Fill a table based on a date range and user input in pandas-CodePudding

I need to automate a table in python that does some simple things. The table has 4 columns (TRAVEL_AGENT, DATE, ROOM_TYPE, ROOM_PRICE). I need a simple script that asks the user for the travel agent, room type and room price and start and end date. I'm stuck at using a date range to insert rows to the table.

Eg. I need dates from 1/4 till 10/5

Travel_Agent	Date	Room_Type	Room_Price
A	1/4/22	DBL	30
A	2/4/22	DBL	30
A	10/5/22	DBL	30

CodePudding user response：

You can use date_range, something like this:

import pandas as pd 

df = pd.DataFrame(
    data={"Date": pd.date_range(start="4/1/2022", end="5/10/2022", freq="d"), "Room_Type": "DBL", "Room_Price": 30, "Travel_Agent": "A"}
)

That will initialize the data as you have above (assuming the date format is inverted)

output:

         Date Room_Type  Room_Price Travel_Agent
0  2022-04-01       DBL          30            A
1  2022-04-02       DBL          30            A
2  2022-04-03       DBL          30            A
3  2022-04-04       DBL          30            A
4  2022-04-05       DBL          30            A
...

CodePudding user response：

Is this what you are trying to accomplish?

name = input('TRAVEL_AGENT')
room_type = input('ROOM_TYPE')
room_price = input('ROOM_PRICE')
date_start = input('Date Start YYYY-MM-DD')
date_end = input('Date End YYYY-MM-DD')
df = pd.DataFrame({
    'TRAVEL_AGENT' : [name, name],
    'ROOM_TYPE' : [room_type, room_type],
    'ROOM_PRICE' : [room_price, room_price],
    'DATE' : [date_start, date_end]
})
df = (df.set_index('DATE').groupby(['TRAVEL_AGENT', 'ROOM_TYPE', 'ROOM_PRICE']).apply(lambda x: x.asfreq('d', fill_value=0))).drop(['TRAVEL_AGENT', 'ROOM_TYPE', 'ROOM_PRICE'], axis = 1).reset_index()
df