How do you shift each row in pandas data frame by a specific value?
0
If I have a pandas dataframe like this:
2 3 4 NaN NaN NaN
1 NaN NaN NaN NaN NaN
5 6 7 2 3 NaN
4 3 NaN NaN NaN NaN
and an array for the number I would like to shift:
array = [2, 4, 0, 3]
How do I iterate through each row to shift the columns by the number in my array to get something like this:
NaN NaN 2 3 4 NaN
NaN NaN NaN NaN 1 NaN
5 6 7 2 3 NaN
NaN NaN NaN 3 4 NaN
I was trying to do something like this but had no luck.
df = pd.DataFrame(values)
for rows in df.iterrows():
df[rows] = df.shift[change_in_bins[rows]]
python python-2.7 pandas
asked Nov 12 '18 at 4:37
Troy Zaremba
785
add a comment |
0
If I have a pandas dataframe like this:
2 3 4 NaN NaN NaN
1 NaN NaN NaN NaN NaN
5 6 7 2 3 NaN
4 3 NaN NaN NaN NaN
and an array for the number I would like to shift:
array = [2, 4, 0, 3]
How do I iterate through each row to shift the columns by the number in my array to get something like this:
NaN NaN 2 3 4 NaN
NaN NaN NaN NaN 1 NaN
5 6 7 2 3 NaN
NaN NaN NaN 3 4 NaN
I was trying to do something like this but had no luck.
df = pd.DataFrame(values)
for rows in df.iterrows():
df[rows] = df.shift[change_in_bins[rows]]
python python-2.7 pandas
asked Nov 12 '18 at 4:37
Troy Zaremba
785
Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48
add a comment |
0
0
0
If I have a pandas dataframe like this:
2 3 4 NaN NaN NaN
1 NaN NaN NaN NaN NaN
5 6 7 2 3 NaN
4 3 NaN NaN NaN NaN
and an array for the number I would like to shift:
array = [2, 4, 0, 3]
How do I iterate through each row to shift the columns by the number in my array to get something like this:
NaN NaN 2 3 4 NaN
NaN NaN NaN NaN 1 NaN
5 6 7 2 3 NaN
NaN NaN NaN 3 4 NaN
I was trying to do something like this but had no luck.
df = pd.DataFrame(values)
for rows in df.iterrows():
df[rows] = df.shift[change_in_bins[rows]]
python python-2.7 pandas
asked Nov 12 '18 at 4:37
Troy Zaremba
785
If I have a pandas dataframe like this:
2 3 4 NaN NaN NaN
1 NaN NaN NaN NaN NaN
5 6 7 2 3 NaN
4 3 NaN NaN NaN NaN
and an array for the number I would like to shift:
array = [2, 4, 0, 3]
How do I iterate through each row to shift the columns by the number in my array to get something like this:
NaN NaN 2 3 4 NaN
NaN NaN NaN NaN 1 NaN
5 6 7 2 3 NaN
NaN NaN NaN 3 4 NaN
I was trying to do something like this but had no luck.
df = pd.DataFrame(values)
for rows in df.iterrows():
df[rows] = df.shift[change_in_bins[rows]]
python python-2.7 pandas
python python-2.7 pandas
asked Nov 12 '18 at 4:37
Troy Zaremba
785
asked Nov 12 '18 at 4:37
Troy Zaremba
785
asked Nov 12 '18 at 4:37
Troy Zaremba
785
asked Nov 12 '18 at 4:37
Troy Zaremba
785
asked Nov 12 '18 at 4:37
Troy Zaremba
785
785
Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48
add a comment |
Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48
Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48
Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48
add a comment |
1 Answer
1
active
oldest
votes
2
Use for loop with loc and shift:
for index,value in enumerate([2, 4, 0, 3]):
df.loc[index,:] = df.loc[index,:].shift(value)
print(df)
0 1 2 3 4 5
0 NaN NaN 2.0 3.0 4.0 NaN
1 NaN NaN NaN NaN 1.0 NaN
2 5.0 6.0 7.0 2.0 3.0 NaN
3 NaN NaN NaN 4.0 3.0 NaN
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
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
2
Use for loop with loc and shift:
for index,value in enumerate([2, 4, 0, 3]):
df.loc[index,:] = df.loc[index,:].shift(value)
print(df)
0 1 2 3 4 5
0 NaN NaN 2.0 3.0 4.0 NaN
1 NaN NaN NaN NaN 1.0 NaN
2 5.0 6.0 7.0 2.0 3.0 NaN
3 NaN NaN NaN 4.0 3.0 NaN
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
add a comment |
2
Use for loop with loc and shift:
for index,value in enumerate([2, 4, 0, 3]):
df.loc[index,:] = df.loc[index,:].shift(value)
print(df)
0 1 2 3 4 5
0 NaN NaN 2.0 3.0 4.0 NaN
1 NaN NaN NaN NaN 1.0 NaN
2 5.0 6.0 7.0 2.0 3.0 NaN
3 NaN NaN NaN 4.0 3.0 NaN
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
add a comment |
2
2
2
Use for loop with loc and shift:
for index,value in enumerate([2, 4, 0, 3]):
df.loc[index,:] = df.loc[index,:].shift(value)
print(df)
0 1 2 3 4 5
0 NaN NaN 2.0 3.0 4.0 NaN
1 NaN NaN NaN NaN 1.0 NaN
2 5.0 6.0 7.0 2.0 3.0 NaN
3 NaN NaN NaN 4.0 3.0 NaN
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
Use for loop with loc and shift:
for index,value in enumerate([2, 4, 0, 3]):
df.loc[index,:] = df.loc[index,:].shift(value)
print(df)
0 1 2 3 4 5
0 NaN NaN 2.0 3.0 4.0 NaN
1 NaN NaN NaN NaN 1.0 NaN
2 5.0 6.0 7.0 2.0 3.0 NaN
3 NaN NaN NaN 4.0 3.0 NaN
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
edited Nov 12 '18 at 4:52
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
answered Nov 12 '18 at 4:44
Sandeep Kadapa
5,947428
5,947428
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
add a comment |
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
1
1
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
Thank you so much!
– Troy Zaremba
Nov 12 '18 at 14:17
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
@TroyZaremba You are Welcome!
– Sandeep Kadapa
Nov 12 '18 at 15:42
add a comment |
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Is the last column always NaN?
– coldspeed
Nov 12 '18 at 4:48