Getting resampled data even if target time is not finished

Question

I am trying to resample '5m' data into a '240m' data. However when I resample, with this code:

import yfinance as yf
from dateutil.relativedelta import relativedelta
import datetime

ticker ='tsla'
df = yf.download(tickers=ticker, start=datetime.datetime.now()-relativedelta(days=30), end= datetime.datetime.now(), interval="5m", progress = False)

t4h = df.resample('240min').mean().dropna() 

This will produce more data like this :

                                  Open         High  ...    Adj Close         Volume
Datetime                                             ...                            
2022-02-28 08:00:00-05:00   852.525315   857.157102  ...   854.357377  564232.666667
2022-02-28 12:00:00-05:00   862.665577   864.999358  ...   862.596879  289393.666667
2022-03-01 08:00:00-05:00   869.184041   872.438151  ...   869.149200  466986.633333
2022-03-01 12:00:00-05:00   864.464479   866.511848  ...   864.564774  208426.895833

What i want to understand is if there is a way for it to be resampled as such so that even if 12:00 is not yet but given the data which is available, to get the next 1 resample time. Trading softwares let you see the candle price which is not yet completed. So one can see the 2h candle event though it has 1 hour left for it to be completed. I am trying to do the same with pandas.

At the time of writing this question it was 2:15 PM in new york. However if i resample this data, the last data I have is for 1 PM. :

2022-03-29 13:00:00-04:00  1097.674362  1099.311020  ...  1098.094414  146068.187500

Even though on a '5m' resolution there is data for :

2022-03-29 14:14:40-04:00  1100.609985  1100.609985  ...  1100.609985        0

What can I do so that i can get the next 1 resample even if it is not completed or reached target time of resample.

Any help would be appreciated!

===Edit===

As suggested by @Jezrael I have changed the ticker to acc.ns since US market is closed and there is no lower resolution data available.

t4h = df.resample('240min').mean().dropna().ffill()

last line is :

2022-03-30 08:00:00+05:30 2157.858836 2160.852941 ... 2158.283828 8992.705882

so the last sample time is 08:00:00+05:30

t4h = df.resample('240min').mean().dropna().bfill()

produces:

2022-03-30 08:00:00+05:30  2157.841187  2160.835291  ...  2158.298534    9016.617647

again the last sample time is 08:00:00+05:30

But in df with 5m interval the last time index available is 11:58:49+05:30

2022-03-30 11:58:49+05:30  2153.949951  2153.949951  ...  2153.949951       0

Thus what I wanted was to have a resample data in df of the next resample which will happen on 2022-03-30 12:00:00+05:30 based on the average data available even though it its not 12:00 and thus is incomplete for the resample.