CODEWITHSUNDEEP
pythonpandas
deega
deega

Reputation: 905

replace all values in all columns based on condition

I have a df as below

enter image description here

I want to make this df binary as follows

enter image description here

I tried

df[:]=np.where(df>0, 1, 0)

but with this I am losing my df index. I can try this on all columns one by one or use loop but I think there would be some easy & quick way to do this.

Upvotes: 2

Views: 74

Answers (3)

F.Mink
F.Mink

Reputation: 16

Without using numpy:

df[df>0]=0

Upvotes: 0

Panda Kim
Panda Kim

Reputation: 13247

of course it is possible by func, it can be done with just operator

(df > 0) * 1

Upvotes: 1

jezrael
jezrael

Reputation: 862901

You can convert boolean mask by DataFrame.gt to integers:

df1 = df.gt(0).astype(int)

Or use DataFrame.clip if integers and no negative values:

df1 = df.clip(upper=1)

Your solution should working with loc:

df.loc[:] = np.where(df>0, 1, 0)

Upvotes: 4

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