Pandas: How do I repeat dataframe for each value in a series?

Question

I have a dataframe (df) as such:

A B
1 a
2 b
3 c

And a series: S = pd.Series(['x','y','z']) I want to repeat the dataframe df for each value in the series. The expected result is to be like this: result:

S A B
x 1 a
y 1 a
z 1 a
x 2 b
y 2 b
z 2 b
x 3 c
y 3 c
z 3 c

How do I achieve this kind of output? I'm thinking of merge or join but mergeing is giving me a memory error. I am dealing with a rather large dataframe and series. Thanks!

Answer 1

Using numpy, lets say you have series and df of diffenent lengths

s= pd.Series(['X', 'Y', 'Z', 'A']) #added a character to s to make it length 4
s_n = len(s)
df_n = len(df)
pd.DataFrame(np.repeat(df.values,s_n, axis = 0), columns = df.columns, index = np.tile(s,df_n)).rename_axis('S').reset_index()

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

Answer 2

UPDATE:

here is a bit changed @A-Za-z's solution which might be bit more memory saving, but it's slower:

x = pd.DataFrame(index=range(len(df) * len(S)))

for col in df.columns:
    x[col] = np.repeat(df[col], len(s))

x['S'] = np.tile(S, len(df))

---

Old incorrect answer:

In [94]: pd.concat([df.assign(S=S)] * len(s))
Out[94]:
   A  B  S
0  1  a  x
1  2  b  y
2  3  c  z
0  1  a  x
1  2  b  y
2  3  c  z
0  1  a  x
1  2  b  y
2  3  c  z