Spaces:
Sleeping
Sleeping
| from vega_datasets import data | |
| from scipy import stats | |
| from bokeh.plotting import figure | |
| from bokeh.models import ColumnDataSource | |
| import panel as pn | |
| import numpy as np | |
| # Tell banel to use Bokeh | |
| pn.extension() | |
| # Get the data | |
| source = data.movies() | |
| temp = sorted(source['IMDB_Rating'].dropna().values) | |
| # compute an initial number of bins | |
| n_int_bins = int(np.ceil(max(temp))+ 1 - np.floor(min(temp))) | |
| # define a function that takes the parameters and creates the plot | |
| def create_plot(bandwidth=1.0, bins=n_int_bins): | |
| plot = figure(width=300, height=300, toolbar_location=None) | |
| # Compute the histogram with the specified number of bins | |
| hist, edges = np.histogram(temp, bins=bins) | |
| # normalize and plot it | |
| hist = hist / hist.sum() | |
| quad = plot.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:], | |
| fill_color="grey", line_color="white", alpha=0.5) | |
| # Compute the density with the specified bandwidth | |
| kernel = stats.gaussian_kde(temp, bw_method=bandwidth) | |
| x = np.linspace(min(temp), max(temp), 100) | |
| y = kernel(x) | |
| col_source = ColumnDataSource(data=dict(x=x, y=y)) | |
| line = plot.line('x', 'y', source=col_source, alpha=1.0, width=2) | |
| return plot | |
| # Create widgets for the bandwidth and number of bins | |
| bw_widget = pn.widgets.FloatSlider(name="Bandwidth", value=1.0, start=0.03, end=2.0, step=0.02) | |
| bins_widget = pn.widgets.IntSlider(name="Number of Bins", value=n_int_bins, start=1, end=n_int_bins*10) | |
| # bind the sliders to the plotting function | |
| bound_plot = pn.bind(create_plot, bandwidth=bw_widget, bins=bins_widget) | |
| # Combine everything together | |
| first_app = pn.Column(bw_widget, bins_widget, bound_plot) | |
| first_app.servable() |