pd.cut

常用方式总结：

import pandas as pd
da=data['case_count'].describe([0.2,0.4,0.6,0.8])
bins=[0,da['20%'],da['40%'],da['60%'],da['80%'],da['max']]
data['case_cut']=pd.cut(data['case_count'],bins,labels=[1,2,3,4,5])

list1=[]
bins=[float('-inf'),-0.3,-0.2,-0.1,0,0.1,0.2,0.3,float('inf')]
#计算分箱内的个数
d_bin=pd.cut(data,bins).value_counts()
#计算分箱内不同个数所占百分比
d_bins=pd.cut(data,bins).value_counts(normalize=True)
list1.append(d_bin)
list1.append(d_bins)
df=pd.DataFrame(list1)#可再修改列名