第一，import numpy as np
我们的数据框：

df = pd.DataFrame([
    ["John", "T1",8],
    ["John", "T2", 32],
    ["Alex","A1",40],
    ["Bob","B1",16]],
    columns=["User", "Task", 'Hours'])

# We create a column with the average work hours
df["avg"] = df["Hours"] / 5

# A column with the leftover hours of the first 4 days of week
df["leftover"] = (df["avg"] - np.floor(df2["avg"]) ) * 4

# We create a function, in which we will store in a list
# the working hours for each day, adding the leftovers in the 5th day.
# The elements of the list are tuples following the format (<working-hours>, <nth-day>)
def days_list(row):
    days = [(np.floor(row["avg"]), i+1) for i in range(4)]
    days.append((np.floor(row["leftover"] + row["avg"]), 5))
    return days

df["list_of_days"] = df.apply(lambda row: days_list(row), axis=1) # applying the function

# We explode the column 'list_of_days' so as to have a row for each tuple
df = df.explode("list_of_days")

# Finally, we unzip the values of each tuple in the 2 columns 'Hours' & 'Days' accordingly.
df['Hours'], df['Days'] = zip(*df["list_of_days"])

保留我们需要的列并打印Dataframe：

final_df = df[["User", "Task", "Hours", "Days"]]
final_df

| 使用者|任务|小时数|天数|
| - -----|- -----|- -----|- -----|
| 约翰|T1| 1.0| 1|
| 约翰|T1| 1.0| 2|
| 约翰|T1| 1.0| 3|
| 约翰|T1| 1.0| 4|
| 约翰|T1| 4.0| 5个|
| 约翰|T2| 6.0| 1|
| 约翰|T2| 6.0| 2|
| 约翰|T2| 6.0| 3|
| 约翰|T2| 6.0| 4|
| 约翰|T2| 8.0| 5个|
| 亚历克斯|A1| 8.0| 1|
| 亚历克斯|A1| 8.0| 2|
| 亚历克斯|A1| 8.0| 3|
| 亚历克斯|A1| 8.0| 4|
| 亚历克斯|A1| 8.0| 5个|
| 鲍勃|B1| 3.0| 1|
| 鲍勃|B1| 3.0| 2|
| 鲍勃|B1| 3.0| 3|
| 鲍勃|B1| 3.0| 4|
| 鲍勃|B1| 4.0| 5个|