How to add pandas data frame to each row?

Question

If I have a pandas data frame like this:

     0   1   2 
 0   0   0   0
 1   1   0   1
 2   0   0   1
 3   1   1   0

and an pandas data frame like this:

     0   1   2
 0   0   2   3

How do I concatenate this array to each row such that I get a new pandas data frame like this:

     0   1   2   3   4   5
 0   0   0   0   0   2   3
 1   1   0   1   0   2   3
 2   0   0   1   0   2   3
 3   1   1   0   0   2   3

Possible duplicate of [how to combine two data frames in python pandas](https://stackoverflow.com/questions/12850345/how-to-combine-two-data-frames-in-python-pandas) — emilaz, Apr 15 '19 at 16:32

score 2 · Answer 1 · answered Apr 15 '19 at 16:37

There was a deleted answer which was very closed.

# merge the data frame
df = pd.concat([df1, df2], axis=1, sort=False)

# rename dataframe to advoid duplications
df.columns = range(len(df.columns))

# fill na's in the columns of df2
df[-len(df2.columns):].ffill(inplace=True)

score 0 · Answer 2 · answered Apr 15 '19 at 17:27

Can assign multiple static values with a dict:

df1.columns = ['3', '4', '5']
df = df.assign(**df1.to_dict('index')[0])
# If need to be int names: df.columns = df.columns.astype(int)

   0  1  2  3  4  5
0  0  0  0  0  2  3
1  1  0  1  0  2  3
2  0  0  1  0  2  3
3  1  1  0  0  2  3

How to add pandas data frame to each row?

2 Answers2