Pandas: concatenate a list of columns into one column

Question

I am wondering if I could build such a module in Pandas:

    def concatenate(df,columnlist,newcolumn):
        # df is the dataframe and
        # columnlist is the list contains the column names of all the columns I want to concatnate
        # newcolumn is the name of the resulted new column

        for c in columnlist:
            ...some Pandas functions

        return df # this one has the concatenated "newcolumn"

I am asking this because that len(columnlist) is going to be very big and dynamic. Thanks!

Answer 1

Try this:

import numpy as np
np.add.reduce(df[columnlist], axis=1)

What this does is to "add" the values in each row, which for strings means to concatenate them ("abc" + "de" == "abcde").

---

Originally I thought you wanted to concatenate them lengthwise, into a single longer series of all the values. If anyone else wants to do that, here's the code:

pd.concat(map(df.get, columnlist)).reset_index(drop=True)

Answer 2

Given a dataframe like this:

df

     A    B
0  aaa  ddd
1  bbb  eee
2  ccc  fff

You can just use df.sum, given every column is a string column:

df.sum(1)

0    aaaddd
1    bbbeee
2    cccfff
dtype: object

If you need to perform a conversion, you can do so:

df.astype(str).sum(1)

If you need to select a subset of your data (only string columns?), you can use select_dtypes:

df.select_dtypes(include=['str']).sum(1)

If you need to select by columns, this should do:

df[['A', 'B']].sum(1)

In every case, the addition is not inplace, so if you want to persist your result, please assign it back:

r = df.sum(1)