| notebook.community (2024)

Now that we have Bokeh loaded it is time to build the plot. There's a lot going on in the next notebook cell, but each piece is relatively straightforward; I'll try to explain what is going on in each chunk of code.

First we need some colour. We can use the clusters for that, but that means we need to map cluster numbers to colours and reserve gray for noise points. We can construct a palette and then use the LinearColorMapper for this. There is also some code to set a fill_alpha value which we will come back to later.

Next we create a ColumnDataSource. This just connects up our dataframe with bokeh so it can embed data (like the names of the subreddits!) directly in the html for the plot (and not have to round trip back to Python to get that information). We also have some custom javascript for handling alpha values -- again, we'll come back to this.

The next step is to create a figure to plot to, and then add a hover tool (which we wire up to display the subreddit and cluster). We then add circles to the figure, taking x, y and color values for the circles from the ColumnDataSource we created. Then there is some custom callbacks which we'll skip over for now, and the rest, prior to show(plot) is just customising the display style a little.

The result is a scatterplot, colored by cluster, which we can zoom and pan around in, complete with tooltips. The plot itself is pure html and javascript, and we can embed it in a webpage independent of any Python -- it is standalone at this point.

One catch is that we set a fairly low alpha channel level (the translucency of points) so that we can see dense areas when zoomed out due to all the overplotting of points. If we were to zoom in while keeping that same alpha channel all the points would be very pale and hard to see. I was expecting that fixing this would be a very difficult task -- how does one dynamically alter the alpha value as you zoom in? It turns out to be surprsingly straightforward in Bokeh. By adding a fill_alpha value to the dataframe (and hence the ColumnDataSource) we can set the alpha value from the ColumnDataSource. Bokeh also let's us add custom callbacks when the zoom level changes, so we simply update the alpha values based on the bounds of the zoomed area.

In[16]:
 # Construct a color palette and map clusters to colorspalette = ['#777777'] + plasma(cluster_ids.max())colormap = LinearColorMapper(palette=palette, low=-1, high=cluster_ids.max())color_dict = {'field': 'cluster', 'transform': colormap}# Set fill alpha globallysubreddit_map_df['fill_alpha'] = np.exp((subreddit_map.min() - subreddit_map.max()) / 5.0) + 0.05# Build a column data sourceplot_data = ColumnDataSource(subreddit_map_df)# Custom callback for alpha adjustmentjscode=""" var data = source.data; var start = cb_obj.start; var end = cb_obj.end; alpha = data['fill_alpha'] for (i = 0; i < alpha.length; i++) { alpha[i] = Math.exp((start - end) / 5.0) + 0.05; } source.trigger('change');"""# Create the figure and add toolsbokeh_figure = figure(title='A Map of Subreddits', plot_width = 700, plot_height = 700, tools= ('pan, wheel_zoom, box_zoom,' 'box_select, resize, reset'), active_scroll=u'wheel_zoom')bokeh_figure.add_tools( HoverTool(tooltips = OrderedDict([('subreddit', '@subreddit'), ('cluster', '@cluster')])))# draw the subreddits as circles on the plotbokeh_figure.circle(u'x', u'y', source=plot_data, fill_color=color_dict, line_color=None, fill_alpha='fill_alpha', size=10, hover_line_color=u'black')bokeh_figure.x_range.callback = CustomJS(args=dict(source=plot_data), code=jscode)bokeh_figure.y_range.callback = CustomJS(args=dict(source=plot_data), code=jscode)# configure visual elements of the plotbokeh_figure.title.text_font_size = value('18pt')bokeh_figure.title.align = 'center'bokeh_figure.xaxis.visible = Falsebokeh_figure.yaxis.visible = Falsebokeh_figure.grid.grid_line_color = Nonebokeh_figure.outline_line_color = '#222222'# display the figureshow(bokeh_figure);

