将pandas列写入csv，不合并整数

Question

我已经提取了user_id对shop_ids

user_id     shop_ids
0   022221205   541
1   023093087   5088,4460,4460,4460,4460,4460,4460,4460,5090
2   023096023   2053,2053,2053,2053,2053,2053,2053,2053,2053,1...
3   023096446   4339,4339,3966,4339,4339
4   023098684   5004,3604,5004,5749,5004

我正试图将此数据框写入csv使用:df.to_csv('users_ordered_shops.csv')

最后，csv将商店id合并为一个数字，如下所示:

user_id     shop_ids
0   22221205    541
1   23093087    508,844,604,460,446,000,000,000,000,000,000,000
2   23096023    2,053,205,320,532,050,000,000,000,000,000,000,000,000,000,000,000,000
3   23096446    43,394,339,396,643,300,000
4   23098684    50,043,604,500,457,400,000

索引2的值为:

print(df.iloc[2].shop_ids)
2053,2053,2053,2053,2053,2053,2053,2053,2053,1294,1294,2053,1922

期望的输出是一个csv文件，所有的shop_id在一列或不同的列中完整，如:

user_id     shop_ids
0   022221205   541
1   023093087   5088,4460,4460,4460,4460,4460,4460,4460,5090
2   023096023   2053,2053,2053,2053,2053,2053,2053,2053,2053,1294,1294,2053,1922
3   023096446   4339,4339,3966,4339,4339
4   023098684   5004,3604,5004,5749,5004

关于如何在写入csv文件时不合并商店id的任何提示?我已经尝试将shop_ids列使用astype()转换为int和str，这导致了相同的输出。

Answer 1

更新

要获得每个列一个商店(并删除重复的)，您可以使用:

pd.concat([df['user_id'],
df['shop_ids'].apply(lambda x: sorted(set(x.split(','))))
.apply(pd.Series)],
axis=1).to_csv('users_ordered_shops.csv', index=False)

---

更改分隔符。试一试:

df.to_csv('users_ordered_shops.csv', sep=';')

或者改变引用策略:

import csv
df.to_csv('users_ordered_shops.csv', quoting=csv.QUOTE_NONNUMERIC)