Pandas: counter increasing each time conditions are met
2
I have a dataframe with some conditions and a Counter that Counts when condition A is met.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 0
01,01,2018 08:07 B 0
01,01,2018 08:10 B 0
01,01,2018 08:13 B 0
01,01,2018 08:22 A 1
01,01,2018 08:24 A 2
01,01,2018 08:25 B 0
01,01,2018 08:27 B 0
01,01,2018 08:29 B 0
01,01,2018 08:30 A 1
I would like that the Count doesn't reset each time condition changes.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 3
01,01,2018 08:07 B 3
01,01,2018 08:10 B 3
01,01,2018 08:13 B 3
01,01,2018 08:22 A 4
01,01,2018 08:24 A 5
01,01,2018 08:25 B 5
01,01,2018 08:27 B 5
01,01,2018 08:29 B 5
01,01,2018 08:30 A 6
At the Moment the code for the Count Looks like:
df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()
Thanks!
python pandas
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
add a comment |
2
I have a dataframe with some conditions and a Counter that Counts when condition A is met.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 0
01,01,2018 08:07 B 0
01,01,2018 08:10 B 0
01,01,2018 08:13 B 0
01,01,2018 08:22 A 1
01,01,2018 08:24 A 2
01,01,2018 08:25 B 0
01,01,2018 08:27 B 0
01,01,2018 08:29 B 0
01,01,2018 08:30 A 1
I would like that the Count doesn't reset each time condition changes.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 3
01,01,2018 08:07 B 3
01,01,2018 08:10 B 3
01,01,2018 08:13 B 3
01,01,2018 08:22 A 4
01,01,2018 08:24 A 5
01,01,2018 08:25 B 5
01,01,2018 08:27 B 5
01,01,2018 08:29 B 5
01,01,2018 08:30 A 6
At the Moment the code for the Count Looks like:
df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()
Thanks!
python pandas
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
add a comment |
2
2
2
I have a dataframe with some conditions and a Counter that Counts when condition A is met.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 0
01,01,2018 08:07 B 0
01,01,2018 08:10 B 0
01,01,2018 08:13 B 0
01,01,2018 08:22 A 1
01,01,2018 08:24 A 2
01,01,2018 08:25 B 0
01,01,2018 08:27 B 0
01,01,2018 08:29 B 0
01,01,2018 08:30 A 1
I would like that the Count doesn't reset each time condition changes.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 3
01,01,2018 08:07 B 3
01,01,2018 08:10 B 3
01,01,2018 08:13 B 3
01,01,2018 08:22 A 4
01,01,2018 08:24 A 5
01,01,2018 08:25 B 5
01,01,2018 08:27 B 5
01,01,2018 08:29 B 5
01,01,2018 08:30 A 6
At the Moment the code for the Count Looks like:
df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()
Thanks!
python pandas
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
I have a dataframe with some conditions and a Counter that Counts when condition A is met.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 0
01,01,2018 08:07 B 0
01,01,2018 08:10 B 0
01,01,2018 08:13 B 0
01,01,2018 08:22 A 1
01,01,2018 08:24 A 2
01,01,2018 08:25 B 0
01,01,2018 08:27 B 0
01,01,2018 08:29 B 0
01,01,2018 08:30 A 1
I would like that the Count doesn't reset each time condition changes.
date condition count
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 3
01,01,2018 08:07 B 3
01,01,2018 08:10 B 3
01,01,2018 08:13 B 3
01,01,2018 08:22 A 4
01,01,2018 08:24 A 5
01,01,2018 08:25 B 5
01,01,2018 08:27 B 5
01,01,2018 08:29 B 5
01,01,2018 08:30 A 6
At the Moment the code for the Count Looks like:
df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()
Thanks!
python pandas
python pandas
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
asked Nov 19 '18 at 17:02
Luca91Luca91
1808
1808
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
4
Why not
df['count']=df['condition'].eq('A').cumsum()
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am tryingdf['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
– Luca91
Nov 20 '18 at 8:46
add a comment |
1
I think groupby.cumsum is what you're looking for
df['count']= df.groupby((df['Date']['condition']).cumsum())
and then later subset the df based on required condition.
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
4
Why not
df['count']=df['condition'].eq('A').cumsum()
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am tryingdf['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
– Luca91
Nov 20 '18 at 8:46
add a comment |
4
Why not
df['count']=df['condition'].eq('A').cumsum()
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am tryingdf['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
– Luca91
Nov 20 '18 at 8:46
add a comment |
4
4
4
Why not
df['count']=df['condition'].eq('A').cumsum()
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
Why not
df['count']=df['condition'].eq('A').cumsum()
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
answered Nov 19 '18 at 17:09
W-BW-B
107k83165
107k83165
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am tryingdf['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
– Luca91
Nov 20 '18 at 8:46
add a comment |
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am tryingdf['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
– Luca91
Nov 20 '18 at 8:46
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying
df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?– Luca91
Nov 20 '18 at 8:46
what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying
df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?– Luca91
Nov 20 '18 at 8:46
add a comment |
1
I think groupby.cumsum is what you're looking for
df['count']= df.groupby((df['Date']['condition']).cumsum())
and then later subset the df based on required condition.
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
add a comment |
1
I think groupby.cumsum is what you're looking for
df['count']= df.groupby((df['Date']['condition']).cumsum())
and then later subset the df based on required condition.
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
add a comment |
1
1
1
I think groupby.cumsum is what you're looking for
df['count']= df.groupby((df['Date']['condition']).cumsum())
and then later subset the df based on required condition.
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
I think groupby.cumsum is what you're looking for
df['count']= df.groupby((df['Date']['condition']).cumsum())
and then later subset the df based on required condition.
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
answered Nov 19 '18 at 17:21
Ken DekalbKen Dekalb
319112
319112
add a comment |
add a comment |
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