CODEWITHSUNDEEP
pythonpandasdataframenumpyrandom
NeStack
NeStack

Reputation: 2012

In a pandas dataframe convert all values of all columns to random float

I have a dataframe that looks something like that:

In [2]: df
Out[3]:
     A   B   C   D
0   45  88  44  92
1   62  34   2  86
2   85  65  11  31
3   74  43  42  56

My code contains some conditions, and if one of them get fulfilled I want to turn all the values in all the columns to random floats between 0 and 1. I want to keep the shape and the column names the same, so I hope there is an easy way to do this, something like:

In [4]: df2 = df.apply(value_randomization(0,1))
In [5]: df2
Out[6]:
    A     B     C     D
0   0.76  0.88  0.44  0.92
1   0.62  0.34  0.2   0.86
2   0.85  0.65  0.11  0.31
3   0.74  0.43  0.42  0.56

Is there such a simple solution to it? If not, what would you recommend me? tnx

Upvotes: 0

Views: 144

Answers (3)

NeStack
NeStack

Reputation: 2012

Combining the answers by BENY and rhug123 this is the most satisfying solution I have encountered so far:

df2 = pd.DataFrame(data=np.random.random(df.shape), columns=df.columns, index=df.index)

Upvotes: 0

BENY
BENY

Reputation: 323326

Try with

df[:] = np.random.random(df.shape)
df
Out[283]: 
          A         B         C         D
0  0.151300  0.196162  0.200368  0.775231
1  0.844184  0.611911  0.055625  0.015523
2  0.687728  0.693773  0.364394  0.357987
3  0.887951  0.882617  0.175575  0.318022

Upvotes: 4

rhug123
rhug123

Reputation: 8768

Try this:

df2 = pd.DataFrame(np.random.random(size=(len(df.index),len(df.columns))),columns= df.columns).round(2)

Upvotes: 1

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