concatenate two pandas dataframes with different sizes

Question

I have two pandas dataframes, called data and data1 (which I extracted both from an unestructured excel file).

data is a one row dataframe. data1 is a multiple row dataframe (it will vary depending on the original excel file).

What I want to achieve is to concatenate both, but the values from data repeat for each row in data1. resulting like this:

data	data	data	data1	data1	data1
One	Two	Three	asda	dsad	dsass
One	Two	Three	dsad	dasda	dasds
One	Two	Three	asda	asdsss	dsass
One	Two	Three	adsa	dsad	asdds

Is there an efficient way to do this? I've been doing it manually, but it is taking too long because there are like 1k+ files.

Best regards.

Answer 1

Try something like this:

pd.concat([data.reindex(data.index.repeat(len(data1))).reset_index(drop=True), 
           data1], 
          axis=1, 
          ignore_index=True)

Details:

• Repeat the one row index of data for the number of rows in data1.
• Reindex data to expand the size the number of rows in data and drop repeated index.
• Concatenate data with data1 using axis=1.

Answer 2

You can do something like this:

data = pd.DataFrame(data = ['One', 'Two', 'Three'])
data = data.T
data1 = pd.DataFrame({"col1": ['asda', 'dsad', 'adsa'],
                        "col2": ['dsad', 'dasda', 'asdsss'],
                        "col3": ['dsass', 'dasds', 'asdds']})
data.merge(data1, how = 'cross')

which should give:

    0   1   2       col1    col2    col3
0   One Two Three   asda    dsad    dsass
1   One Two Three   dsad    dasda   dasds
2   One Two Three   adsa    asdsss  asdds

It's then kind of down to you how you want to deal with your column names. You cannot have more than one column with the same name so data can't be reused.