Averaging value based off previous value Python
0
I have a dataframe that looks like:
value 1 value 2
1 10
4 1
5 8
6 10
10 12
I want to go down each entry of value 1, average the previous value, and then create a new column beside value 2 with the average.
The output needs to look like:
value 1 value 2 avg
1 10 nan
4 1 2.5
5 8 4.5
6 10 5.5
10 12 8.0
.
.
How would I go about doing this?
python python-3.x python-2.7 pandas dataframe
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
add a comment |
0
I have a dataframe that looks like:
value 1 value 2
1 10
4 1
5 8
6 10
10 12
I want to go down each entry of value 1, average the previous value, and then create a new column beside value 2 with the average.
The output needs to look like:
value 1 value 2 avg
1 10 nan
4 1 2.5
5 8 4.5
6 10 5.5
10 12 8.0
.
.
How would I go about doing this?
python python-3.x python-2.7 pandas dataframe
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27
add a comment |
0
0
0
I have a dataframe that looks like:
value 1 value 2
1 10
4 1
5 8
6 10
10 12
I want to go down each entry of value 1, average the previous value, and then create a new column beside value 2 with the average.
The output needs to look like:
value 1 value 2 avg
1 10 nan
4 1 2.5
5 8 4.5
6 10 5.5
10 12 8.0
.
.
How would I go about doing this?
python python-3.x python-2.7 pandas dataframe
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
I have a dataframe that looks like:
value 1 value 2
1 10
4 1
5 8
6 10
10 12
I want to go down each entry of value 1, average the previous value, and then create a new column beside value 2 with the average.
The output needs to look like:
value 1 value 2 avg
1 10 nan
4 1 2.5
5 8 4.5
6 10 5.5
10 12 8.0
.
.
How would I go about doing this?
python python-3.x python-2.7 pandas dataframe
python python-3.x python-2.7 pandas dataframe
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
asked Nov 16 '18 at 0:23
HelloToEarthHelloToEarth
515215
515215
It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27
add a comment |
It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27
It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27
It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27
add a comment |
1 Answer
1
active
oldest
votes
3
shift
You can sum a series with the shifted version of itself:
df['avg'] = (df['value1'] + df['value1'].shift()) / 2
print(df)
value1 value2 avg
0 1 10 NaN
1 4 1 2.5
2 5 8 4.5
3 6 10 5.5
4 10 12 8.0
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
3
shift
You can sum a series with the shifted version of itself:
df['avg'] = (df['value1'] + df['value1'].shift()) / 2
print(df)
value1 value2 avg
0 1 10 NaN
1 4 1 2.5
2 5 8 4.5
3 6 10 5.5
4 10 12 8.0
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
add a comment |
3
shift
You can sum a series with the shifted version of itself:
df['avg'] = (df['value1'] + df['value1'].shift()) / 2
print(df)
value1 value2 avg
0 1 10 NaN
1 4 1 2.5
2 5 8 4.5
3 6 10 5.5
4 10 12 8.0
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
add a comment |
3
3
3
shift
You can sum a series with the shifted version of itself:
df['avg'] = (df['value1'] + df['value1'].shift()) / 2
print(df)
value1 value2 avg
0 1 10 NaN
1 4 1 2.5
2 5 8 4.5
3 6 10 5.5
4 10 12 8.0
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
shift
You can sum a series with the shifted version of itself:
df['avg'] = (df['value1'] + df['value1'].shift()) / 2
print(df)
value1 value2 avg
0 1 10 NaN
1 4 1 2.5
2 5 8 4.5
3 6 10 5.5
4 10 12 8.0
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
answered Nov 16 '18 at 0:31
jppjpp
102k2165115
102k2165115
add a comment |
add a comment |
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It all depends on how the data is represented. Do you have a list? A list of lists? Try to explain it in the question and add an example of what you tried so far.
– Marco Bonelli
Nov 16 '18 at 0:27