   
"}}; function display_loaded() { if (window.Bokeh !== undefined) { var el = document.getElementById("bf7f8fc6-d114-4492-8501-f885e82f4f48"); el.textContent = "BokehJS " + Bokeh.version + " successfully loaded."; } else if (Date.now() < window._bokeh_timeout) { setTimeout(display_loaded, 100) } } function run_callbacks() { window._bokeh_onload_callbacks.forEach(function(callback) { callback() }); delete window._bokeh_onload_callbacks console.info("Bokeh: all callbacks have finished"); } function load_libs(js_urls, callback) { window._bokeh_onload_callbacks.push(callback); if (window._bokeh_is_loading > 0) { console.log("Bokeh: BokehJS is being loaded, scheduling callback at", now()); return null; } if (js_urls == null || js_urls.length === 0) { run_callbacks(); return null; } console.log("Bokeh: BokehJS not loaded, scheduling load and callback at", now()); window._bokeh_is_loading = js_urls.length; for (var i = 0; i < js_urls.length; i++) { var url = js_urls[i]; var s = document.createElement('script'); s.src = url; s.async = false; s.onreadystatechange = s.onload = function() { window._bokeh_is_loading--; if (window._bokeh_is_loading === 0) { console.log("Bokeh: all BokehJS libraries loaded"); run_callbacks() } }; s.onerror = function() { console.warn("failed to load library " + url); }; console.log("Bokeh: injecting script tag for BokehJS library: ", url); document.getElementsByTagName("head")[0].appendChild(s); } };var element = document.getElementById("bf7f8fc6-d114-4492-8501-f885e82f4f48"); if (element == null) { console.log("Bokeh: ERROR: autoload.js configured with elementid 'bf7f8fc6-d114-4492-8501-f885e82f4f48' but no matching script tag was found. 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*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*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*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*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*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*cklX7CyR7AcLN4sTD0JcCIRncQO8MsQOOItfgUUBzABYcXRKQGBUD2QCswZBUdwB6M2CeA4ue/hssqbAaoKMDAkxYuq7AMQOeMKO0NXhPAm1YKgVzi4T/pYP2fw6wSQHEDPj+McADA4KEo0CeqI8CmRX2SO9wWQDwtP3CVlxhA1elA1lOr9b8mAWpq2boiQCmvldBdwihAnyEcs+xJxj8eF9UiotAxwDScMjffcC5A/fZ14JxBJ0BszVZe8p8fwOPfZ1w4UPo/jgWFQZnWFsDVBbzMsNETwInt7gG6/xxAN8e5TbiX8z+v7ILBNV8jwBztuOF3MxTAQlpj0AmBCMCUiVsFMYAXQGe3lslw/BXASBtHrMXnHMAhyhe0kMDxv7ubpzrk9hdAyzDuBtHiMcC4Wicuxyv3P3hHxmrznxVA+dhdoKSgFMDuBPuvc9PlP6tf6Xx4phnADMhe7/7YCUDHn6hsWPMgQH8zMV2IFS5AjUephCeUBUC2ZcBZSpYQwBo1XyUfWyfAlkIglzgSJ0AhzO1e7u8zwJaX/E/+diJA5DJuaqB56L/wT6kSZW/LPyHoaFVLKhtAO+RmuAHfEcDMtz6sN8oWwDl80okEU62/i1HX2vskKsDKplzhXa4YwCRCI9i4Xg/ASS9q96tAAcCQozmy8ksbwJDAH37+O/K/lnmrrkPFFMD1K50Pz6IWwPzkKEAUXBnAG0esxacAMEAE4+DSMZ8owGCt2jUhfRTAJuDXSBLUGMABMJ5BQx8RQIVE2safSB3AKm9HOC1oGsCERUWcTvIOwC9szVZeaiDA2o8UkWHVBMAlJNI2/kTsv18HzhlRmve/FlCop48sMsDWqfI9IxkzwDkqN1FL8+k/kxraAGygG8BmhLcHISAJwAaDa+7o/+C/ZTiez4AyJ0C6LZELzuC3v9mXbDzYUhjAIa6cvTM6BcDvyFht/l/nPx+DFada+xBAdSFWf4RhBcB0Q1N2+kEXQImxTL9E/Py/GjBI+rQaL0CDUrRyL0glwLPTD+oijSNAjWMke4SaoT/Pnzaq00EewPflzHaF/gzAn8coz7wcFEDo9LwbC8Y0QDnx1Y7iLBJAp+Zyg6GOBkBfKcsQxxoGwLN6h9uhkRNAN/qYDwg09T+Xdf9YiI7wPx13Sgfr/7A/ZMxdS8iPLEBrYoGv6FYhQLd6TnrfUCLA/pqsUQ8xBMBckgN2NXmiP8aIRKFlXeG/gXwJFRwuI0D+LJYi+Qr/v64s0VlmqSHAr1xvm6ngL0B1WOGWj4QGQNgPscHC3TDAj4tqEVHcEkACDqFKzX4AQLGnHf6aTAPA0a3X9KCg6b9ma32R0NYvwO25TE2CVwnAeJs3TgorI0AP7WMFv20FQO5cGOlFbe8/WoC21awLI8ABFY4glVIXwFJIMqt3yBhAcjRHVn4JEcD/d0SF6kYewDyDhv4JThRAz6RN1T1y/b+quHGL+bkcwDqSy39InxBAb0VighpeGsBYdVYL7NkkQMVx4NVy3yJAqN+Frdk6JkAw8UdRZy4JwOI8nMB0yilAuDzWjAwyHEA8iJ0pdC4RQFN1j2yuuhtADtsWZTY4GEArajANw48iwHbG98Wl5jDAhxQDJJqQEsCnID8budYwQIV4JF6eLgpA/3Vu2ozT17/uX1lpUmomwAlszsEzSTBAxJYeTfXkAkAyWdx/ZDoLQEPLun8sZAFARtJu9DG/CcCnXOFdLqIKwN83vvbM0idAkPgVa7hI6D+u9UVCW/4fQNKKbyh8DixARIXq5uKnNMC95H/yd18WQE59IHnn8AJAmu/gJw7YJMAaw5ygTa4FwDbIJCNnIfI/UMjO29jkNMDPaKuSyP4gwGJJufscH/q/lZuopbmdKUBWfhmMEQnqv8UgsHJoYStAm8qisIuKIcCVtrjGZ6oxwJXvGYnQiOE/F0UPfAxW6D8GvTeGAFggQBNFSN3ObhrAdF/ObFcgIcAMkGgCRWwdQLtE9dbA9i5AUDV6NUDpCUAVGohlM/cuwEPlX8sr1/Y/o3a/CvAlLUDy0eKMYQ7+vy1eLAyRgxvADkqYaftXur/EzalkAAAgQDOK5ZZW6yJAlfPF3ovv9T82yY/4FWvSv4eHMH4axzRAd4TTghd9zb8CgGPPnpsaQJhokIKn0AXAFvn1Q2xAI8AuymyQSU4hQGsQ5nYvRxfA4/xNKEQgE8DylNV0PdEFwHLdlPJaiRXAbcoV3uUCDcBGlWHcDSLjv4o8Sbpm4h/ARMGMKVhDBsDnGfuSjacWwJXVdD3RRRvAbCHIQQkz/L+c+GpHcUIwQBzvjozVRhhAgPEMGvqvKUDn4m97ggQJwC20c5oFoiFA5PkMqDcHMUCo/dZOlJQbwFZ/hGHAMhRAgXaHFAN0LsBEp+fdWMAWwOXTY1sGnP2/Zr6DnziACUD+ZIwPs3cfQIguqG+ZgyLAMbWlDvIaIMDXZ876lOP5P06aBkXzqCnAradWX131BEBv10tTBIAmwEfp0r8k1fI/2GX4TzewFcCu00hL5e2wv/xR1Jl7SBPAfO4E+6+LIUCN8WH2siUhQNU8R+S71B7ARML3/gZtBEDGTngJTj37v2poA7AB0QJAsqGb/YFyzz+nWDUIc+sewGvwvioXKtM/Wi4bnfOTEMCYhXZOs8DrP8qLTMCvgS9As+xJYHNWLEDeH+9VKzMfwE+Q2O4eoOe/kst/SL+dGsCbV3VWC2zlP3Nk5ZfBqBnAQfD49q7xLkBKJqd2htknwHfzVIfclCtAoFBPH4E/FkDjjjf5LeoiQExUbw1slee/e9rhr8niKMB4t7JEZykWQPUTzm4toxTALq2GxD2eK0D43t+gvVoWQG02VmKexRhA+aBns+oz8T/hlo+kpPcUQPaWcr7YexzAic+dYP/lEcDcgTrl0YUgwM5wAz4/jHC/NEdWfhkcHcBI+rSK/sASQCDVsN8TSxfAm6kQj8RjIEDj4xOy87YSwPuT+NwJTiRAww/Op47V4D9mTwKbc3DmP+vHJvkRlyJAou4DkNpEAkCj6exkcBQbwBa9UwH3/BbABHKJIw9E5D81ejVAaegDwLtE9dbAVs+/mSmtvyVwFMCatn9lpYkFwBIR/kXQqCDAih9j7lqCJEDjp3FvfkMAwF/uk6MAHTFAW5VE9kHWLsB/bJIf8WsZQBLAzeLFEhBAMshdhCnqDEAdcjPcgG8EwKw2/686iixAaXBbW3gmIMCLpN3oY14DQKX4+ITs/Pu/BoVBmUarIMAT1sbYCf8nwKbTug1qxyNA9dkB1xUTDcCfqkIDsYwvQMegE0IHBSxAkx6GVidnBcCnd/F+3P4SwO/Lme0K/R5Ac2a7Qh8MCMCnzw64rlAgQCB/aVGfBAjAs3kcBvOXFUDzyvW2meoDwDVFgNO7uBbA2ZWWkXr/GMBmh/iHLc0xQO5BCMiX8AnA/DkF+dncMEBET8qkhjYMwLG/7J48rBvAzvv/OGEC9D9F9dbAVgnbv8UDyqZcoShAbtxifm54HkBtAaH18EUjwP4ORYE+8QJAdcx5xr50HcDyzwziA1sbwIQQkC+hAgLAKji8ICK14j8zGvm84pkewAXB49u7pihA7+NojqwMEcC+M9qqJOoiQDeMguDx7Y2/6pYd4h82G8BZTdcTXacpQCy2SUVjTR7AogxVMZXeB8AxXvOqzqr+v2AeMuVD2CtAhEawcf27B8DABkSIK+cdwDyE8dO4fybAvma5bHQOI8BK7UW0HQsgQCCXOPJAJAVAZqNzfoozJUDp76XwoFkQwG4WLxaGSP6/x2Rx/5FpBMBM4UGz674EwO19qgoNtBnAP1JEhlX8AUBBuW3fo44VQJ4LI72ofRHA3KD2WzsBIMD4qL9eYdEVQKa4quy7IuA/Q+bKoNrgyL8TYFj+fJv0vyDT2jS2V+u/AYkmUMTSKsAc7E0Mycm8P9k9eVioNfo/bRyxFp+yI8DQmh9/aVEEwIXSF0LOe/C/UmStodSOLkCpL0s7NVfzv76ECg4vWBlA61bPSe8b9r/AJJUp5iDEvyh+jLlr4S9AxTvAkxbGJ0CB64oZ4Y0DwFg4SfPHlBhA53KDoQ7LGkC28pL/ye8wwORLqODwchTAHtydtdvuFMCJeyx96LooQDeJQWDlYCRA0uRiDKxjAsA8M8FwrjEeQBXI7Cx6NxrATG2pg7x+EMC2SUVj7U8JQFqAttWsOyxAiPaxgt/WK0BnDHOCNjnrPxU7Gof6/R/AhiFy+no+DMAw2uOFdMgVQBKhEWxcXyhA2GSNeohG5z+YofFEENcTwONsOgK4Wf0/LWACt+5OL0AJcHoX718iwJI9Qs2QKso/mIkipG4XFsB7a2CrBJsZwHdNSGsM6iLA7Q2+MJmCJsBCB13CodcgQLwDPGnhEgnAI9kj1Azp/r/8/s2LE9/uv6d2hqktdai/Km9HOC2MMEDKTj+oiwwxQNS19j5VhcI/73VSX5bGL8AplIWvr2UgwNOlf0kqU9y/MUEN38L6BcAC2IAIcS0qwJWBA1q6wiPAGT230JXwJ8DL1Y9N8qP3v6BvC5bqWiPAi3CTUWX4HsAqyqXxC+8lQMl2vp8azxZACqGDLuGQCcC139qJknASwIxMwK+R7C/A8Bge+1k0MUCHxahr7b0NwGWoiqn06yhA+yKhLeciI0A6kWCqmRUSwP3c0JSdfh/AQQsJGF3+GEBvnX+77KcewJHSbB6HYQzAcyzvqgdcG8DTFAFO76L/v8anABjPAAZAdLUV+8s+FUA0DvW7sGUmwLPTD+oiPSLANSbEXFJlGMD2J/G5E2QvQHqJsUy/fChAxCEbSBfDL8AYz6Chf+IhQN3rpL4szQbAMXpuoSuR9L/rcHSV7oYuwFHc8Sa/pRXAuCBblq8LGMBFLc2tEJb8v+xph78mGxjA2T15WKj1FMC6opQQrBogQIBjz57LNAbAQPz89+BVAsD4cMlxpxQiQOoHdZFCwSfAw9SWOsgLCkADJJpAESMywMFY38DkRg1At3wkJT3UL0BkraHUXoQYwOdR8X9HFAVAOPbsuUydJkArieyDLPscwGgfK/htkCbAXW+bqRBfHcBHrTB9r0EVwIQSZtr+1fq/wAMDCB/KC8ALfhtivKb4P+dUMgBU8QjAEK6AQj0dGEBbKJmc2gkVwG78icqGzS9AiPTb14H7M8Bo5zQLtLv6P18HzhlRWv6/cGByo8j6BMAzMzMzMxMDQJNuS+SCcxrAFkz8UdSZDMDwNJnxtlIWQIFDqFKz1y9A9DRgkPQpFEDekbHa/F8VwDQr24e8Ze8/JQNAFTeOE8ATC3xFt1YhQNiDSfHxqR/Ac6JdhZSfAUDp0r8klRkVQEyqtpvgGzBAtvP91HjJGcDbTfBN09cVQO+QYoBEswDAH7+36c++I8ApQX+hR+gwwEdWfhmMsQ7A4h3gSQtfJECwyK8fYmsjwPC/lezYeCRAQs77/zhh5j/YYUz6eyn1vzcawFsgUSDAR7Bx/bsWIcBN1xNdF34BQAtjC0EOOhtAlQ7W/znMDcCLh/ccWC4awEMfLGNDLybATn/2I0X8JEDBq+XOTNAuwLH9ZIwPYyLAx7ji4qhEJcBGelG7X4XsP7cos0EmeSnAeLMG76ty9D83OXzSiUTzP1hyFYvfhB9A1uJTAIwnCkDSqpZ0lDMWwAA8okJ1QxvA0lYlkX1gIUBqvko+dlchwPtbAvBPqf8/AHLChNHs/L+5iO/ErCcUQB0CRwINNgLAgxQ8hVzZMEBFnE6y1aUBwCqOA6+We/w/BduIJ7vxLkBKfVnaqTkGwBMn9zsUWTPA4IYYr3lV878VjiCVYofwv9jyyvW2iRHAAMRdvYqMtr98uU+OAiQEQHxCdt7GJg5A8fW1LjWaJUCrrkM1JXkAQI8X0uEhTPq/W+m12Vi5F0CWlpF6Tx0mQGIQWDm0+BJASP5g4LmXF0DOpiOAmwUawHqp2JjXyStA7PtwkBDFAcCco46Oq6EUwHycacL2E+K/mDJwQEt3DkCf6Lrwg6MjQAnh0cYRqwFAw4GQLGDyF0DW4H1VLkQXwKTBbW3hOfo/76tyofKvDUBJFFrW/SshwKTgKeRKvfQ/P+CBAYRP878XoG0160wLwJOnrKbrSQ/AxsA6jh+yLUD11sBWCWYfQFxV9l0RHBLAiGTIsfVsCcBfCaTEru29P3tNDwpKWS5AGjT0T3DpJECk4v+OqFDSP9aryOiApOY/pfeNrz1zCsCifhe2ZtsVwJJe1O5XAQDAX2BWKNI9EEDGpSptcY3rP1MhHomXBx/ArU1jey34GkDEW+ffLlMvQNcYdELoIPq/jnQGRl4W+r83NjtSfU8nQPCiryDNaBzAuYlamlupIcCjXBq/8FoUQAdeLXdmKiDArvNvl/069T8XZqGd04wVQLr4254giSLAS7A4nPnNK0D9ag4QzPEVwJxOstXlFOM/Kv9aXrle/D9zgctjzQgWwEN1c/G3fSVAuwopP6m2AEAnMJ3WbVDUv9IZGHlZvzTAkfP+P04Y7D+SJXMs70odQODW3TzVoe4/qUpbXOMzwT/ScTWyK90iQPsCeuHOtSDAh8Q9lj5087/LvFXXoXoZQPRvl/268wTAXOZ0WUxs9D8HB3sTQ1IMwHO9baZCHAXAdES+S6mbFMCveOqRBkcgwJeL+E7MuhTAn+V5cHdWBEB1AwXeyXchwAgEOpM21fK/hslUwajECUDb+uk/a54pwFQZxt0gmiFARSxi2GE8JcA6lnfVA2b6vw4TDVLwFO4/T5SERNrWGMCa0Y+GUwYBwOSeru5Y7OW/IAiQoWOnFUBhqS7gZcYaQDnsvmN4zC5Am6+Sj92FIMAIBaVo5f4pwHhflQuVDy1AA0GADB0LIUBaSSu+oWgwQPKZ7J+nsRJAqMXgYdorMcAKn62Dg3UqwIsXC0PkVB7AjdE6qpoAH8C6vaQxWvccQKiOVUrPlCxANc8R+S4lAMDcSUT4FyEPwKoOuRlu4BvAeESF6uaSKMAqHaz/c9gWwB8RUyKJbhrAXyUfuwuUzr/SHcTOFGoeQLWNP1HZuC9A+fTYlgGn9L+YMnBASxcEwMLdWbvtnjTAPWTKh6AyL8BwBn+/mD0gwBaE8j6OdhxA38FPHECvGECWIY51cUsgQC+ISE27WAXA5bUSuksCAsDy7V2DvhQsQE5hpYKKShFAjiPW4lOA/79UdCSX/5ATwO7qVWR0+CVAo+VAD7X9G0CPN/ktOgEjwNhjIqXZ5CHAqRJlbyn3HMDWrDO+L9YuQN5xio7kwhxARfRr66dPGcCg/rPmx38aQAmp29lXrhzA0a5Cyk9qGECaJQFqajkAwEJ3SZwVySxAcM/zp40KD0AhO29js6PxP56ayw2G2hPACvfKvFXHMEDZzYx+NOwewDP8pxso8Pu/LXjRV5DONMCU+UffpPkmQDnU78LWbMu/lpUmpaC7MUDyejApPs4aQKoqNBDLHiDAMGe2K/ShDUBJL2r3qwgpwMLfL2ZLlvs/+bt31JiALEAuH0lJD+MUQFdD4h5LTxrAOXtntFWZEECTUWUYd+svwHo3FhQGfSXADQBV3LglAcCpL0s7NQcgQPLvMy4cSBPA7+apDrnJIkBU46WbxOAuwAithy8TxQLAu9Vz0vs2JEA0Tdh+MkbjP6d2hqkt5RdAYU87/DWJE8CPcjCbAKskQPvqqkAtJgRAGTigpStY9D/Aety3WlcXwLkZbsDnh+w/YXE486u5+r8S2nIuxYUcwB0AcVevIgHAX5Z2ai63A0AwDcNHxNQRwFABMJ5BAx7Azhq8r8qFoj8B+n3/5oUawDi7tUyGSyPACCEgX0JlGUArMc9KWrEuQJYIVP8gUgRAdlH0wMfUMEBDklm9wz0qwDscXaW76+i/lbiOccUNIEBQ3zKny4opQLtCHyxj4w3AMVuyKsJtFMDzx7Q2je0JQHh/vFetNC/ApFUt6Sg3HMBXPzbJj7gvQIYBS65i8QFAzQTDuYYhKcDpt68D5ywYQOeqeY7I3yHAukxNgjdkBED2RUJbzqWgP5tY4Cu6tf+/bJOKxtrXMUBMbamDvI4VwPfpeMxAvStAgV1NnrIaGEBf0hito7ofwB6lEp7QmyPA1As+zckbKEACRwINNiUkQK1LjdDPVO4/2AsFbAfzFMANHTuoxPXpv41jJHuEcidAzVt1HapJDUBLVkW4yej1v2PVIMzt3uS/0H05s13JIMAH0zB8RBgwQNPddTbkn88/rrmj/+WaDUD9FMeBV8udv91bkZigPihAITzaOGItI8CMvRdftKcQwN0nRwGiQBjAGohlM4ek3D/aVrPO+BYgwHQHsTOFzuG/Xp1jQPbKMECTisba37kZwIF7nj9tZCDApwcFpWi1JsCgbMoV3pURwImbU8kAIBNAWJBmLJrO2L+3JXLBGTwAQFD7rZ0oaTBAhGbXvRWJ7j9MGM3K9pEfQJPJqZ1hqgDAONxHbk069D82IEJcOVMlQLcJ98q8lR9A9YHknUMpMsCbAwRz9LgDwEnYt5OIEApAp1oLs9C+F8AWak3zjjMgQGpoA7AB4SfAiSe7mdGLMEDdtBmnITojwK8I/reS5TTAyAvp8BCG+D82Hmyx22fpP8mRzsDIywHAgGH5823ByD9q3nGKjmTjP6X2ItqO0TFA6Sec3VqmIMDJdyl1ybghQJg0RuuooijAh6JAn8i7KcBm2CjrNxMYwFSOyeL+cxJAlsyxvKve8j8PQkC+hArgP9LhIYyfRvq/SFD8GHPX1j/Asz16wx0ZQLggW5avi/S/6Qq2EU9WGcCKVYMwt4snwGEaho+IMSFAmrSpukf2KEBzgGCOHlctQPWgoBStjB/AUyKJXkbBNMADQBU3bqksQPt3feasTxjA/I7hsZ8lEEDZCS/BqY/4P/oMqDejxhrAaK7TSEvlHMA3jliLT5kvQH7iAPp9f/o/tWytLxK6H0CJRQw7jAkGwOs4fqg0khPAlzYclgY+A0C4W5IDdjUvwA6eCU0SawLAi8Iuih7wIEAZBFYOLbK9Pxwj2SPUTBfAK8O4G0QbEECsHcU56hgQwAeaz7nblR5Ap+Zyg6HOD0AQyZBj6xmiP7g7a7ddaA7Ax2ZHqu/8IUBK7rCJzBzyv+nvpfCgWSLAMlab/1f9E8ADlfHvM/4ewJ1kq8spoRtA3e16aYpgGMANwXEZN60pQIcUAySaQOW/1CgkmdWjI8B+/nvw2g0iwKRskbQbZSbAH2rbMAqiC0BWt3pOeh//v4uNeR1xOCDAs82N6QnrC8CcFVETff4KwMBbIEHxY8y/coqO5PIf2r+ZRSi2gsYMQDT0T3CxIiBAcEG2LF/nEMCNCwdCsigiwDc0ZacfFCTAJTyh159E5j+eXinLEJccwO6VeauugxfAX7hzYaRHH8DrrYGtEizTv9/BTxxAf/e/g/xs5LrJBMDfG0MAcCz+v+W0p+ScWAHAUG9GzVe5E8B3nnjOFiAhwNI3aRoUPRnADFuzlZfME8DCS3DqAykbQCRkIM8un/A/JA7ZQLrENEAqjC0EOegOQMx6MZQT7SZAMqt3uB1aGsCLNse5TTAqwEllijkIKhbAl4xjJHs0FcAlsg+yLLgCwKJgxhSssRzAhsd+FksJIEDGFoIclHAUQKXXZmMlJhrA+13Ymq088T9QcRx4tdwVQAD+KVWijAnASuza3m5ZGUCA1vz4S4suwN9t3jgpjPa/skrpmV5i8r+OA6+WO3P/v+Xv3lFjEiFAeTpXlBKC6T8Cfo0kQbj5P6vrUE1JLiZAD2Q9tfpKCMAiiskbYAYwQBQH0O/7nyLAkq6ZfLMFIMAWwJSBAxoHwHf3AN2XoxVAjNgngGKcLEC3fCQlPSwfwOyGbYsyay9Abf5fdeR4GUBstBzooZ4lQH5wPnWsIiTA8bvplh3yKMBHdqVlpC4iwMTOFDqvqSTA1owMchc5JkBSDmYTYFjeP0+y1eWUgOw//UtSmWJO/D/+7bJfd2oUwOqu7ILBVRPAlnhA2ZRr8r9QjCyZY/kEwDntKTknXiZALGLYYUxKJcB1riglBEsBwK3ddqG5Dh/ADksDP6qRHkBweawZGZwhQDPcgM8PI/Q/2gJC6+HrDcB/TGvT2EYkQEyL+iR3WA5AaVIKur3k9782eF+VC/UPwHpwd9ZuQyLA9Pv+zYszE8DZzCGphYIawDVEFf4MTwRA0QSKWMTgHkCPjNXm/0UXwHaMKy6OGidA9tIUAU4vEsBLV7CNeMIvwBMoYhHDFiRAvTWwVYLVE0DW5ZSAmOQQwMQhG0gXQyHACVG+oIUkBcAlWvJ4Wq4XQMUdb/JbRBXAyJV6FoRyCcDChxIteZwNwCMw1jcwuRBAx0rMs5LWAMCOzY5U34kQwAYtJGB0+QXAAtTUsrXuJUD5TWGlgoqyv89oq5LIHhbA32+044bfpT+/tRMlIeUwwEELCRhd7iZAHmyx22fV+r9Qxvgwe5n0v1IQPL69a/I/5dGNsKioD0AaqIx/n4EmQPj578FrF/y/rVCk+zklBEAs1JrmHfcUQNB8zt2upxJAaEEo7+MYG8AZPbfQlYgTQCDSb18HziXAmnecoiP5DMDKh6Bq9OoJQJPJqZ1hIiJAxmte1VmNGECpEmVvKacEwEZe1sQCKzLAL4oe+Bh8H0AjMqzijQz/vz+sN2qFCQ1AfPKwUGta+z/o2EElrnc0wLtGy4EeygVAzLbT1ohgAkDoiHyXUl8nQKt3uB0a1gNAUWfuIeFDIUCsV5HRAckhQInPnWD//SRAURGnk2wNJkDK/Q5FgT7zv5J2o4/5QCLAyk4/qIvML0DIlA9B1agJQMSzBBkB9QHAnBcnvtqR9z8kXp7OFb0vQNIBSdi3yyNACmgibHh6BMBlNPJ5xRMHwJaVJqWg28O/nuv7cJAILMAgfv578NrTv9VeRNsxTSdAADYgQlxZGECcps8OuK7cv9hGPNnNvBbA2V2gpMByEEA50ENtG2YuwBWrBmFuLy5AdF34wflUCsBkzcggd7EcQD6xTpXvWRrATdh+MsaHCMAw8x38xEECQHl4z4Hl4CFA91eP+1brzj/LngQ25+AFQBJQ4QhSCRVAEfxvJTv2/r+DUUmdgGYKwOF86lillCPAzjXM0HhyEMA826M33PcfwPrUsUrp+QbAPSe9b3wNBcA7p1mg3ekmQPw2xHjNiyFA+bziqUd6B0Bz9zk+WkQvQNLijGFOIBHAmnecoiM5BsB8fa1LjQglQETdByC1yfQ/nl2+9WEtJ0CARunSvyQQwO19qgoNVBtAxeV4BaI/I8Bpqifzj54iwHXpX5LKtCJAUUzeADPfw7/CEg8omyIawMFyhAzk0SRAjgJEwYwZEUDiIYyfxh0gQLyS5Lm+TyDAmxw+6USyI0BuaMpOP4gDQNXnaiv2py5Ac/G3PUFi878On3QiwZT8PwxAo3TpfyVA6pEGt7UdIUAq5iDoaJ0hQPhvXpz4AiZA1a4JaY3hDMDaOGItPvUjwBAlWvJ42gtA7l7uk6MA5z8+kpIehiYbwMu/lleuxyDA/P1itmQlEUDKiuHqAFggwGSyuP/I9P2/UzwuqkUkAED4HFiOkAECQNxHbk26zQDAlkBK7NpuGsBtOCwN/IghQNun4zEDVQLAnBTmPc4UGMAaTS7GwFoTQCB7vfvjpSFA+wJ64c6F679xAz4/jNAuwMct5ueG1hzAo1nZPuTt/z/NA1jk19ciQMZSJF8JpMa/RYE+kSf5G0CUSnhCr9cmQAgB+RIqOB9AnKIjufxPJMDCaFa2D/kCwJZcxeI3ZSjAR+aRPxjQJ0C9qUiFsUX1P4HQevgyoRjAem8MAcBBJMBo6J/gYuUQwEzEW+fffiBAbApkdha9sz+bWrbWF8EhQAh2/BcIaitAWfj6Wpca3z+GdePdkVEvQNzxJr9F5xtAUcB2MGJfIUD0FaQZi84mQHAi+rX1swFAPPpfrkX7E0AhdqbQeZ0pQMk9Xd2xSB9AceMW83OLJkAVUn5S7RsgQHicoiO5HCbAQ48YPbeQEcCdaFch5XcjQBd+cD51XCfAjZqvko/FLsCz696KxAS5v2TNyCB36SfAhNbDl4lSIUCKWMSww8ApwJvLDYY6DATAnYL8bOQ67r8r3sg88kcDwD7t8NdkTQzAkzgroia6BMCrs1pgj4mwP5QvaCEBYxXAhGOWPQls1L9SnKOOjusfwJs7+l+uxf2/3xtDAHD8F0AgXtcv2P0rwC0ly0ko1S1A4q5eRUaXGsAzwtuDENAaQEerWtJRnhTAk+S5vg/nBsBgIt46/3btv4i9UMB2oB/ASpf+JanM+r9WRiOfVxwbwHEbDeAtEP+/0m2JXHAGEMCIZMix9Qyhv91gqMMKN/4/KNGSx9PyAUCEK6BQT2cgQBcNGY9SeRvAVU/mH31zBED9wcBz74EBwBR15h4SbhHAsyeBzTk4G0DEr1jDRSYywHP1Y5P8KCFAmpguxOqvDsCpM/eQ8C0qwMZsyaoIZxTAibSNP1FJG0ANNJ9zt+vav+7QsBh1rf2/pz/7kSKy/b9LcsCuJs/xP19dFajFCCdAhh3GpL+fKUAi/8wgPpANwGyYofFEQC1AJ/im6bPzGkBYrOEi9wwtwK3D0VW6GxxAcasgBrp2LsCuf9dnzuoZwAqDMo0mNwDAIT1FDhE31D+gpSvYRug0wMzTuaKUQBZAeLmI78Qs4D8ZVBuciD4EwM/b2OxIFQJA3pGx2vy/77/QRUPGo0gywCLeOv92+RbAlUc3wqJi8b9CIQIOoUrDv4S3ByEgrxLAxeV4BaInCMDpnnWNlkP3v+i9MQQA9xFA1qcck8VdA8DEYP4KmaMhQFb18jtNdhLADOVEuwopv7+OkewRaobGP4Y5QZscHgLAOgSOBBps9z+itaLNca4HQNDWwcHeDCZAE2VvKeerIsDNPLmmQI4mQB7EzhQ6jwbAmDPbFfogCsCyZ89lagIvwPiqlQm/RCLAboYb8Plh9j85Qgby7FIDQJmAXyNJELo/QZ5dvvWhBED5D+m3r5MpwCLCvwgaEwHA6svSTs1lIUBT6/1GO74TwAYq499ndCLAFASPb+8aBcBu3c1THVIcQKDdIcUAHTfa*gY18XvEUAkC6EKs/wrAmQGMl5llJ+xTAUWuad5wiI8BgIAiQoaMowLGlR1M92RlAu7a3W5KTEsACRSxi2KH2v0hvuI/cGiBAMV7zqs4aGsC5F5gVilQAwPn2rkFfMjBAzGCMSBSaGEBMqUvGMZK1v1mK5CuBnCJAjgJEwYzpH8D4wmSqYDQAwIvAWN/ApAPAlnmrrkPVBcBOYaWCijoVwIxqEVFMXh3ASnoYWp3c+T9eaRmp99T0v6a6gJcZFhLABFWjVwNkMEA9LNSa5g0WwGTpQxfUpyJAqvHSTWIwGkB8LH3oghobwFUzaykgrfW/MXpuoSuRCEAJpwUv+mIlwOepDrkZnjfa*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*g5AvfxOkxlPFUB4fHvXoG/5v6JD4Eiggf+/SriQR3CDEUBcWDfeHdkVQAMkmkARSwRABygNNQpJD0CkN9xHbiUxQEm+EkiJ3QlAdhvUfmufIMBPIVfqWZDsPzpa1ZKOSijAsqGb/YFy+D8JM23/yuoQQPskd9hEBg1AHTwTmiSGEkCakxeZgL8OQA4tsp3vVxFAbHh6pSzDC0AteNFXkMYRQAK37uaprhTAnYAmwoaHDEAgX0IFhzcEQObLC7CPTu2/NA9gkV9/GsAROugSDm0QQNqoTgeybhfa*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*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*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*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*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*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*gCE82jiiAsAotoKmJVbMP5QXmYBfmyhAby9pjNaZL0B0RpT2Bh/5v0ZB8Pj2bv6/V19dFajF978PXyaKkDoeQJgvL8A++vY/vOtsyD+LL0AfaAWGrOIxQCWvzjEg2x5AJ58e2zLg+L/2Rq0wfScjwHzVyoRfa*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*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","dtype":"float64","shape":[10000]},"y":{"__ndarray__":"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*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*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*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*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*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*zjuejP+DW3TzVkRpA097gC5Mp+D/OT3EcePXzP2stzEI7pw7AXhPSGoMSM8CLbr2mB80owHeC/de52SjALquwGeDiKMAIlE25wrv2PwdEiCtnDwVAOV/svfii9b+k/+VatJgxwJrudVJfVhNAZhNgWP68+T/752nAIAE6QA69xcN7Dh7A/reSHRuB+b8K8x5nmhgywBoziXrBjyBASwLU1LK16z+bVgqBXL4xwEFIFjCB2y7AC0YldQLaAED28GWico*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*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*k/fSO6Z13PM8B95qxPOTYXQGghAaPL0yDAa0QwDi6dHsCHUKVmD0QywGfSpuoeYS/Ah78ma9SrKMB48X7cfkkmwBNgWP58VzpAVdy4xfzcC8AqVaLsLf*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*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*