包含可变长度和逗号分隔的值字符串的熊猫行列如何堆叠成单独的值？

Question

I'm in the process of trying to separate specific values in a pandas column so that any "groups" of values become separate values.

The code I'm using to do this currently is as follows:

import csv
import pandas as pd 

data = pd.read_csv('ctabuses.csv')
route_column = data['routes']

with open('results.csv', 'wt+') as csv_file:
    writer = csv.writer(csv_file)
    for value in route_column:
        writer.writerow(value.split)

However, when I write the contents to a file it produces this:

126

121,123

1,7,X28,126,129,130,132,151

1,7,X28,126,129,130,151

1,7,X28,126,129,130

1,7,X28,126,129

1,3,4,7,J14,26,X28,126,129,132,143,147,148

7,126,132,143,147

1,7,X28,126,129

3,4,6,J14,26,143

1,7,X28,126,129,151

1,7,X28,126,129,130,134,135,136,151,156

125,126

126

126

126

I've searched and tried everything I can think of and keep getting the same result.

Edit: Expected Result My expected output if I encounter a group of values like this:

1,7,X28,126,129,130,134,135,136,151,156

Should be:

1
7
X28
126
129
130
134
135
136
151
156

Which would then be used to import into a MySQL database.

Answer 1

Imports:

import pandas as pd

Create DataFrame:

df = pd.read_csv('data.csv', header=None)

df.head()

                              0
0                           126
1                       121,123
2   1,7,X28,126,129,130,132,151
3       1,7,X28,126,129,130,151
4           1,7,X28,126,129,130

String to list:

df_list = df.apply(lambda row: pd.Series(row).str.split(','))

df_list.head()

                                       0
0                                  [126]
1                             [121, 123]
2   [1, 7, X28, 126, 129, 130, 132, 151]
3        [1, 7, X28, 126, 129, 130, 151]
4             [1, 7, X28, 126, 129, 130]

List to long:

df_long = df_list.apply(lambda x: pd.Series(x[0]), axis=1).stack().reset_index(level=1, drop=True)

df_long

0     126
1     121
1     123
2       1
2       7
2     X28
2     126
2     129
2     130
2     132
2     151
3       1
3       7
3     X28
3     126
3     129
3     130
3     151
...

Save to csv:

df_long.to_csv('results.csv', index=False)

Final Program (4 lines):

df = pd.read_csv('ctabuses.csv')
df_routes = df.routes.apply(lambda row: pd.Series(row).str.split(','))
df_routes = df_routes.apply(lambda row: pd.Series(row[0]), axis=1).stack().reset_index(level=1, drop=True)
df_routes.to_csv('results.csv', index=False)