# 10 examples of 'bins in histogram python' in Python

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``3def bin(X, binsize = 1):4    """Split X into bins and return the average of each bin as a new set of5    measurements."""6    if binsize == 1:7        return X;8    else:9        extra = 0 if pl.size(X, axis = 0) % binsize == 0 else 110        dims = [i for i in pl.shape(X)]11        dims[0] = dims[0] / binsize + extra12        dims = tuple(dims)13        X_binned = pl.zeros(dims)1415        for i in xrange(pl.size(X_binned, axis = 0)):16            X_binned[i] = pl.mean(X[i * binsize:(i + 1) * binsize], axis = 0)1718        return X_binned``
``160def bin(X, nbins=20):161    equa0 = (X <= 0.0)162    equa1 = (X >= 1.0)163164    binned = []165166    groups = range(nbins+1)167    for g1, g2 in zip(groups, groups[1:]):168        l, u = g1/float(nbins), g2/float(nbins)169        binned.append((l < X) & (X <= u))170    retval = np.concatenate([equa0, equa1] + binned, axis=1)171    return retval``
``9def py_histogram(int_vec):10    11    hist = {}12    for val in int_vec:13        hist[val] = 1 + hist.get(val, 0)1415    return hist``
``4def histogramValues(values):5    counts, binEdges = histogram(values, bins=40, density=True)6    ys = list(counts)7    xs = []8    for i in range(len(binEdges) - 1):9        xs.append((binEdges[i] + binEdges[i + 1]) / 2)10    return xs, ys``
``107def bins(self):108    raise NotImplementedError("bins is not implemented")``
``48def plot_histogram(values, num_bins=100):49    """50    Generates a plot of the histograms of grasps by probability of force closure51    """52    bin_edges = np.linspace(np.min(values), np.max(values), num_bins+1)53    plt.figure()54    n, bins, patches = plt.hist(values, bin_edges)``
``23def calculate_histogram(data, bins: int, signal: str):24    stats = data.statistics['signals'][signal]25    maximum, minimum = stats['max']['value'], stats['min']['value']26    width = 3.5 * np.sqrt(stats['σ2']['value']) / (data.sample_count ** (1. / 3))27    num_bins = bins if bins > 0 else ceil((maximum - minimum) / width)28    hist = None29    bin_edges = None3031    for data_chunk in data:32        if bin_edges is None:33            hist, bin_edges = np.histogram(data_chunk['signals'][signal]['value'],34                                           range=(minimum, maximum), bins=num_bins)35        else:36            hist += np.histogram(data_chunk['signals'][signal]['value'], bins=bin_edges)[0]3738    return hist, bin_edges``
``127def fast_hist(a, b, n):128    k = (a >= 0) & (a < n)129    return np.bincount(n * a[k].astype(int) + b[k], minlength=n**2).reshape(n, n)``
``84def hist(data, title='histogram', bins=10, **args):85    histFig = pyecharts.charts.Bar()86    histFig.set_global_opts(title_opts=opts.TitleOpts(title=title))87    y, x = np.histogram(data, bins=bins)88    x = x.astype(int).astype(str)89    xlabels = [x[i - 1] + '-' + x[i] for i in range(1, len(x))]90    histFig.add_xaxis(xlabels)91    histFig.add_yaxis(data.name, y.tolist(), **args)92    result = histFig.render_notebook(93    ) if Config['return_type'] == 'HTML' else histFig94    return result``
``154def _histogram(image,155               min,156               max,157               bins):158    """159    Delayed wrapping of NumPy's histogram160161    Also reformats the arguments.162    """163164    return numpy.histogram(image, bins, (min, max))[0]``