plt.hist(x1, **kwargs);

As an AI language model, I can provide you with an explanation of the `plt.hist()` function and its parameters, but I cannot execute the code or provide the `kwargs` parameter since it is not specified in the question.

`plt.hist()` is a function from the Matplotlib library in Python that creates a histogram of a given dataset. The basic syntax for using this function is:

plt.hist(x, bins=None, range=None, density=False, cumulative=False, bottom=None, histtype='bar', align='mid', orientation='vertical', rwidth=None, log=False, color=None, label=None, stacked=False, normed=None)

where `x` is the input data (list or array of values), and the other parameters are optional and control various aspects of the histogram. Here's a brief explanation of some of the most commonly used parameters:

- `bins`: the number of bins (or intervals) to use in the histogram. If not specified, Matplotlib will choose a default value based on the data.
- `range`: the range of the histogram bins. If not specified, the range will be determined by the minimum and maximum values in the data.
- `density`: if True, the histogram is normalized to form a probability density, so that the area under the histogram equals 1.
- `cumulative`: if True, the histogram is cumulative (shows the distribution up to each bin), rather than a count of values in each bin.
- `histtype`: the type of histogram to draw, either 'bar' (vertical bars), 'barstacked' (stacked bars), 'step' (unfilled line), or 'stepfilled' (filled line).
- `color`: the color of the histogram bars or lines.
- `label`: a string label for the histogram, which can be used in a legend.

The `kwargs` parameter in the original question refers to any additional keyword arguments that can be passed to the `plt.hist()` function, such as `alpha` (transparency of the bars), `edgecolor` (color of the bar edges), or `weights` (array of weights for each data point).