Enhancement: allow iterating signals in chunks of dataframes

I'm using the new to_dataframe() function that was implemented in https://github.com/MIT-LCP/wfdb-python/pull/380

One issue that I'm seeing is that when loading some of the waveform signals from https://physionet.org/content/mimic3wdb-matched/1.0/ using to_dataframe() it eats up a lot of memory. Specifically, on the machine I'm running on which has 96gb of memory, reading the record and calling to_dataframe runs out of memory.

I would like to lazy load the signal data into a chunked dataframe which would allow me to process the waveform signals in parts that could fit into memory, rather than loading it all into memory.

Inizia dall’implementazione di to_dataframe() introdotta nella pull request 380 e verifica come carica attualmente i segnali di forma d’onda. Definisci un approccio per l’elaborazione lazy e a blocchi dei dataframe che eviti di caricare l’intero segnale in memoria; il lavoro è completo quando record di grandi dimensioni, come quelli di MIMIC-III, possono essere elaborati in parti delle dimensioni della memoria disponibile.