I have a data frame
data = pd.DataFrame({'student': ['a', 'b', 'c'],
'rank': [2, 2, 1],
'rank1': [3, 3, 2],
'rank2': [4, 2, 3]})
my code
import numpy as np
data['Diff'] = np.where((data['rank'] != data['rank1']) &
(data['rank1'] != data['rank2']), '1', '0')
requirement all the ranks must be different then 1 else 0 but I am getting b also as 1
You can use set() and check if the lenght of the set constructed from all the column values == 3:
data["Diff"] = (
data[["rank", "rank1", "rank2"]]
.apply(lambda x: len(set(x)) == 3, axis=1)
.astype(int)
)
print(data)
Prints:
student rank rank1 rank2 Diff
0 a 2 3 4 1
1 b 2 3 2 0
2 c 1 2 3 1
Let us try pd.Series.unique with let
data['new'] = data.filter(like='rank').apply(pd.Series.unique,1).str.len().eq(3).astype(int)
Out[45]:
0 1
1 0
2 1
dtype: int64
