将数据框架列中的每个元素减去给定的数字- python

Question

我希望将数据框架列中的每个元素减去该列中的特定数字。我目前正在通过将每列转换为numpy数组来实现这一点，这并不理想。

作为一个例子，

data = [[1, 10], [2, 20], [3, 30],[4, 40],[5, 50]]
# Existing dataframe
df = pd.DataFrame(data, columns=['column1', 'column2']) 
a = np.array([2,4]) # this is an array for the index of elements. 2 is for column 1, 4 is for column 2. 
# In column 1 with index=2, find the element, and subtract that from all the elements in column 1. 
#Similarly with column 2, with index = 4, find the element, and subtract that from all the elements in column 2

# Required Output dataframe
data2 = [[-2, -40], [-1, -30], [0, -20],[1, -10],[2, 0]]
df2 = pd.DataFrame(data2, columns=['column1', 'column2'])

输出

Existing data frame: 
column1  column2
0        1       10
1        2       20
2        3       30
3        4       40
4        5       50
Required Output data fram
column1  column2
0       -2      -40
1       -1      -30
2        0      -20
3        1      -10
4        2        0

Answer 1

我们可以使用numpy索引从DataFrame中选择值，通过转换DataFrame.to_numpy，然后减去:

output = df - df.to_numpy()[a, np.arange(df.columns.size)]

或与DataFrame.sub:

output = df.sub(df.to_numpy()[a, np.arange(df.columns.size)], axis='columns')

output:

column1  column2
0       -2      -40
1       -1      -30
2        0      -20
3        1      -10
4        2        0

---

使用a中的行索引选择值:

a = np.array([2, 4])
# [2, 4]

使用np.arange和Index.size为列的长度创建一个RangeIndex:

col_index = np.arange(df.columns.size)
# [0 1]

这些索引可以一起用于从DataFrame中选择值:

df.to_numpy()[a, col_index]
# [ 3 50]