pandas filling nans by mean of before and after non-nan values
8
I would like to fill df's nan with an average of adjacent elements.
Consider a dataframe:
df = pd.DataFrame({'val': [1,np.nan, 4, 5, np.nan, 10, 1,2,5, np.nan, np.nan, 9]})
val
0 1.0
1 NaN
2 4.0
3 5.0
4 NaN
5 10.0
6 1.0
7 2.0
8 5.0
9 NaN
10 NaN
11 9.0
My desired output is:
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0 <<< deadend
10 7.0 <<< deadend
11 9.0
I've looked into other solutions such as Fill cell containing NaN with average of value before and after, but this won't work in case of two or more consecutive np.nans.
Any help is greatly appreciated!
python pandas
asked 29 mins ago
ChrisChris
1,191213
add a comment |
8
I would like to fill df's nan with an average of adjacent elements.
Consider a dataframe:
df = pd.DataFrame({'val': [1,np.nan, 4, 5, np.nan, 10, 1,2,5, np.nan, np.nan, 9]})
val
0 1.0
1 NaN
2 4.0
3 5.0
4 NaN
5 10.0
6 1.0
7 2.0
8 5.0
9 NaN
10 NaN
11 9.0
My desired output is:
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0 <<< deadend
10 7.0 <<< deadend
11 9.0
I've looked into other solutions such as Fill cell containing NaN with average of value before and after, but this won't work in case of two or more consecutive np.nans.
Any help is greatly appreciated!
python pandas
asked 29 mins ago
ChrisChris
1,191213
add a comment |
8
8
8
1
I would like to fill df's nan with an average of adjacent elements.
Consider a dataframe:
df = pd.DataFrame({'val': [1,np.nan, 4, 5, np.nan, 10, 1,2,5, np.nan, np.nan, 9]})
val
0 1.0
1 NaN
2 4.0
3 5.0
4 NaN
5 10.0
6 1.0
7 2.0
8 5.0
9 NaN
10 NaN
11 9.0
My desired output is:
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0 <<< deadend
10 7.0 <<< deadend
11 9.0
I've looked into other solutions such as Fill cell containing NaN with average of value before and after, but this won't work in case of two or more consecutive np.nans.
Any help is greatly appreciated!
python pandas
asked 29 mins ago
ChrisChris
1,191213
I would like to fill df's nan with an average of adjacent elements.
Consider a dataframe:
df = pd.DataFrame({'val': [1,np.nan, 4, 5, np.nan, 10, 1,2,5, np.nan, np.nan, 9]})
val
0 1.0
1 NaN
2 4.0
3 5.0
4 NaN
5 10.0
6 1.0
7 2.0
8 5.0
9 NaN
10 NaN
11 9.0
My desired output is:
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0 <<< deadend
10 7.0 <<< deadend
11 9.0
I've looked into other solutions such as Fill cell containing NaN with average of value before and after, but this won't work in case of two or more consecutive np.nans.
Any help is greatly appreciated!
python pandas
python pandas
asked 29 mins ago
ChrisChris
1,191213
asked 29 mins ago
ChrisChris
1,191213
asked 29 mins ago
ChrisChris
1,191213
asked 29 mins ago
ChrisChris
1,191213
asked 29 mins ago
ChrisChris
1,191213
1,191213
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
11
Use ffill + bfill and divide by 2:
df = (df.ffill()+df.bfill())/2
print(df)
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0
10 7.0
11 9.0
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
If first and last elements arenan. Then usedf.bfill().ffill()after using the above solution.
– Dark
2 mins ago
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
11
Use ffill + bfill and divide by 2:
df = (df.ffill()+df.bfill())/2
print(df)
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0
10 7.0
11 9.0
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
If first and last elements arenan. Then usedf.bfill().ffill()after using the above solution.
– Dark
2 mins ago
add a comment |
11
Use ffill + bfill and divide by 2:
df = (df.ffill()+df.bfill())/2
print(df)
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0
10 7.0
11 9.0
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
If first and last elements arenan. Then usedf.bfill().ffill()after using the above solution.
– Dark
2 mins ago
add a comment |
11
11
11
Use ffill + bfill and divide by 2:
df = (df.ffill()+df.bfill())/2
print(df)
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0
10 7.0
11 9.0
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
Use ffill + bfill and divide by 2:
df = (df.ffill()+df.bfill())/2
print(df)
val
0 1.0
1 2.5
2 4.0
3 5.0
4 7.5
5 10.0
6 1.0
7 2.0
8 5.0
9 7.0
10 7.0
11 9.0
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
edited 10 mins ago
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
answered 24 mins ago
Sandeep KadapaSandeep Kadapa
6,843630
6,843630
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
If first and last elements arenan. Then usedf.bfill().ffill()after using the above solution.
– Dark
2 mins ago
add a comment |
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
If first and last elements arenan. Then usedf.bfill().ffill()after using the above solution.
– Dark
2 mins ago
3
3
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
That is just brilliant. Thanks a ton :)
– Chris
22 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
@Chris Glad to help.
– Sandeep Kadapa
17 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
this will fail if the first or last element is a nan
– anon01
5 mins ago
2
2
If first and last elements are
nan. Then use df.bfill().ffill() after using the above solution.– Dark
2 mins ago
If first and last elements are
nan. Then use df.bfill().ffill() after using the above solution.– Dark
2 mins ago
add a comment |
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