Python Pandas - Combining Multiple Columns into one Staggered Column

Question

How do you combine multiple columns into one staggered column? For example, if I have data:

  Column 1 Column 2
0        A        E
1        B        F
2        C        G
3        D        H

And I want it in the form:

  Column 1 
0        A       
1        E       
2        B       
3        F       
4        C       
5        G       
6        D       
7        H     

What is a good, vectorized pythonic way to go about doing this? I could probably do some sort of df.apply() hack but I'm betting there is a better way. The application is putting multiple dimensions of time series data into a single stream for ML applications.

Answer 1

First stack the columns and then drop the multiindex:

df.stack().reset_index(drop=True)
Out: 
0    A
1    E
2    B
3    F
4    C
5    G
6    D
7    H
dtype: object

Answer 2

To get a dataframe:

 pd.DataFrame(df.values.reshape(-1, 1), columns=['Column 1'])

For a series answering OP question:

 pd.Series(df.values.flatten(), name='Column 1')

For a series timing tests:

pd.Series(get_df(n).values.flatten(), name='Column 1')

---

Timing

code

def get_df(n=1):
    df = pd.DataFrame({'Column 2': {0: 'E', 1: 'F', 2: 'G', 3: 'H'},
                       'Column 1': {0: 'A', 1: 'B', 2: 'C', 3: 'D'}})
    return pd.concat([df for _ in range(n)])

Given Sample

Given Sample * 10,000

Given Sample * 1,000,000