将pandas DataFrame中的列转换为多列

Question

I have a pandas DataFrame with a column which has the following values in a column:

Identifier
[1;12;7;3;0]
[4;5;2;6;0]

I want to convert the values in square brackets in this column to 5 new columns. Essentially, I want to split those values into 5 new columns, while keeping the index for new columns same as the original column.

Identifier,a,b,c,d,e
[1;12;7;3;0],1,12,7,3,0
[4;5;2;6;0],4,5,2,6,0

pattern = re.compile(r'(\d+)')
for g in raw_data["Identifier"]:
    new_id = raw_data.Identifier.str.findall(pattern) # this converts the Identifier into a list of the 5 values
raw_data.append({'a':new_id[0],'b':new_id[1],'c':new_id[2],'d':new_id[3],'d':new_id[4]}, ignore_index=True)

The above code adds the extracted values from the column "identifier" to the end of the DataFrame and not to the corresponding rows. How can I add the values extracted to the same row/index as the original column ('Identifier')?

Answer 1

One way would be to use str methods to get the numbers, make a new dataframe from that, and then join (or concatentate) the results. For example,

id_data = df.Identifier.str.strip("[]").str.split(";").tolist()
df_id = pd.DataFrame(id_data, columns=list("abcde"), index=df.index, dtype=int)
df2 = df.join(df_id)

produces something like

      Identifier  a   b  c  d  e
10  [1;12;7;3;0]  1  12  7  3  0
20   [4;5;2;6;0]  4   5  2  6  0