I'm trying to sum the duration of the activities using a for loop with conditions.
mydf= {'Duration' : [14, 8, 6, 36, 12, 5, 3, 2, 4, 5, 8, 3, 14, 1, 27, 25, 117, 2, 962, 2, 2, 1],
'Activity': ['Groom', 'Pause', 'Groom', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Sleep', 'Awaken', 'Groom', 'Pause', 'Groom', 'Eat', 'Cuddle', 'Come down', 'Dig', 'Forage']}
df = pd.DataFrame(mydf)
I want to sum all the sleep duration together.
I tried:
Sleep_sum = [sum(df['Duration'] for i in df['Activity'] if [i+1]=='Sleep')]
but this gives me an error : TypeError: can only concatenate str (not "int") to str.
I also tried this:
for i in range of len(df):
df['Activity'][i] == 'Sleep'
if [i] = [i+1]
df['Duration'].sum()
Essentially, I need to sum the duration of 'Sleep" if it's followed by another row == "Sleep".
Thank you for your time!
You can create virtual groups to group consecutive activities (Sleep and other):
out = (df.groupby(df['Activity'].ne(df['Activity'].shift()).cumsum(), as_index=False)
.agg({'Duration': 'sum', 'Activity': 'first'}))
print(out)
# Output
Duration Activity
0 14 Groom
1 8 Pause
2 6 Groom
3 92 Sleep
4 1 Awaken
5 27 Groom
6 25 Pause
7 117 Groom
8 2 Eat
9 962 Cuddle
10 2 Come down
11 2 Dig
12 1 Forage
Update
Just for Sleep activity:
m = df['Activity'] == 'Sleep'
sleep = (df.reset_index(drop=False)[m]
.groupby(df['Activity'].ne(df['Activity'].shift()).cumsum())
.agg({'index': 'first', 'Duration': 'sum', 'Activity': 'first'})
.set_index('index'))
out = pd.concat([df[~m], sleep]).sort_index()
print(out)
# Output
Duration Activity
0 14 Groom
1 8 Pause
2 6 Groom
3 92 Sleep
13 1 Awaken
14 27 Groom
15 25 Pause
16 117 Groom
17 2 Eat
18 962 Cuddle
19 2 Come down
20 2 Dig
21 1 Forage