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*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*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*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*ckGqGfwThA0UAsmzncIcA//tKiPnU3QNQpj26EVRDATbuYZro3McCU3je+9rQ5QFFKCFbVkyZAC+9yEd9RJUAsZRniWOcSwDEKgse38zNAyotMwK/1QUDuCKcFL2ocwBrerMH7YiNAHY8ZqIxfDMAtmPijqCsrwK/uWGyTeiVA5q+QuTJwIsBXdsHgmksQQCWzeofbQS7Ad4L917lxIkDUtfY+Vf*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*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*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*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*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*ga4OgLjPQECM8zehEMFAQPZ7Yp0ql0BAr1sExvq6McC0c5oF2v0jQO7qVWR0mDpAfHvXoC+xQEDhJM0f0wIjwA0YJH1azThAWG/UCtP32L9RFr6+1qFAQK01lNqLFDtAHv8FggCZDUDdYKjDCrdAQDHsMCb9fRfA6xuY3CgmNsAGZoUi3d1AQFbvcDs0mDDAAU2EDU8PBUBCsoAJ3LriP6pm1lJAehNAd7rzxHOWOUAr+64I/v8qwPceLjnutAXAgGYQH9gxCsD0bFZ9rtozwKYpApzeu0BA9n6jHTeOQECKraBpiVX6P5c8npYf2CfAURa+vtabQEAoLPGAsmn+v3I2HQHcbPg/hllo5zQfPEDusfShCxotwNTuVwG+cyzAryKjA5KmQECKAKd38dY6QDQO9buwXTpASih9IeR0OkBG71TAPd9AQJV9VwT/UzpADhMNUvAUEUCA8+LEV385QMnk1M4wNSZApddmYyWKNcD+fcaFA8EXwKiMf59xo0BAEce6uI3WF0A3b5wU5r0SQOkOYmcKPTpAQxuADYjgI0BS7j7HR3s6QK+T+rK0AyzANIP4wI7JQEC+9WG9UUshwMLCSZo/IjpAeoocIm6uCcCA0lCjkOwywO23dqIk1BDA/z7jwoGOQECz6nO1FRsbQFU01v7OzkBAC89LxcYEO0Axs89jlKNAQFFqL6LtYCBAAqCKG7cgOECsrdhfdrFAQCGVYkfjnDDAM93rpL4cGECutmJ/2cNAQJ8dcF0xrzpAZM4z9iVLLcDyCdl5G486QBppqbwd4dY/7BNAMbIkDsCLa3wm+w85QDm536EoykBAbsST3czIQEBIwr6dRFQdwHNnJhjOVQZAxr/PuHBwE0DjioujcuMVQEsfuqC+uUBAgm+aPjucQEBYycfuAnUewGnHDb+b9iBABtZx/FC7QEBwtOOG35kzwIP8bOS68SLAhEvHnGemQEA34V6ZtyoPwHfc8LvpkjpAsfojDAN2FUD1RxgGLH06QBH8byU79hHA4nK8AtGzKcAQIa6cvblAQOV620yFYCZAqOMxA5WZKsBolgSoqfk6QJOOcjCbIC7A4q5eRUYH2b/RlnMprgoKwL5O6svSfiDAeV2/YDfOQEAdHVcju7I6QGw9QzhmFTtA4pNOJJiKO0BS81XysSstwMtneR7cTRpA542Twry5QEBa9bnaijU6QJ5i1SDMpUBAKzV7oBVYOECA2NKjqbJAQAnCFVConyRAMsnIWdhfOUBanZyhuJshwLYr9MEyvkBAY5rpXiepQEASonxBC6FAQDduMT83qkBA7WMFvw3DQED8pUV9ks1AQJNWfEPhx0BAcAnAP6XAQEB9WkV/aM5AQPiov15hy0BAw4L7AQ+oQEDh0Fs8vNdAQNY2xeOixkBAvHZpw2GtQEBpNo/DYMBAQBA+lGjJgw1AXVK13QS/QEDvqDEh5rhAQHRgOUIGvkBAhLpIoSy0QEBB176AXtRAQMuFyr+Wu0BA8PeL2ZLBOEDjM9k/T81AQKYO8nowKTlARiI0go3LQEAK2A5G7Bc1wDlE3JxK3EBA31FjQsy9QEAo84++SblAQHWTGARWrEBAaLJ/ngbKQEB6VtKKbwAuwOI5W0Bo2UBATx+BP/ywQEDRlJ1+UOc6QOYg6GhVmyjAXVK13QSfKMCeI/JdSoE6QPw1WaMeFjtAQdR9AFLDLMANxohEoUUtwLjIPV3dVTPAspsZ/WhQKECasz7lmJQ5QBsS91j6WCVAvHfUmBCPOUDKUuv9Rhc4QN+I7lnXlDpAkMAffv4nOUCH3XcMjz0LQEBrfvylRRtAv9cQHJc1PEBzafzCK+kywHmQniKHyPw/xhUXR+USOUBqGD4ipgwywNPZyeAoecE/SrIOR1cp9z/iHksfuvAiwNiACHHl7NC/RgvQtppFF8BVwaikTnAswEeRtYZSOwhAdcjNcAP+K8AShCugUHc6QDNrKSDtv/k/Z5jaUgdBJEBiLT4FwFgYQHHHm/wWzRxA6fAQxk//McAKStHKvYD7v58ENufg9TPAOKRRgZNxOkB2btqM08AWQJaS5SSUXiJAGAYsuYolAkCFQgQcQkUqwLckB+xq4hBAuoJtxJNBOECMEB5tHNkmQD9YxoZuejlA2EenrnyGEsDXMhmO5+MtwGjMJOoF/xVAXk2espru+z+2EU92M1MTwB5QNuUKLwVAJ/im6bPDDEB/bJIf8WsGwI6tZwjHLA1A3dCUnX5Q/r+HbYsyG0wqwOo9ldOeYiPAXkvIBz27AECOHr+36WM6QKIKf4Y3fztALA5nfjVHIcD1aRX9obU6QACOPXsurzhAXyaKkLptK8DFPZY+dEk6QPse9dcrXDhA5q4l5INe+z+yR6gZUmE8QJGA0eXNARtAVkW4yajSEkBX0LTEyqgQwNdMvtnmxv6/z4b8M4PIEkBflQuVf60kwKClK9hGqDhASIszhjmhEsCa6sn8o386QLmnqzsWyyXAR6zFpwCYO0B0J9h/nRsuwCjxuRPsv9S/E9VbA1tdJMDJ6IAk7Ns0wFH6Qsh5uzhA5EwTtp+EJsDvG197Zsn0P4o+H2XERfi/r0D0pEyGOkDDu1zEdyIewBL5LqUuzTlAH/ZCAdtpOUDpD808uZ46QHk+A+rNeCDAVMTpJFsd+D9znxwFiPIXwACpTZzcnzpAQ1a3ek6aOkAfEVMiiSYkwKvpeqLroiFAC5xsA3eQOkAmqOFbWNM6QEjCvp1EMDhAibSNP1EtOkD4F0FjJikkwBLb3QN0tzhAoWez6nOFF8BznNuEe2k6QJ8dcF0xIwVAuFZ72AthOUA/48KBkNQ4QGHgufdwiRdA0CUceovHKsANbmsLz2seQPuxSX7EVzhAq1/pfHjGOkC8zob8M7spwAn9TL1uoTpA647FNqlo5j8T8GskCZIawBkdkIR9Sy3AGELO+/+YIUCSO2wiM98gwNJwytx8ky3Aoib6fJQhOkDNPo9RntkEQB5QNuUKFzpAPN7kt+j0NcAdyeU/pB/6v5ojK78MriDAwwyNJ4KMNkDFkQciixg2wMr7OJojiwxA0xIro5EPJcCRQ8TNqfQTQPuuCP63UjpAU5PgDWnU87+fHXBdMY86QHe9NEWADzpAifAvgsYsIcB1AS8zbDQPQI6QgTy7rBfAxyqlZ3qxKsCBd/LpsS3fvzdvnBTm3SzAfLjkuFOaF0BuNIC3QILjPzcWFAZlWjhAIR0ewvip979cyCO4kVIQQOPjE7LzTi3As2Dij6JO/T+CxkyiXiw4QEph3uNMWzpACwkYXd78GcA97lutExcLQDf6mA8IbCNARBfUt8w1McDbM0sC1JA6QE8EcR5OfDpAaF2j5UBHNcB5BaInZZIEQAU25+CZYB1AHy3OGOZcOUA25nXEIUspwDiCVIodjdE/EodsIF28HUBdpFAWvkYnQHejj/mAPDlA8ghupGzhKsB81cqEXyoWwBXl0viFrzhA3o5wWvDWOkAB+n3/5uE5QIZ1492R1THAxt/2BImVMsA+6Nms+lzVv/iJA+j3nR1AOpLLf0hbOkCUTbnCuwwywJd0lIPZ9BpAQE8DBkk/OkCB6EmZ1Ow5QFfog2VsHDbAPZ0rSgkxHEAcJET5gqo4QJd1/1iIPhlAGqiMf