Convert a column of strings into columns of characters

Question

I have imported CSV file in pandas it contains, 1 column and 25000 rows, I want to transform this file into new data frame sample data:

1 column 4 rows:

           ABC
           122
           678
           abc 

I want to create DataFrame with, each element of the list(ABC) as rows columns like, followed by other rows, like this :

           A  B  C
           1  2  2
           6  7  8
           a  b  c

How to perform this task, I am new to programming.

Answer 1

Option 1
Straightforward solution altering the view :

pd.DataFrame(
    df.values.astype(str).view('<U1'), columns=list(df.columns[0])
)
   A  B  C
0  1  2  2
1  6  7  8
2  a  b  c

Note that all resultant columns are now strings. Here's how it fares performance-wise:

df = pd.concat([df] * 100000, ignore_index=True)

%timeit pd.DataFrame(
    df.values.astype(str).view('<U1'), columns=list(df.columns[0])
)
122 ms ± 3.17 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

---

Option 2
Slower alternative using extractall + unstack :

df.ABC.str.extractall('(.)')[0].unstack().rename(
     columns=dict(enumerate('ABC'))
)

match  A  B  C
0      1  2  2
1      6  7  8
2      a  b  c

---

Option 3
One more with a list comprehension:

pd.DataFrame([list(x) for x in df.ABC.astype(str)], columns=list('ABC'))

   A  B  C
0  1  2  2
1  6  7  8
2  a  b  c

Answer 2

Another way would be

In [131]: pd.DataFrame(df.ABC.apply(list).tolist(), columns=list(df.columns[0]))
Out[131]:
   A  B  C
0  1  2  2
1  6  7  8
2  a  b  c