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#Bokeh movie netflix Patch
#Bokeh movie netflix full

We also can see that India and China and india both have a good amount of titles but India far surpasesĬhina while having a smaller population, maybe the reasoning for why that is something we can explore.

So this by proximity would increase the number for mexico and canada.

America is the main location for producing movies ( which makes sense netflix is american based company).

Now by looking at the map and also the bar chart we can identify a few things show ( p ) createFrequencyMap ( dfFinal, 'Countr圜ode', 'frequency', 'Number of Netflix Titles Per Country' ) add_layout ( color_bar, 'right' ) #Display figure inline in Jupyter Notebook. patches ( 'xs', 'ys', source = geosource, fill_color =, line_color = 'black', line_width = 0.2, fill_alpha = 1 ) #Specify figure layout.

#Bokeh movie netflix Patch

grid_line_color = None #Add patch renderer to figure. p = figure ( title = title, plot_height = 500, plot_width = 1000, toolbar_location = None ) p. color_bar = ColorBar ( color_mapper = color_mapper, label_standoff = 10, width = 10, height = 400, border_line_color = None, location = ( 0, 0 ), orientation = 'vertical' ) #Create figure object. color_mapper = LogColorMapper ( palette = palette, low = min ( data ), high = max ( data )) #Create color bar. palette = palette #Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors. palette = brewer #Reverse color order so that dark blue is highest obesity. geosource = GeoJSONDataSource ( geojson = json_data ) #Define a sequential multi-hue color palette. dumps ( merged_json ) #Input GeoJSON source that contains features for plotting. merge ( data, left_on = 'country_code', right_on = nameOfColumnForCountr圜ode ) merged_json = json. This hit sitcom follows the merry misadventure.ĭef createFrequencyMap ( data, nameOfColumnForCountr圜ode, frequenc圜olumnName, title = "Default Title" ): shapefile = './GeoShapeFile/ne_110m_admin_0_countries.shp' #Read shapefile using Geopandas gdf = gpd. Jennifer Aniston, Courteney Cox, Lisa Kudrow. Set during the Russian Revolution, this comic. Nursery rhymes and original music for children.Ī Young Doctor's Notebook and Other Storiesĭaniel Radcliffe, Jon Hamm, Adam Godley, Chris. With the help of three human allies, the Autob. Peter Cullen, Sumalee Montano, Frank Welker, J. Jandino Asporaat riffs on the challenges of ra. Alan Marriott, Andrew Toth, Brian Dobson, Cole.īefore planning an awesome wedding for his gra.

So next time you need a film to watch on Netflix, pick one of these 13 options and prepare for some serious LOLs.

Either way, you'll likely find yourself absolutely wanting more of these movies that make no sense.

Yet that's a shame, because some of these films are seriously entertaining, even if you won't be sure while watching if you think the movie is actually pretty good or just wacky AF.

#Bokeh movie netflix full

Netflix is full of unique movies that people often overlook when choosing what to watch. Whatever the case, these 13 movies on Netflix are so ridiculous you won't be able to stop talking about them long after the credits roll. Some of these works are silly because they feel far from reality, while others just feature absolutely hilarious scenarios. And mixed into all of the options are a handful of films with ridiculous storylines, movies you can tell from the outset that you're going to totally obsess over. When you're scrolling through Netflix trying to decide what movie to watch, you're prompted with tons of different choices, from low-key indies to Academy Award-winning dramas.