00 09:02:00 9
5 58641876 04:01:00 09:02:00 10
6 58641876 04:01:00 09:02:00 11
7 58641876 04:01:00 09:02:00 12
8 58641876 04:01:00 09:02:00 13
9 58641876 04:01:00 09:02:00 14
10 58641876 04:01:00 09:02:00 15
11 58641876 04:01:00 09:02:00 16
12 58641876 04:01:00 09:02:00 17
13 58641876 04:01:00 09:02:00 18
IMP_CLR_TIME_BIN
0 0
1 0
2 0
3 18
4 18
5 18
6 18
7 18
8 18
9 18
10 18
11 18
12 18
13 18