4 examples of 'pandas hist title' in Python

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def plot_hist(axes, data, xlabel=None, log=False, avg=True, median=True, bins=None, **kwargs):
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    time_max = max(data)
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    time_min = min(data)
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    time_avg = np.average(data)
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    time_median = np.median(data)
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    if bins is None:
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        bins = time_max - time_min + 1
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    hist = axes.hist(data, bins=bins, log=log, **kwargs)
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    if avg:
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        axes.axvline(x=time_avg, alpha=0.7, linestyle="dotted", color="blue", label="avg = {}".format(time_avg))
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    if median:
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        axes.axvline(x=time_median, alpha=0.7, linestyle="dotted", color="green", label="median = {}".format(time_median))
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    axes.set_ylabel("count" + ("\n(log)" if log else ""))
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    axes.set_xlabel("time" if xlabel is None else xlabel)
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    axes.xaxis.set_major_locator(ticker.MaxNLocator())
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    if avg or median:
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        axes.legend(loc="best")
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    return hist

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def fig_hist(da, bins, title, condi=None, outside=(False, True),
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             colors=('#8ecbad', '#b3ffd9')):
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    density, edges = dens_hist(da, bins, outside)
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    if condi is None:
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        fig = draw_hist(edges, density)
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    else:
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        density2, edges2 = dens_hist(da[condi], bins, outside)
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        bar1 = go.Bar(
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            y=edges2, x=density2, orientation='h',
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            marker=dict(color='black', line=dict(color='black'))
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        )
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        bar2 = go.Bar(
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            y=edges, x=density, orientation='h',
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            marker=dict(
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                color='rgba(0,0,0,0)',
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                line=dict(color='white', width=1)
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            )
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        )
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        fig = go.Figure(data=[bar1, bar2])
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        density = density2
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        edges = edges2
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    format_hist(fig, bins, edges, density, title, outside, colors)
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    return fig

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def compare_hist(hist, bins, like, x, figname, discrete=False):
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    """Plot and save a figure comparing the histogram with the
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    probability.
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    :Parameters:
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      - `samples`: random variables.
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      - `like`: probability values.
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      - `bins`: histogram bins.
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      - `x`: values at which like is computed.
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      - `figname`: Name of figure to save.
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    """
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    ax = P.subplot(111)
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    width = 0.9*(bins[1]-bins[0])
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    ax.bar(bins, hist, width)
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    P.setp(ax.patches, alpha=.5)
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    if discrete:
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        ax.plot(x, like, 'k', linestyle='steps')
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    else:
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        ax.plot(x, like, 'k')
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    P.savefig('figs/' + figname)
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    P.close()

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def pandas_group_hist_plot(df, var, group, x_name, y_name, folder='figures', save=True):
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    plt.figure(figsize=(8, 5))
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    g = sns.FacetGrid(df, hue=group, height=5, aspect=1)
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    g.map(sns.distplot, var)
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    g.add_legend()
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    plt.xlabel(x_name)
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    plt.ylabel(y_name)
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    plt.tight_layout()
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    if save:
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        plt.savefig("{0}/{1}_hist.pdf".format(folder, y_name), format="pdf")
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    else:
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        plt.show()
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    plt.close()