Always start from the histogram, any non-parametric density estimation methods are essentially fancier versions of a histogram.
Compare the problem of choosing and optimal size of bins in histogram with choice of h in kernel estimator
The point of the exercise is to reveal all features of data; and that what important to keep in mind.
And now take a look at a perfect application of the idea in
Nissanov, Zoya, and Maria Grazia Pittau. “Measuring changes in the Russian middle class between 1992 and 2008: a nonparametric distributional analysis.” Empirical Economics 50.2 (2016): 503-530.
Going back to advice: keep in mind that you doing it to reveal features of data and it has to be strictly more informative than a histogram, otherwise the computational costs are not justified.
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