Pandas: How can I repeat the dataframe for each value in the series?

Question

I have a dataframe (df) as such:

A B
1 a
2 b
3 c

And a number: S = pd.Series(['x','y','z'])I want to repeat the dataframe df for each value in the series. The expected result should be as follows: 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 to achieve this type of conclusion? I am thinking of merging or merging, but merging gives me a memory error. I am dealing with fairly large data frames and rows. Thank!

Answer 1

Using numpy, let's say you have a series and df with different 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:

@A-Za-z , , :

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))

---

:

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

Answer 3

df = pd.DataFrame({'A': {0: 1, 1: 2, 2: 3}, 'B': {0: 'a', 1: 'b', 2: 'c'}})
S = pd.Series(['x','y','z'], name='S')

#Convert the Series to a Dataframe with desired shape of the output filled with S values.

#Join df_S to df to get As and Bs
df_S = pd.DataFrame(index=np.repeat(S.index,3), columns=['S'], data= np.tile(S.values,3))

df_S.join(df)

Out[54]: 
   S  A  B
0  x  1  a
0  y  1  a
0  z  1  a
1  x  2  b
1  y  2  b
1  z  2  b
2  x  3  c
2  y  3  c
2  z  3  c