在Python中将已装箱的数据分组到不同的箱子中

我有特定箱子中提供的数据：

0          T<=-25
1619   -25<T<=-10
98391  -10<T<=0
698588   0<T<=15
782997  15<T<=20

我想将这些装箱值分配给新的箱子。新的边界是：

    T<-14
-14<T<=-12
-12<T<=-10
-10<T<=-8
 -8<T<=-6
 -6<T<=-4
 -4<T<=-2
 -2<T<=0
  0<T<=2
  2<T<=4
  4<T<=6
  6<T<=8
  8<T<=10
 10<T<=12
 12<T<=14
 14<T<=16
 16<T<=18
 18<T<=20
    T>22

---

不确定这是否是实现你想要的最有效的方式，但以下是我通常做的：

def f(x):
    # range T < -14
    if x < -14:
        # return value for corresponding bin
    # range -14 < T < -12
    if x < -12:
        # return value for corresponding bin
    # etc...

df['bin_value'] = df['T'].apply(f)

def（x）：
#范围T<-14
如果x<-14：
#对应bin的返回值
#范围-14

您的问题和示例不清楚。

import pandas as pd
bb_temp =  [-14 + i*2 for i in range( 0, 35 ) ]

d = {'val': [0, 1619, 98391, 698588, 782997, 308393, 131402, 16319, 899, 0, 0, 0, 0, 0 ], 'T_min': [ 0,-25,-10,0,10,20,25,30,35,40,45,50,55,60 ], 'T_max': [-25,-10,0,10,20,25,30,35,40,45,50,55,60,0 ]}
df = pd.DataFrame(data=d)

def f(row):
  bb = [ i for i in bb_temp if i > row[ "T_min" ] and i <= row[ "T_max" ] ] 
  if len( bb ) == 0:
    bb = [0]
    
  new_bin_val = row[ "val" ] / len(bb)
  
  return ( bb, new_bin_val )
  
df[ 'new_bin' ] = df.apply( f, axis=1 )
df

    val     T_min   T_max   new_bin
0   0         0     -25     ([0], 0.0)
1   1619    -25     -10     ([-14, -12, -10], 539.6666666666666)
2   98391   -10     0       ([-8, -6, -4, -2, 0], 19678.2)
3   698588    0     10      ([2, 4, 6, 8, 10], 139717.6)
4   782997   10     20      ([12, 14, 16, 18, 20], 156599.4)
5   308393   20     25      ([22, 24], 154196.5)
6   131402   25     30      ([26, 28, 30], 43800.666666666664)
7   16319    30     35      ([32, 34], 8159.5)
8   899      35     40      ([36, 38, 40], 299.6666666666667)
9   0        40     45      ([42, 44], 0.0)
10  0        45     50      ([46, 48, 50], 0.0)
11  0        50     55      ([52, 54], 0.0)
12  0        55     60      ([0], 0.0)
13  0        60     0       ([0], 0.0)

def f(x):
    # range T < -14
    if x < -14:
        # return value for corresponding bin
    # range -14 < T < -12
    if x < -12:
        # return value for corresponding bin
    # etc...

df['bin_value'] = df['T'].apply(f)