Numpy具有专用函数，用于以您需要的方式创建直方图:

Numpy has a dedicated function for creating histograms the way you need to:

histogram(a, bins=10, range=None, normed=False, weights=None, new=None)

您可以像这样使用

(hist_data, bin_edges) = histogram(my_array[:,0], weights=my_array[:,1])

此处的关键点是使用weights参数:每个值a[i]都会对直方图贡献weights[i].示例:

The key point here is to use the weights argument: each value a[i] will contribute weights[i] to the histogram. Example:

a = [0, 1]
weights = [10, 2]

在x = 0时描述10点，在x = 1时描述2点.

describes 10 points at x = 0 and 2 points at x = 1.

您可以使用bins参数设置垃圾箱的数量或垃圾箱限制(请参阅

You can set the number of bins, or the bin limits, with the bins argument (see the official documentation for more details).

然后可以使用以下类似的方式绘制直方图:

The histogram can then be plotted with something like:

bar(bin_edges[:-1], hist_data)

如果您只需要进行直方图 plot ，则类似的 hist()函数可以直接绘制直方图:

If you only need to do a histogram plot, the similar hist() function can directly plot the histogram:

hist(my_array[:,0], weights=my_array[:,1])