Is it possible to take the mean of hourly data to get a daily data I would like to work with hourly recorded data. I would like to convert it to daily data. I am thinking of taking the mean of each day. However, I am not sure if this is correct or no?
Any help, please?
 A: You can build a model at the hourly level and forecast the next N hours for the next K days 
If there are hidden/latent anthropormorphic effects such as day-of-the-week effects , day-of-the-month effects they may be detectable. If there are deterministically significant seasonal effects i.e.monthly effects they may be detectable and used with assumptions. If there are level shifts or local  time trends or anomalies they may be detectable.
Only your data knows for sure. You might search on SE https://stats.stackexchange.com/search?q=user%3A3382+hourly for more discussions about hourly data.
A: You can do that, calling it as a smoothing (moving average) process (please, don't confuse this meaning of moving average with the one related, for example, to ARMA process).
It worth noting that if you have 240 hourly data, this process give you only 10 daily data points. Are they enought? Good. If not, there is another way.
Depending on your task, you could preserve the initial number of observation in your sample by using a rolling window to average: 


*

*take the mean of the first 24 observations (1st to 24th), which is the first daily data point;

*take the mean of the "second" 24 observations (not from 25th to 48th, but from the 2nd to 25th) to obtain the second data point;

*and so on...

