[英]How to make different columns for each elements in a list?
I have a pandas dataframe column that contains list of strings (lengths are different) like below: df['category']
:我有一个 pandas dataframe 列,其中包含字符串列表(长度不同),如下所示:
df['category']
:
category | ...
---------
['Grocery & Gourmet Food', 'Cooking & Baking', 'Lard & Shortening', 'Shortening'] | ...
['Grocery & Gourmet Food', 'Candy & Chocolate', 'Mints'] | ...
['Grocery & Gourmet Food', 'Soups, Stocks & Broths', 'Broths', 'Chicken'] | ...
Now, I want to break this category column into different columns for each string element in the list.现在,我想为列表中的每个字符串元素将此类别列分成不同的列。 Is it possible to do using pandas?
可以使用 pandas 吗? How I am gonna handle the column names?
我将如何处理列名?
I have gone through the answers of this question , but the difference is my list lengths are not the same always.我已经完成了这个问题的答案,但不同的是我的列表长度并不总是相同。
My expected output would be something like below:我预期的 output 将如下所示:
category_1 | category_2 | category_n | other_columns
------------------------------------------------------------------
Grocery & Gourmet Food | Cooking & Baking | Lard & Shortening | ...
... | ... | ... | ...
I would do something like this:我会做这样的事情:
df2 = pd.DataFrame(df['category'].to_list(), columns=[f"category_{i+1}" for i in range(len(df['category'].max()))])
df = pd.concat([df.drop('category', axis=1), df2], axis=1)
Output: Output:
category_1 category_2 category_3 \
0 Grocery & Gourmet Food Cooking & Baking Lard & Shortening
1 Grocery & Gourmet Food Candy & Chocolate Mints
2 Grocery & Gourmet Food Soups, Stocks & Broths Broths
category_4
0 Shortening
1 None
2 Chicken
Edit:编辑:
As @mozway suggested, it is better to create the columns with their default names and then update them:正如@mozway建议的那样,最好使用默认名称创建列,然后更新它们:
df2 = pd.DataFrame(df['category'].to_list())
df2.columns = df2.columns.map(lambda x: f'category_{x+1}')
df = pd.concat([df.drop('category', axis=1), df2], axis=1)
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