python - pandas mask change value where condition true and false

Question

I have a matrix of values. I want to rank the values in the columns and then set top ranked values to 1 and others to zero.

I have tried to do this using nlargest, head but the only solution I can figure out is to apply mask twice.

My solution is below, but is there a smarter way to do this?

many thanks

John

import pandas as pd
df = pd.DataFrame([(1, 2, 3),
                   (4, 5, 6),
                   (7, 8, 9),
                   (11, 21, 31),
                   (41, 51, 31),
                   (71, 51, 61),
                   (71, 81, 91)],
                  columns=('value_1','value_2','value_3'))

	value_1	value_2	value_3
0	1	2	3
1	4	5	6
2	7	8	9
3	11	21	31
4	41	51	31
5	71	51	61
6	71	81	91

Answer 1

Try creating the boolean values and then use astype

(~(df.rank(ascending=False, axis=0, method='min') > N)).astype(int)

   value_1  value_2  value_3
0        0        0        0
1        0        0        0
2        0        0        0
3        0        0        1
4        1        1        1
5        1        1        1
6        1        1        1