Python 根据现有列中的值为dataframe列指定随机值

我正在尝试使用employee列中的值填充dataframe的Assignment列。我已将示例赋值粘贴到下表中。 分配值不能等于该行的管理器或下级列中的值。赋值值也不应重复。举个例子，因为Sue和Mary已经被分配了任务，所以他们不应该再被分配任务

我在上找到了和这篇文章的这些说明，但我仍停留在如何使用python执行中间步骤上

+----------+---------+-------------+-------------------+----------------------------------------+
| Employee | Manager | Subordinate | Manager Exclusion | Subordinate Exclusion   |  Assignment  |
+----------+---------+-------------+-------------------+----------------------------------------+
| Jim      | Joe     |             |                 2 |                         |      Mary    |
| Joe      |         | Jim         |                   |                    1    |      Sue     |
| Sue      |         | David       |                   |                    5    |              |
| Kelly    | David   |             |                 5 |                         |              |
| David    | Sue     | Kelly       |                 3 |                    4    |              |
| Mary     | Jim     |             |                 1 |                         |              |
+----------+---------+-------------+-------------------+----------------------------------------+

---

这里有一种使用循环和“随机”函数的方法。似乎有更有效的方法，但这对于一个简短的列表来说已经足够快了：

import pandas as pd
import random 
import numpy as np

#Create the data above

data = {
        'Employee':['Jim','Joe','Sue','Kelly','David','Mary'],
        'Manager':['Joe','','','David','Sue','Jim'],
        'Subordinate':['','Jim','David','','Kelly',''] }
df = pd.DataFrame(data)

#Create list to store 'used' assignments
used = []

#Make blank column for the Assignments

df['Assigned'] = ''

#Loop through the dataframe
for index,row in df.iterrows(): 
#Iterate through random choices until it chooses one that meets the criteria
    while df.iat[index,3] == '':
        rname =  random.choice(df['Employee']) #Get random name from column 1
        if (rname != row['Manager']) and (rname != row['Subordinate']) and (rname != row['Employee']) and (rname not in used):
            df.iat[index,3] = rname #If it met the criteria, assign it.
            used.append(rname) #Add to 'used' list so it won't be used again

---

这里有一种使用循环和“随机”函数的方法。似乎有更有效的方法，但这对于一个简短的列表来说已经足够快了：

import pandas as pd
import random 
import numpy as np

#Create the data above

data = {
        'Employee':['Jim','Joe','Sue','Kelly','David','Mary'],
        'Manager':['Joe','','','David','Sue','Jim'],
        'Subordinate':['','Jim','David','','Kelly',''] }
df = pd.DataFrame(data)

#Create list to store 'used' assignments
used = []

#Make blank column for the Assignments

df['Assigned'] = ''

#Loop through the dataframe
for index,row in df.iterrows(): 
#Iterate through random choices until it chooses one that meets the criteria
    while df.iat[index,3] == '':
        rname =  random.choice(df['Employee']) #Get random name from column 1
        if (rname != row['Manager']) and (rname != row['Subordinate']) and (rname != row['Employee']) and (rname not in used):
            df.iat[index,3] = rname #If it met the criteria, assign it.
            used.append(rname) #Add to 'used' list so it won't be used again

---

嗨，梅根，欢迎来到StackOverflow！在提问时，通常最好包含一些您尝试过的代码。通读是了解什么类型的问题在这里会很受欢迎的好方法。嗨，梅根，欢迎来到StackOverflow！在提问时，通常最好包含一些您尝试过的代码。通读是了解哪些类型的问题在这里会受到欢迎的好方法。