Pandas resize dataframe to have all values in ascending order per column independently
The title should tell everything, I want to rotate this DataFrame:
A NaN 4 3
B 2 1 4
C 3 4 2
D 4 2 8
into this DataFrame:
A 2 1 2
B 3 2 3
C 4 4 4
D NaN 4 8
And I want to do it beautifully. An ugly solution would be to take each column and form a new DataFrame. To check, use:
d = {'one':[None, 2, 3, 4],
'two':[4, 1, 4, 2],
'three':[3, 4, 6, 8],}
df = pd.DataFrame(d, index = list('ABCD'))
+3
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1 answer
The desired view ignores the index values, so the operation looks more like a NumPy operation than Pandas one:
import pandas as pd
d = {'one':[None, 2, 3, 4],
'two':[4, 1, 4, 2],
'three':[3, 4, 6, 8],}
df = pd.DataFrame(d, index = list('ABCD'))
# one three two
# A NaN 3 4
# B 2 4 1
# C 3 6 4
# D 4 8 2
arr = df.values
arr.sort(axis=0)
df = pd.DataFrame(arr, index=df.index, columns=df.columns)
print(df)
gives
one three two
A 2 3 1
B 3 4 2
C 4 6 4
D NaN 8 4
+4
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