I have a dataframe with two columns:
x y
0 1
1 1
2 2
0 5
1 6
2 8
0 1
1 8
2 4
0 1
1 7
2 3
What I want is:
x val1 val2 val3 val4
0 1 5 1 1
1 1 6 8 7
2 2 8 4 3
I know that the values in column x are repeated all N times.
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1I think that a column header is missing in your expected output, since you have five num columns and four headers.Fabio Lamanna– Fabio Lamanna2016-01-01 13:39:02 +00:00Commented Jan 1, 2016 at 13:39
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1 Answer
You could use groupby/cumcount to assign column numbers and then call pivot:
import pandas as pd
df = pd.DataFrame({'x': [0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2],
'y': [1, 1, 2, 5, 6, 8, 1, 8, 4, 1, 7, 3]})
df['columns'] = df.groupby('x')['y'].cumcount()
# x y columns
# 0 0 1 0
# 1 1 1 0
# 2 2 2 0
# 3 0 5 1
# 4 1 6 1
# 5 2 8 1
# 6 0 1 2
# 7 1 8 2
# 8 2 4 2
# 9 0 1 3
# 10 1 7 3
# 11 2 3 3
result = df.pivot(index='x', columns='columns')
print(result)
yields
y
columns 0 1 2 3
x
0 1 5 1 1
1 1 6 8 7
2 2 8 4 3
Or, if you can really rely on the values in x being repeated in order N times,
N = 3
result = pd.DataFrame(df['y'].values.reshape(-1, N).T)
yields
0 1 2 3
0 1 5 1 1
1 1 6 8 7
2 2 8 4 3
Using reshape is quicker than calling groupby/cumcount and pivot, but it
is less robust since it relies on the values in y appearing in the right order.
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