58JK8AShCugUO8LQIC77NedNjlAZARUOIKsOEDvN9pxw68aQP0ubM1WjhXAIeS8/49LOUDarPpcbdU5QJVm8zgMNhzAEY3uIHbyOkBZ94+F6IAvwM2spYC0bxXAPKQYINFEE0Ap0CfyJOkTwEymCkYlVQnA2CjrNxPrLMAcYOY7+J06QBcplIWvyzLA19r7VBUa7r+bdFsiF/wVQBNDcjJxEylATMPwETGl+z8ZyLPLt/4PwOOmBprPNTLABYcXRKQuOkDt8xjlmZfVP16CUx9IkjXArb8lAP+EIMC+S6lLxjHsPzXs98Q6iTHAvwrw3eatAMC2oPfGEGQ5QE+UhETaph3APj22ZcCNOEDudygK9InhP/J7m/7s9zhAZRwj2SOUGkDoS29/LgokQLq/ety3ajlAQBTMmIJ9OkD1nPS+8VE5QMk4RrJHYCNACr/Uz5vSIcAS2QdZFqwtwL4tWKoLuPa/r0Ffevuz/b+9UpYhjjE7QAGjy5vDuTpAisdFtYgYFUA1RBX+DD84QFvri4S2eDpAAoI5evxOOUAwSPq0ir4JQJvniHyXWjpAltBdEmf9IsAK9l/nprk6QGFsIchBLTtAR60wfa9hAUDm5hvRPbsUwMXHJ2TnXSvAMewwJv3JOkATKc3mcRQzwDzaOGItqjpAt0Htt3ZyEcAKoBhZMrcgQED5u3fUaDLABabTug3KAUDdYKjDCrs6QPq5oSk7FSHAZaa0/pbQNMAjwOldvGc6QK+w4H7AkzpA/l915EgHLMDAywwbZW0RwPHxCdl51zDA++sVFtz/I0ArMGR1q1cjQBqiCn+GzzpAYqOs30x8FMAdBYiCGXshwByxFp8ClDhAlugsswhFDkAV/aGZJ0s5QHtKzok9NB7AHXQJh97iOkB2M6MfDecWQHlA2ZQrPOS/3uhjPiBsOkCKBil4CkkWQMxAZfz7rC/AnL8JhQj8OUDZmULnNZY4QILhXMMM4TpA7PgvEASYIMDcZb/udGcaQFlQGJRpNAdAv7oqUIthLcCXjc75KU4qwOjAcoQMEDPAMh06Pe/KMMAapyGq8AcMQAG9cOfCMCrA6L6c2a6YOkBdFajF4Bk7QAb0wp0LWzpAiPccWI58OkAiiV5GsXw6QBUBTu/iXRxAkIe+u5UNOUCJC0CjdHE5QKq4cYv50SNA7IfYYOFcMcDqBgq8k6cwwH9pUZ/kXi3ARKhSswfaCUB55XrbTJU6QLjn+dNGvSrAlIYahSQTBcDECrd8JCXav60XQznRljpABJFFmnjzMcCV1AloImzwP3Np/MIrhTlAdArys5Fr7L8Rct7/x0ktwLn8h/TbTyTAexLYnINzNcADXfsCegU1wLUy4Zf6mSHAG4S53csBO0C1N/jCZNIswICBIECGIjtA4QfnU8e6FEDmdi/3ydHoP1oPXyaKlDpAYobGE0G8FMBkBFQ4gsg4QKrzqPi/6zhAzcggdxFmBEDMsieBzWU7QJMa2gBsZDpA+FEN+z3BOkChKxGo/sEzwGsr9pfd0xDAmKdzRSlZOEB+jSRBuN45QOLNGryvJjHAfzFbsirCAkBhMlUwKgkNwOEH51PH2hXAWBr4UQ2bBkB0z7pGy5k6QGMpkq8EmiDAlj50QX1bOkCmY84z9kURQMjrwaT4+Pw/gjtQpzyuO0Bg5dAi20ElQD7PnzaqyyTArHKh8q8FJEBeEfxvJTvgP1xYN94dcTpABKp/EMnAL8BzEHS0qqUTQOWaApmd5TtAob/QI0aTOkBgBmNEolAxwJ4nnrMF1B7A8FF/vcKCKcB324XmOiEzwIczv5oDoDlAFqJD4EiQNcCastMP6mL4P+if4GJFHRpAJsgIqHAgO0DGNqlorH3vP+I8nMB02vK/aeVeYFZQO0CvzcZKzPMJQAHAsWfPzThAZf7RN2lOOkACu5o8ZcU5QBgkfVpFFzbAx4FXy52pJMBwlLw6x0Dzv/Hz34PXXi3AmmA41zBLJUAHliNkII8IQP62J0hsrzpAp804DVGVLcBKehhanaQ5QNQNFHgnEzpAhbGFIAdpOUAro5HPK34qwNRFCmXhwzpAWFaalIJOLcAk1Xd+UYo4QPyPTIdObzpAnYAmwobnIECo5Qeu8gTAPzOoNjgR6TlAMjz2s1h6GUBxIY/gRoo6QIkLQKN0cTpAVkYjn1dsGMBbJO1GH2c4QG6FsBpLqBpApmH4iJhSBcAAA0GADGE5QByWBn5UeztAJVtdTglAKMCYio15HcEdQG3heanYaC3AZ7Yr9MHiHkCQT8jO23gVwBPwayQJ1jpAmL7XEBxvJEAm4UIewV0aQPwZ3qzBkyLAP6iLFMrCKcCGVidnKDY6QOwVFtwPqBNAHhmrzf/LBMDUQzS6gwgfwPiKbr2mRzpAw9fXutToOkC+g584gE4gQJawNsZOqDpAEmkbf6LuOkDxn26gwAs7QBnG3SBarzpAbOhmf6BsOkAhV+pZENoWQNds5SX/mztAWBr4UQ379b/rqdVXVxE6QLly9s5ogy3AzEQRUrejFUABhXr6CKg4QFQ3F3/bay3At32P+uutMsBLd9fZkLs7QEW8df7tljpAjIaMR6m8OkB73LdaJ844QC+lLhnHqAzA6BGj5xa6F0B32ERmLhQ7QFHZsKay8CjAr5gR3h7kCMAOaVTgZP86QOoGCryTpzpAiC8TRUhdIkDh0cYRa3EFwDBinwCKSTtAPZ6WH7huOUBjl6jeGtg4QFn60AX1/ThA1dAGYAOCMcA+7fDXZE35vzCA8KFEmxpALudSXFVeOkCd2EP7WEU6QC1BRkCFdzpArFj8prASHsCt2jUhrWk6QKUTCaaaWTpAec4WEFrnK8Cp2m6Cb7oLwFLvqZz2/CfAescpOpKTOkDluFM6WL/3PzGzz2OUnzpAL2r3qwAnLcAKEtvdA2g6QM9qgT0m2jpAuhCrP8Iw7b91HhX/dwAywKGjVS3pUCVAIxRbQdPmOkB8DFacam07QNdP/1nzVzlAT5FDxM2tOkCXVG03weciQIm1+BQA6yzAUfTAx2ANI0DsvfiiPao6QJxNRwA3AzlAyLJg4o++MMAFpP0PsN4owCeG5GTiqjHAr9FyoIf*ckCO5zOg3nw5QJRnXg673xhApUkp6PYS9b92+kFdpCA6QOgzoN6MbjtA4KKTpdbTOUCg+Zy7XW8YwF/Rrdf0tDpAVHB4QUSaE8Br1a4JaS0OwCTQYFPnwRjANE3YfjLaOkCGrdnKS77yP9hF0QMfMzlA4ZnQJLE0OkDwGB77WWg6QKT7OQX5iTpAKsb5m1A4O0A98gcDzxk6QFXZd0XwVzpA71hsk4qWK8ApPdNLjCUBQEetMH2vSTpAmIqNeR2BOkB3MGKfAHI6QAsJGF3ezDpAj6uRXWn9OUAqG9ZUFk0lQC/dJAaBZTlA96sA323iOkDMJVXbTZw6QFSPNLitITlA71NVaCAGJEB+GCE82vgMQHtmSYCajjtAb6DAO/kco*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*kCxbVFmgxw6QBDPEmQETDpAqyLcZFTlOUBPyqSGNgQ7QM9IhEawYTpAlphnJa18OUDbM0sC1BQ6QAcnol9bszlAyVht/l+1OUDk9PV8zdI5QEUTKGIRnzpAAcEcPX7jOkASFD/G3Kk6QJrpXif1XTpAzuLFwhD1OkCocW9+w9w5QPM8uDtr0zlAQSswZHXjOkAcz2dAvQk7QLxcxHdiljlAymq6nuj6OUBLIvsgyxY6QJWfVPt0EDpA6spneR6co*kDWHCCYo286QLpJDAIrbzpA6l28H7fnOkBZ2qm53OQ5QK96wDxkejpAi8BY38DEOkD8cma7QnM6QHBCIQIOfTlAfa*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And there is our map. It's worth taking some time to hover over points and explore how the different subreddits got placed, or zoom in on clusters and see the internal structure. A note of warning: this is the unfiltered internet and some (many?) subreddits have unpleasant names. The unpleasant areas of reddit do tend to cluster together in the map; in this case much of it at the top of the map.

