How can the bin width affect the shape of a histogram?
The bin width (and thus number of categories or ranges) affects the ability of a histogram to identify local regions of higher incidence. Too large, and you will not get enough differentiation. Too small, and the data cannot be grouped.
A good histogram will show areas of higher incidence of a parameter that may help us to identify causative factors in a system. Thus, inappropriate bin size will defeat the purpose of the histogram. The extremes may help visualize the effect. ONE 'bin' only shows the population or total sample size. A 'bin' for each sample point gives us no more information, but only stretches the width of the chart.
A good bin width will usually show a recognizable normal probability distribution curve, unless the data is really multi-modal. Then there could be two or more distinct 'humps' in the histogram chart.