如何在不获得空值的情况下创建数据帧？

问：

我一直在使用一种算法，并且也获得了所需的输出，但是当我尝试将两个输出转换为特定的数据帧时，我总是收到空的数据帧，谁能告诉我哪里出了问题？我只想将这两个输出列表及其数据保存在单独的数据帧中。正如您在我的输出中看到的那样：推荐酒店有一个列表，所有其他酒店都有一个列表，我想要两个单独的数据帧，仅此而已。谢谢。

import pandas as pd


def recommend_hotels(data, weights):

  df = pd.DataFrame(data)

  # Ask the user for the passenger count
  passenger_count = int(input("Enter the number of passengers: "))

  # Calculate the minimum number of rooms needed
  min_rooms_needed = passenger_count

  # Calculate the difference between total room availability and the passenger count
  df['room_diff'] = df['total_rooms'] - min_rooms_needed

  # Filter hotels with higher availability than the passenger count and sort by room availability in ascending order
   df = df[df['room_diff'] >= 0].sort_values(by='total_rooms')

  # If there are no hotels with higher availability, sort by room availability in ascending order
  if df.empty:
    df = data.copy()
    df = df.sort_values(by='total_rooms')

  # Initialize variables to track room assignments
  assigned_rooms = []
  remaining_passengers = passenger_count

  # Assign double rooms first
  for index, row in df.iterrows():
    double_rooms_available = row['double_rooms']
    if double_rooms_available > 0:
        assigned_double_rooms = min(double_rooms_available, remaining_passengers // 2)
        remaining_passengers -= assigned_double_rooms * 2
        assigned_rooms.append((row['hotel_name'], assigned_double_rooms, 'double'))

  # Assign single rooms if needed
   for index, row in df.iterrows():
    if remaining_passengers > 0:
        single_rooms_available = row['single_rooms']
        assigned_single_rooms = min(single_rooms_available, remaining_passengers)
        remaining_passengers -= assigned_single_rooms
        assigned_rooms.append((row['hotel_name'], assigned_single_rooms, 'single'))

  # Recommend hotels based on room assignments
    recommended_hotels = [hotel[0] for hotel in assigned_rooms]

  # Calculate the total number of rooms to book for all passengers
  total_rooms_to_book = min_rooms_needed

  # Create a DataFrame for recommended hotels
   recommended_hotels_df = 
 df[df['hotel_name'].isin(recommended_hotels)].sort_values(by='total_rooms', ascending=False)
recommended_hotels_df
# Print the initial recommendations
print(f"Recommended Hotels: {', '.join(recommended_hotels)}")
print(f"Book {total_rooms_to_book} rooms for {passenger_count} passengers.")

# List unrecommended hotels in descending order of room availability
unrecommended_hotels = set(data['hotel_name']) - set(recommended_hotels)

if unrecommended_hotels:
    unrecommended_df = df[df['hotel_name'].isin(unrecommended_hotels)].sort_values(by='total_rooms', ascending=False)
    #print(f"\nUnrecommended Hotels (Not in Recommended List) in Descending Order of Availability:")
    for index, row in unrecommended_df.iterrows():
        print(f"{row['hotel_name']} - Total Rooms: {row['total_rooms']}")

# List all other hotels that are not in the recommended list
other_hotels = set(data['hotel_name']) - set(recommended_hotels)

print(f"\nAll Other Hotels (Not in Recommended List): {', '.join(other_hotels)}")

# Create a DataFrame for all other hotels that are not in the recommended list
other_hotels_df = df[df['hotel_name'].isin(other_hotels)]

# Define your data and weights
 data = {
'hotel_name': ['A', 'B', 'C', 'D', 'E'],
'single_rooms': [10, 25, 8, 12, 7],
'double_rooms': [35, 18, 44, 110, 6],
'total_rooms': [45, 43, 52, 122, 13],
 }

 weights = {
 'num_hotels': 0.35,
 'transport': 0.3,
 'room_price': 0.15,
 'meals': 0.1,
 'availability': 0.075,
 'rooms': 0.025,
}
other_hotels_df


# Call the recommend_hotels function with your data and weights
recommend_hotels(data, weights)

我得到的输出是：

我尝试的是：

other_hotels = set(data['hotel_name']) - set(recommended_hotels) # 
   
other_hotels_df =df[df['hotel_name'].isin(other_hotels)].sort_values(by='total_rooms', ascending=False). 

预期输出：

Recommended_df:
 |hotel_name |single_rooms |double_rooms |total_rooms|
 |B|25|18|43|
 |A|10|35|45|
 |C|8|44|52|
 |D |12|110|122|



UnRecommended_df:
 |hotel_name |single_rooms |double_rooms |total_rooms|
 |E|7|6|13|