CODEWITHSUNDEEP
pythonpandasnumpydataframe
uniXVanXcel
uniXVanXcel

Reputation: 806

Apply Numpy function over entire Dataframe

I am applying this function over a dataframe df1 such as the following:

                          AA          AB             AC           AD  
2005-01-02 23:55:00      "EQUITY"    "EQUITY"      "EQUITY"     "EQUITY"   
2005-01-03 00:00:00        32.32      19.5299        32.32      31.0455   
2005-01-04 00:00:00      31.9075      19.4487      31.9075      30.3755   
2005-01-05 00:00:00      31.6151      19.5799      31.6151       29.971   
2005-01-06 00:00:00      31.1426      19.7174      31.1426      29.9647  

def func(x):
    for index, price in x.iteritems():
      x[index] = price / np.sum(x,axis=1)
    return x[index]

df3=func(df1.ix[1:])

However, I only get a single column returned as opposed to 3

    2005-01-03    0.955843
    2005-01-04    0.955233
    2005-01-05    0.955098
    2005-01-06    0.955773
    2005-01-07    0.955877
    2005-01-10     0.95606
    2005-01-11     0.95578
    2005-01-12    0.955621

I am guessing I am missing something in the formula to make it apply to the entire dataframe. Also how could I return the first index that has strings in its row?

Upvotes: 0

Views: 1849

Answers (1)

Ujjwal
Ujjwal

Reputation: 1859

You need to do it the following way :

def func(row):
    return row/np.sum(row)
df2 = pd.concat([df[:1], df[1:].apply(func, axis=1)], axis=0)

It has 2 steps :

  1. df[:1] extracts the first row, which contains strings, while df[1:] represents the rest of the DataFrame. You concatenate them later on, which answers the second part of your question.
  2. For operating over rows you should use apply() method.

Upvotes: 2

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