I have an audio file sampled at 44 kbps and it has a few hours of recording. I would like to view the raw waveform in a plot (figure) with something like matplotlib (or GR in Julia) and then to save the figure to disk. Currently this takes a considerable amount of time and would like to reduce that time. 
What are some common strategies to do so? Are there any special circumstances to consider on approaches of reducing the number of points in the figure? I expect that some type of subsampling of the time points will be needed and that some interpolation or smoothing will be used. (Python or Julia solutions would be ideal but other languages like R or MATLAB are similar enough to understand the approach.)
Assuming that your audio file has a sample rate of 44 kHz (which is the most common sampling rate), then there are 60*60*44_000 = 158400000 samples per hour. This number should be compared to a high-resolution screen which is ~4000 pixels wide (4k resolution). If you would print time series with a 600 dpi printer, 1 hour would be 60*60*44_000 / (600 * 2.54 * 100) = 1039 meters long if every sample should be resolved. (so please don't print this :-))
Instead have a look at PyPlot.jl functions psd (power spectral density) and specgram (spectrogram) which are often used to visualize frequencies present in an audio recording.
How to plot a very large audio file with low latency and time to save file?