如何在 Pandas 中将带有数字列表的列转换为 np.array 格式

Question

How to convert all rows of a column to numpy array format in a pandas dataframe? A sample dataframe:

df=pd.DataFrame({
        "actual":["1,0,0,1","0,0,1,0"],
        "predicted":["[1,0,0,0]","[0,1,1,1]"]
    })

Ideal data frame:

I tried to convert the actual column to array format using the code below but failed.

df['actual']=df.actual(lambda x: np.array([int(s) for s in x.to_numpy().split(',')]))

Answer 1

The error comes because of df.actual( you call on the column itself, like df['actual']( , you may use Series.apply and to_numpy doesn't exists on a str

df['actual'] = df.actual.apply(lambda x: np.array([int(s) for s in x.split(',')]))

         actual  predicted
0  [1, 0, 0, 1]  [1,0,0,0]
1  [0, 0, 1, 0]  [0,1,1,1]

Answer 2

You are missing the 'apply' function in the series. And you don't have to call .to_numpy()

df['actual']=df.actual.apply(lambda x: np.array([int(s) for s in x.split(',')]))