[英]Split dataframe column containing list inside a string to two columns
I have a df where one column, 'vals' contains a list inside a string. 我有一个df,其中一列,'vals'包含一个字符串内的列表。 I want to convert this into two columns 'val1' and 'vals2.
我想把它转换成两列'val1'和'vals2。 I have tried to split and strip the string but can't find an implementation to do this for every row in the df.
我试图拆分和剥离字符串,但无法找到实现为df中的每一行执行此操作。
vals
'[12.1, 15.0]'
val1 val2
12.1 15.0
Use strip
with split
and casting to floats if necessary, last add prefix by add_prefix
: 如有必要,使用
strip
split
和转换的strip
来浮动,最后通过add_prefix
添加前缀:
df = pd.DataFrame({'vals':["'[12.1, 15.0]'","'[12.1, 15.0]'"]})
df = (df['vals'].str.strip("'[]")
.str.split(', ', expand=True)
.astype(float)
.add_prefix('val'))
If no missing values and performance is important: 如果没有缺失值和性能很重要:
df = pd.DataFrame([x.strip("'[]").split(', ') for x in df['vals']],
columns = ['val1', 'val2']).astype(float)
Here we employ ast.literal_eval - 在这里我们使用ast.literal_eval -
import ast
df = pd.DataFrame({'A':['[12.1, 15.0]','[12.4, 11.1]']})
df['val1']=df['A'].apply(lambda x:ast.literal_eval(x)[0])
df['val2']=df['A'].apply(lambda x:ast.literal_eval(x)[1])
df
A val1 val2
0 [12.1, 15.0] 12.1 15.0
1 [12.4, 11.1] 12.4 11.1
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