我有一个包含值的数据框：
3.05
35.97
49.11
48.80
48.02
10.61
25.69
6.02
55.36
0.42
47.87
2.26
54.43
8.85
8.75
14.29
41.29
35.69
44.27
1.08
我想将值转换为范围并为每个值赋予新值。从df我们知道最小值是0.42，最大值是55.36。从范围最小到最大，我想分为4组，它是：
0.42 - 14.15 transform to 1
14.16 - 27.88 transform to 2
27.89 - 41.61 transform to 3
41.62 - 55.36 transform to 4
所以我预期的结果是
1
3
4
4
4
1
2
1
4
1
4
1
4
1
1
2
3
3
4
1
这通常称为binning，但是pandas称之为cut。示例代码如下：
import pandas as pd
# Create a list of numbers, with a header called "nums"
data_list = [('nums', [3.05, 35.97, 49.11, 48.80, 48.02, 10.61, 25.69, 6.02, 55.36, 0.42, 47.87, 2.26, 54.43, 8.85, 8.75, 14.29, 41.29, 35.69, 44.27, 1.08])]
# Create the labels for the bin
bin_labels = [1,2,3,4]
# Create the dataframe object using the data_list
df = pd.DataFrame.from_items(data_list)
# Define the scope of the bins
bins = [0.41, 14.16, 27.89, 41.62, 55.37]
# Create the "bins" column using the cut function using the bins and labels
df['bins'] = pd.cut(df['nums'], bins=bins, labels=bin_labels)
这将创建一个具有以下结构的数据框：
print(df)
nums bins
0 3.05 1
1 35.97 3
2 49.11 4
3 48.80 4
4 48.02 4
5 10.61 1
6 25.69 2
7 6.02 1
8 55.36 4
9 0.42 1
10 47.87 4
11 2.26 1
12 54.43 4
13 8.85 1
14 8.75 1
15 14.29 2
16 41.29 3
17 35.69 3
18 44.27 4
19 1.08 1
您可以构建如下所示的函数来完全控制该过程：
def transform(l):
l2 = []
for i in l:
if 0.42 <= i <= 14.15:
l2.append(1)
elif i <= 27.8:
l2.append(2)
elif i <= 41.61:
l2.append(3)
elif i <= 55.36:
l2.append(4)
return(l2)
df['nums'] = transform(df['nums'])