Python Pandas: Calculate moving average within group
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1
I have a dataframe containing time series for 100 objects:
object period value
1 1 24
1 2 67
...
1 1000 56
2 1 59
2 2 46
...
2 1000 64
3 1 54
...
100 1 451
100 2 153
...
100 1000 21
I want to calculate moving average with window 10 for the value column. I guess I have to do something like
df.groupby('object').apply(lambda ~calculate MA~)
and then merge this Series to the original dataframe by object? Can't figure out exact commands
python pandas pandas-groupby moving-average
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
add a comment |
1
I have a dataframe containing time series for 100 objects:
object period value
1 1 24
1 2 67
...
1 1000 56
2 1 59
2 2 46
...
2 1000 64
3 1 54
...
100 1 451
100 2 153
...
100 1000 21
I want to calculate moving average with window 10 for the value column. I guess I have to do something like
df.groupby('object').apply(lambda ~calculate MA~)
and then merge this Series to the original dataframe by object? Can't figure out exact commands
python pandas pandas-groupby moving-average
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52
add a comment |
1
1
1
I have a dataframe containing time series for 100 objects:
object period value
1 1 24
1 2 67
...
1 1000 56
2 1 59
2 2 46
...
2 1000 64
3 1 54
...
100 1 451
100 2 153
...
100 1000 21
I want to calculate moving average with window 10 for the value column. I guess I have to do something like
df.groupby('object').apply(lambda ~calculate MA~)
and then merge this Series to the original dataframe by object? Can't figure out exact commands
python pandas pandas-groupby moving-average
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
I have a dataframe containing time series for 100 objects:
object period value
1 1 24
1 2 67
...
1 1000 56
2 1 59
2 2 46
...
2 1000 64
3 1 54
...
100 1 451
100 2 153
...
100 1000 21
I want to calculate moving average with window 10 for the value column. I guess I have to do something like
df.groupby('object').apply(lambda ~calculate MA~)
and then merge this Series to the original dataframe by object? Can't figure out exact commands
python pandas pandas-groupby moving-average
python pandas pandas-groupby moving-average
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
asked Nov 16 '18 at 13:40
Alexandr KapshukAlexandr Kapshuk
304115
304115
the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52
add a comment |
the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52
the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52
add a comment |
2 Answers
2
active
oldest
votes
2
You can use rolling with transform:
df['moving'] = df.groupby('object')['value'].transform(lambda x: x.rolling(10, 1).mean())
The 1 in rolling is for minimum number of periods.
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
This is the recommended way: I was going to answer withpd.rolling_meanand got the deprecation warning. So, thank you for teaching me something today @zipa
– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
add a comment |
1
You can use rolling on groupby object directly as:
df['moving'] = df.groupby('object').rolling(10)['value'].mean()
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
Hi, I'm getting an error:TypeError: incompatible index of inserted column with frame index. No idea what's the problem...
– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check thisgroupby.rolling
– Sandeep Kadapa
Nov 16 '18 at 15:20
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
2
You can use rolling with transform:
df['moving'] = df.groupby('object')['value'].transform(lambda x: x.rolling(10, 1).mean())
The 1 in rolling is for minimum number of periods.
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
This is the recommended way: I was going to answer withpd.rolling_meanand got the deprecation warning. So, thank you for teaching me something today @zipa
– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
add a comment |
2
You can use rolling with transform:
df['moving'] = df.groupby('object')['value'].transform(lambda x: x.rolling(10, 1).mean())
The 1 in rolling is for minimum number of periods.
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
This is the recommended way: I was going to answer withpd.rolling_meanand got the deprecation warning. So, thank you for teaching me something today @zipa
– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
add a comment |
2
2
2
You can use rolling with transform:
df['moving'] = df.groupby('object')['value'].transform(lambda x: x.rolling(10, 1).mean())
The 1 in rolling is for minimum number of periods.
