for loop to extract header for a dataframe in pandas

Question

I am a newbie in python. I have a data frame that looks like this:

    A   B   C   D   E
0   1   0   1   0   1
1   0   1   0   0   1
2   0   1   1   1   0
3   1   0   0   1   0
4   1   0   0   1   1

How can I write a for loop to gather the column names for each row. I expect my result set looks like that:

    A   B   C   D   E   Result
0   1   0   1   0   1   ACE
1   0   1   0   0   1   BE
2   0   1   1   1   0   BCD
3   1   0   0   1   0   AD
4   1   0   0   1   1   ADE

Anyone can help me with that? Thank you!

Zeugma · Accepted Answer · 2016-09-02 21:43:30Z

9

The dot function is done for that purpose as you want the matrix dot product between your matrix and the vector of column names:

df.dot(df.columns)
Out[5]: 
0    ACE
1     BE
2    BCD
3     AD
4    ADE

If your dataframe is numeric, then obtain the boolean matrix first by test your df against 0:

(df!=0).dot(df.columns)

PS: Just assign the result to the new column

df['Result'] = df.dot(df.columns)

df
Out[7]: 
   A  B  C  D  E Result
0  1  0  1  0  1    ACE
1  0  1  0  0  1     BE
2  0  1  1  1  0    BCD
3  1  0  0  1  0     AD
4  1  0  0  1  1    ADE

edited Sep 2, 2016 at 21:43

answered Sep 2, 2016 at 21:11

Zeugma

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4 Comments

Merlin Over a year ago

@zihan. what going on hidden from view is Boolean indexing eval. This ONLY works because your matrix values are 0's and 1's.

zihan meng Over a year ago

Thank you for help me answer my question but I have a error shows up >TypeError: can't multiply sequence by non-int of type 'float'

Zeugma Over a year ago

@Merlin sure: with integers n>1 you get n times the value. numpy behind fulfills python logic so you multiply n * 'column title'. That fits OP's matrix form though

Zeugma Over a year ago

@Merlin added a line to explain how to turn a float matrix quickly into a boolean one.

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