Quickest way to make a get_dummies type dataframe from a column with a multiple of strings

I have a column, ‘col2’, that has a list of strings. The current code I have is too slow, there’s about 2000 unique strings (the letters in the example below), and 4000 rows. Ending up as 2000 columns and 4000 rows.

In [268]: df.head()
Out[268]:
    col1    col2
0   6       A,B
1   15      C,G,A
2   25      B

Is there a fast way to make this in a get dummies format? Where each string has it’s own column and in each string’s column there is a 0 or 1 if it that row has that string in col2.

In [268]: def get_list(df):
d = []
for row in df.col2:
    row_list = row.split(',')
    for string in row_list:
        if string not in d:
            d.append(string)
return d

df_list = get_list(df)

def make_cols(df, lst):
    for string in lst:
        df[string] = 0
    return df

df = make_cols(df, df_list)


for idx in range(0, len(df['col2'])):
    row_list = df['col2'].iloc[idx].split(',')
    for string in row_list:
        df[string].iloc[idx]+= 1

Out[113]:
col1    col2    A   B   C   G
0   6   A,B     1   1   0   0
1   15  C,G,A   1   0   1   1
2   25  B       0   1   0   0

This is my current code for it but it’s too slow.

Thanks you any help!

Answers:

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Method 1

You can use:

>>> df['col2'].str.get_dummies(sep=',')
   A  B  C  G
0  1  1  0  0
1  1  0  1  1
2  0  1  0  0

To join the Dataframes:

>>> pd.concat([df, df['col2'].str.get_dummies(sep=',')], axis=1)
   col1   col2  A  B  C  G
0     6    A,B  1  1  0  0
1    15  C,G,A  1  0  1  1
2    25      B  0  1  0  0

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0