我有一个数据帧,我把它分成相等的块,但我不知道如何访问这些信息。我正在考虑进行交叉验证,但不知道如何切片/使用拆分的数据集。
这是一个伪示例。。。
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,100,size=(50, 4)), columns=list('ABCD'))
N = 5
df = np.array_split(df, N)
df
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,100,size=(50, 4)), columns=list('ABCD'))
N = 5
a=[]
df = np.array_split(df, N)
for items in df:
a.append(str(items))
cnt = 0
for things in a:
cnt +=1
print(' '+str(cnt) + ': A B C D linear col')
print('___________________')
print(things.split('n'))
这是输出:
1: A B C D linear col
___________________
[' A B C D', '0 95 67 17 8', '1 87 79 94 82', '2 72 13 72 13', '3 30 88 13 49', '4 38 4 79 47', '5 57 42 29 28', '6 6 31 16 25', '7 15 60 1 94', '8 14 88 2 16', '9 39 83 53 89']
2: A B C D linear col
___________________
[' A B C D', '10 54 69 96 97', '11 72 15 9 51', '12 38 84 21 75', '13 0 52 5 29', '14 11 55 5 22', '15 27 81 48 8', '16 36 24 83 99', '17 80 97 59 86', '18 61 90 61 49', '19 28 67 79 13']
3: A B C D linear col
___________________
[' A B C D', '20 85 69 58 81', '21 85 70 1 25', '22 98 62 35 67', '23 64 6 87 45', '24 85 56 16 74', '25 19 69 88 62', '26 78 43 31 27', '27 57 59 73 90', '28 26 27 31 97', '29 54 39 19 90']
4: A B C D linear col
___________________
[' A B C D', '30 24 57 64 4', '31 21 70 93 29', '32 87 17 72 97', '33 82 47 4 60', '34 54 2 13 41', '35 87 88 58 97', '36 75 9 42 32', '37 45 17 3 7', '38 74 14 72 53', '39 13 35 11 94']
5: A B C D linear col
___________________
[' A B C D', '40 95 10 9 28', '41 52 4 80 11', '42 90 99 6 64', '43 58 67 74 57', '44 74 0 82 47', '45 52 48 73 79', '46 12 12 96 60', '47 52 3 37 29', '48 36 13 2 41', '49 56 4 6 7']
格式化为切片后,检查此切片tuto:https://www.w3schools.com/python/ref_func_slice.asp#:~:text=%20slice((%20函数%20返回,slice%20仅%20每个%20其他%20项。