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
You can use rolling with transform:
df['moving'] = df.groupby('object')['value'].transform(lambda x: x.rolling(10, 1).mean())
The 1 in rolling is for minimum number of periods.
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
answered Nov 16 '18 at 13:52
zipazipa
16.3k31738
16.3k31738
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
This is the recommended way: I was going to answer withpd.rolling_meanand got the deprecation warning. So, thank you for teaching me something today @zipa
– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
add a comment |
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
This is the recommended way: I was going to answer withpd.rolling_meanand got the deprecation warning. So, thank you for teaching me something today @zipa
– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
Oh it's so beautiful! I love Pandas!
– Alexandr Kapshuk
Nov 16 '18 at 13:55
1
1
This is the recommended way: I was going to answer with
pd.rolling_mean and got the deprecation warning. So, thank you for teaching me something today @zipa– Charles Landau
Nov 16 '18 at 13:55
This is the recommended way: I was going to answer with
pd.rolling_mean and got the deprecation warning. So, thank you for teaching me something today @zipa– Charles Landau
Nov 16 '18 at 13:55
You are welcome :)
– zipa
Nov 16 '18 at 13:56
You are welcome :)
– zipa
Nov 16 '18 at 13:56
add a comment |
1
You can use rolling on groupby object directly as:
df['moving'] = df.groupby('object').rolling(10)['value'].mean()
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
Hi, I'm getting an error:TypeError: incompatible index of inserted column with frame index. No idea what's the problem...
– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check thisgroupby.rolling
– Sandeep Kadapa
Nov 16 '18 at 15:20
add a comment |
1
You can use rolling on groupby object directly as:
df['moving'] = df.groupby('object').rolling(10)['value'].mean()
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
Hi, I'm getting an error:TypeError: incompatible index of inserted column with frame index. No idea what's the problem...
– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check thisgroupby.rolling
– Sandeep Kadapa
Nov 16 '18 at 15:20
add a comment |
1
1
1
You can use rolling on groupby object directly as:
df['moving'] = df.groupby('object').rolling(10)['value'].mean()
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
You can use rolling on groupby object directly as:
df['moving'] = df.groupby('object').rolling(10)['value'].mean()
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
answered Nov 16 '18 at 13:58
Sandeep KadapaSandeep Kadapa
7,408831
7,408831
Hi, I'm getting an error:TypeError: incompatible index of inserted column with frame index. No idea what's the problem...
– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check thisgroupby.rolling
– Sandeep Kadapa
Nov 16 '18 at 15:20
add a comment |
Hi, I'm getting an error:TypeError: incompatible index of inserted column with frame index. No idea what's the problem...
– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check thisgroupby.rolling
– Sandeep Kadapa
Nov 16 '18 at 15:20
Hi, I'm getting an error:
TypeError: incompatible index of inserted column with frame index. No idea what's the problem...– Alexandr Kapshuk
Nov 16 '18 at 15:17
Hi, I'm getting an error:
TypeError: incompatible index of inserted column with frame index. No idea what's the problem...– Alexandr Kapshuk
Nov 16 '18 at 15:17
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
Could you please provide a Minimal, Complete, and Verifiable example.
– Sandeep Kadapa
Nov 16 '18 at 15:18
@AlexandrKapshuk It will work you can check this
groupby.rolling– Sandeep Kadapa
Nov 16 '18 at 15:20
@AlexandrKapshuk It will work you can check this
groupby.rolling– Sandeep Kadapa
Nov 16 '18 at 15:20
add a comment |
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the moving averages would be less rows, which periods should they be assigned to?
– Walter Tross
Nov 16 '18 at 13:48
It would be ideal to do like this: for period 1, the MA equals just value from period 1. From period 2, MA = (value_1 + value_2) / 2, and so on until 10. After 10, it's a normal moving average
– Alexandr Kapshuk
Nov 16 '18 at 13:52
I'm trying to use pd.rolling_mean(), but didn't figure it out yet
– Alexandr Kapshuk
Nov 16 '18 at 13:52