我是Python的新手。仍在学习列表理解。我有年龄作为连续的数字变量，我需要将其存储为0-10、10-20、20-30…90+。我将调用以下函数。我需要对数据中的100列使用不同的上下限值进行处理，这需要非常高效和简洁。有没有更好的方法可以做到这一点？
def createfactor(x,lower,upper,by,sep="-",above_char="+"):
labs = []
curr = lower
while curr < upper - by:
labs.append(str(curr) + sep + str(curr + by))
curr = curr + by
labs.append(str(upper - by) + above_char)
y = pandas.cut(x,bins=numpy.linspace(lower,upper/by+1),labels=labs)
return y
您可以尝试使用pandas.cut：
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.cut.html
import pandas as pd
import numpy as np
df=pd.DataFrame({"age": [4,23,45,39,76,91,110,10],"x": [1,2,1,5,8,1]})
print(pd.merge(df,pd.cut(df["age"],bins=pd.IntervalIndex.from_tuples([(0,10),(11,20),(21,30),(31,40),(41,50),(51,60),(61,70),(71,80),(81,90),(90,np.Infinity)]),right=True,include_lowest=True),left_index=True,right_index=True,how="outer",suffixes=["","_bins"]))
输出：
age x age_bins
0 4 1 (0.0,10.0]
1 23 2 (21.0,30.0]
2 45 1 (41.0,50.0]
3 39 5 (31.0,40.0]
4 76 2 (71.0,80.0]
5 91 8 (90.0,inf]
6 110 1 (90.0,inf]
7 10 1 (0.0,10.0]
[Program finished]