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python - 删除 Pandas 数据框中的列表

问题描述

我有以下数据框：

Index   Recipe_ID   order   content
0       1285        1       Heat oil in a large frypan with lid over mediu...
1       1285        2       Meanwhile, add cauliflower to a pot of boiling...
2       1285        3       Remove lid from chicken and let simmer uncover... 
3       1289        1       To make the dressing, whisk oil, vinegar and m...
4       1289        2       Cook potatoes in a large saucepan of boiling w..

任务：我需要在一个单元格中获取内容：

df = df.groupby('recipe_variation_part_id', as_index=False).agg(lambda x: x.tolist())

这将返回以下内容：

Index   Recipe_ID   order         content
0       1285        [1, 2, 3]     [Heat oil in a large frypan with lid over medi...
1       1289        [1, 2, 3]     [To make the dressing, whisk oil, vinegar and ...
2       1297        [1, 2, 4, 3]  [Place egg in saucepan of cold water and bring...
3       1301        [1, 2]        [Preheat a non-stick frying pan and pan fry th...
4       1309        [2, 3, 4, 1]  [Meanwhile, cook noodles according to package ...

如果您查看第一个配方条目，您会得到以下信息：

['Heat oil in a large frypan with lid over medium-high heat. Cook onions, garlic and rosemary for a couple of minutes until soft. Add chicken and brown on both sides for a few minutes, then add in tomatoes and olives. Season with salt and pepper and allow to simmer with lid on for 20-25 minutes. ',
 'Meanwhile, add cauliflower to a pot of boiling water and cook for 10 minutes or until soft. Drain and then mash and gently fold in olive oil, parmesan, salt and pepper. ',
 'Remove lid from chicken and let simmer uncovered for five minutes more. Sprinkle with parsley then serve with cauliflower mash. ']

这就是我想要的，但我需要删除方括号

dtype = 列表

我试过了：

df.applymap(lambda x: x[0] if isinstance(x, list) else x)

只返回第一个条目，而不是每一步

我试过了：

df['content'].str.replace(']', '')

只返回 NAN

我试过了：

df['content'].str.replace(r'(\[\[(?:[^\]|]*\|)?([^\]|]*)\]\])', '')

只返回 NAN

我试过了：

df['content'].str.get(0)

只返回第一个条目

任何帮助将不胜感激。

如果您需要任何进一步的信息，请告诉我。

标签： pythonpandasdata-cleaning

解决方案

我创建了一个小例子，可以为你解决这个问题：

import pandas as pd
df = pd.DataFrame({'order': [1, 1, 2], 'content': ['hello', 'world', 'sof']})
df
Out[4]: 
   order content
0      1   hello
1      1   world
2      2     sof
df.groupby(by=['order']).agg(lambda x: ' '.join(x))
Out[5]: 
           content
order             
1      hello world
2              sof

因此，就像您在问题的第 5 行中所做的那样，您使用' '.join(x)而不是tolist()将所有内容都作为 1 个大字符串而不是字符串列表，因此，不[]

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