Python Dataframe 从一行的每个列表中减去一个值

Python Dataframe subtract a value from each list of a row

我有一个由列表作为元素组成的数据框。我想从每个列表中减去一个值并创建一个新列。 我的代码:

df = pd.DataFrame({'A':[[1,2],[4,5,6]]})
df
           A
0     [1, 2]
1  [4, 5, 6]

# lets substract 1 from each list
val = 1
df['A_new'] = df['A'].apply(lambda x:[a-b for a,b in zip(x[0],[val]*len(x[0]))],axis=1)

当前解决方案:

IndexError: index 3 is out of bounds for axis 0 with size 2

预期解决方案:

df
           A      A_new
0     [1, 2]     [0, 1]
1  [4, 5, 6]  [3, 4, 5]
df['A_new'] = df['A'].apply(lambda x:[a-b for a,b in zip(x,[val]*len(x))])

您必须将列表传递给 len 函数。这里 x 是列表本身。所以索引它,x[0] 只是 returns 一个数字,在上下文中是错误的。这给出了输出:

           A      A_new
0     [1, 2]     [0, 1]
1  [4, 5, 6]  [3, 4, 5]

转换为 numpy array

df['A_new'] = df.A.map(np.array)-1
Out[455]: 
0       [0, 1]
1    [3, 4, 5]
Name: A, dtype: object

简单的列表理解如何:

df['new'] = [[i - 1 for i in l] for l in df['A']]

           A        new
0     [1, 2]     [0, 1]
1  [4, 5, 6]  [3, 4, 5]

您可以将列表转换为 np.array 然后减去 val:

import numpy as np

df['A_new'] = df['A'].apply(lambda x: np.array(x) - val)

输出:

           A      A_new
0     [1, 2]     [0, 1]
1  [4, 5, 6]  [3, 4, 5]