在 pandas/python 中，读取存储为字符串的数组
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In pandas/python, reading array stored as string
提问by AMM
I have a pandas dataframe where one of the columns has array of strings as each element.
我有一个 Pandas 数据框，其中一列的每个元素都有字符串数组。
So something like this.
所以像这样的事情。
col1 col2
0 120 ['abc', 'def']
1 130 ['ghi', 'klm']
Now when i store this to csv using to_csv it seems fine. When i read it back using from_csv i seems to read back. But then when i analyse the value in each cell the array is
现在，当我使用 to_csv 将它存储到 csv 时，它看起来很好。当我使用 from_csv 读回它时，我似乎读回了。但是当我分析每个单元格中的值时，数组是
'[' ''' 'a' 'b' 'c' and so on. So essentially its not reading it as an array but a set of strings. Can somebody suggest how I can convert this string into an array?
'[' ''' 'a' 'b' 'c' 等等。所以本质上它不是将其作为数组读取，而是将其读取为一组字符串。有人可以建议我如何将此字符串转换为数组吗？
I mean to say the array has been stored like a string
我的意思是说数组已像字符串一样存储
'[\'abc\',\'def\']'
回答by Andy Hayden
As mentioned in the other questions, you should use literal_evalhere:
正如其他问题中提到的，你应该literal_eval在这里使用：
from ast import literal_eval
df['col2'] = df['col2'].apply(literal_eval)
In action:
在行动：
In [11]: df = pd.DataFrame([[120, '[\'abc\',\'def\']'], [130, '[\'ghi\',\'klm\']']], columns=['A', 'B'])
In [12]: df
Out[12]:
A B
0 120 ['abc','def']
1 130 ['ghi','klm']
In [13]: df.loc[0, 'B'] ?# a string
Out[13]: "['abc','def']"
In [14]: df.B = df.B.apply(literal_eval)
In [15]: df.loc[0, 'B'] #?now it's a list
Out[15]: ['abc', 'def']
回答by AMM
Nevermind got it.
没关系得到它。
All i had to do was
我所要做的就是
arr = s[1:-1].split(',')
This got rid of the square brackets and also split the string into an array like I wanted.
这摆脱了方括号，并将字符串拆分为我想要的数组。
回答by shaktimaan
Without pandas, this is one way to do it using the astmodules' literal_eval():
没有Pandas，这是使用ast模块的一种方法literal_eval()：
>>> data = "['abc', 'def']"
>>> import ast
>>> a_list = ast.literal_eval(data)
>>> type(a_list)
<class 'list'>
>>> a_list[0]
'abc'
回答by Alex S
Maybe try using a different separator value? Like so:
也许尝试使用不同的分隔符值？像这样：
DataFrame.to_csv(filepath, sep=';')
and then read with
然后阅读
DataFrame.from_csv(filepath, sep=';')
