Merging a dataframe with another dataframe with constant values from the first dataframe

Question

I would like to merge two data frames, df1 and df2:

import pandas as pd

df1 = pd.DataFrame({
    'A': ['a'],
    'B': ['b'],
    'C': ['c']
})

df2 = pd.DataFrame({
    'W': [1, 2, 3],
    'X': [4, 5, 6],
    'Y': [7, 8, 9],
    'Z': [10, 11, 12]
}) 

df1: (will always have only one row)

df2: (can have any number of rows)

In a way that all the columns of df1 are added to the df2 dataframe with all the rows having the same values present in the df1 dataframe.

I have tried:

df3 = pd.concat([df1,df2], sort=False, axis=1)

But this is giving me NaN's:

But i want all the rows to have the same constant value that is present in df1 like:

I would also like to maintain having the new columns from df1 be before the columns of df2 as above. What might be the most efficient way to achieve this.

Answer 1

We can do an outer merge on an artificially created key:

df1.assign(key=1).merge(df2.assign(key=1), on='key').drop('key', axis=1)

   A  B  C  W  X  Y   Z
0  a  b  c  1  4  7  10
1  a  b  c  2  5  8  11
2  a  b  c  3  6  9  12

Answer 2

Use DataFrame.assign with selecting first row and then change order of columns by DataFrame.reindex:

df3 = df2.assign(**df1.iloc[0]).reindex(df1.columns.union(df2.columns, sort=False),axis=1)
print (df3)
   A  B  C  W  X  Y   Z
0  a  b  c  1  4  7  10
1  a  b  c  2  5  8  11
2  a  b  c  3  6  9  12

Or add rows to df1 by df2.index with method='ffill':

df3 = pd.concat([df1.reindex(df2.index, method='ffill'),df2], sort=False, axis=1)
print (df3)
   A  B  C  W  X  Y   Z
0  a  b  c  1  4  7  10
1  a  b  c  2  5  8  11
2  a  b  c  3  6  9  12