CODEWITHSUNDEEP
pythonreplacepandasdataframe
Nilani Algiriyage
Nilani Algiriyage

Reputation: 35666

Pandas DataFrame Replace every value by 1 except 0

I'm having a pandas DataFrame like following.

3,0,1,0,0
11,0,0,0,0
1,0,0,0,0
0,0,0,0,4
13,1,1,5,0

I need to replace every other value to '1' except '0'. So my expected output.

1,0,1,0,0
1,0,0,0,0
1,0,0,0,0
0,0,0,0,1
1,1,1,1,0

Upvotes: 4

Views: 12444

Answers (3)

user2557522
user2557522

Reputation: 169

Thanks Marius. Also works on just one column when you want to replace all values except 1. Just be careful, this does it inplace

create column 280 from 279 for class {1:Normal,0:Arrhythmia}

df[280] = df[279]
df[280][df[280]!=1] = 0

Upvotes: 0

FooBar
FooBar

Reputation: 16488

As an unorthodox alternative, consider

%timeit (df/df == 1).astype(int)
1000 loops, best of 3: 449 µs per loop
%timeit df[df != 0] = 1
1000 loops, best of 3: 801 µs per loop

As a hint what's happening here: df/df gives you 1 for any value not 0, those will be Inf. Checking ==1 gives you the correct matrix, but in binary form - hence the transformation at the end.

However, as dataframe size increases, the advantage of not having to select but simply operate on all elements becomes irrelevant - eventually you it becomes less efficient.

Upvotes: 0

Marius
Marius

Reputation: 60070

Just use something like df[df != 0] to get at the nonzero parts of your dataframe: 

import pandas as pd
import numpy as np
np.random.seed(123)

df = pd.DataFrame(np.random.randint(0, 10, (5, 5)), columns=list('abcde'))
df
Out[11]: 
   a  b  c  d  e
0  2  2  6  1  3
1  9  6  1  0  1
2  9  0  0  9  3
3  4  0  0  4  1
4  7  3  2  4  7

df[df != 0] = 1
df
Out[13]: 
   a  b  c  d  e
0  1  1  1  1  1
1  1  1  1  0  1
2  1  0  0  1  1
3  1  0  0  1  1
4  1  1  1  1  1

Upvotes: 11

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