Exploring the Clusters

After you've spent a while exploring the interactive map, and looking at how the subreddits group up, one starts to want to explore things in a little more detail -- look at individual clusters, and possibly produce static plots with the subreddits labelled so as to tell a story. We can certainly do that, but we will need a little infrastructure first.

Given the name of a subreddit we would like to find the cluster it is in, and then get some bounds so we can just display that cluster (and perhaps some of the nearby points for context). To make this easier we'll create a cluster bounds function. All that we have to do is find the subreddit in our dataframe, extract the cluster it is in, and then find the min and max x and y values of points in that cluster. We'll pad those bounds out a little bit to ensure we give the cluster a little context.

In[17]:
 def cluster_bounds(dataframe, subreddit): # Find the cluster the subreddit belongs to cluster = dataframe.cluster[ dataframe.subreddit == subreddit].values[0] if cluster == -1: warn('This subreddit was lost as noise and not in any cluster') # Extract the dubset of the dataframe that is the cluster sub_dataframe = dataframe[dataframe.cluster == cluster] x_min = sub_dataframe.x.min() x_max = sub_dataframe.x.max() x_padding = (x_max - x_min) * 0.5 x_min -= x_padding x_max += x_padding y_min = sub_dataframe.y.min() y_max = sub_dataframe.y.max() y_padding = (y_max - y_min) * 0.5 y_min -= y_padding y_max += y_padding return x_min, x_max, y_min, y_max

Next, given bounds, we would like to subselect out the data that lies within those bounds. At the very least this contains the cluster containing the subreddit we selected, but (especially since we padded the bounds) it may contain other data points from outside the cluster as well. We can create a simple function to extract all the points in the dataframe that lie within a given set of bounds.

In[18]:
 def data_in_bounds(dataframe, bounds): return dataframe[ (dataframe.x > bounds[0]) & (dataframe.x < bounds[1]) & (dataframe.y > bounds[2]) & (dataframe.y < bounds[3]) ]

Bokeh did an excellent job of the interactive map; for static plots however the venerable Python standard plotting library matplotlib remains hard to beat in terms of power and flexibility. That means loading up and initializing a slightly different set of visualisation tools.

In[19]:
 from matplotlib import pyplot as pltfrom matplotlib.patches import Rectanglefrom matplotlib.lines import Line2Dfrom matplotlib.gridspec import GridSpecimport seaborn as snsimport adjustText%matplotlib inlinesns.set_context('poster')sns.set_style('white')

If you are going to do something more than a few times you should just write a function to do it. We are almost certainly going to want to plot clusters for many different subreddits so it makes sense to create the function to do so. The parameters should simply be the subreddit map dataframe and the name of a subreddit to look for.

This is a big complicated looking function, but that's mostly just a matter of getting all the visual styling right to present the best possible result. I'll break it down into constituent parts (as we did for the Bokeh plot) to explain what is going on at each stage.

As with Bokeh, we build a colormap (using seaborn to get an identical palette). We are going to have two plots; one is the zoomed in area of the cluster, and the other is a smaller plot of the full map with a zoom box identifying where the zoomed in plot fits into the bigger picture. We'll use gridspec to make laying out the plots easier. We then set about constructing the first plot, getting the cluster bounds (with a suitable error in the case of a bad subreddit name), then getting the data subset, and plotting a scatter plot of that data.

Next we add the text labels. To ensure things don't get too messy we will use a sample of subreddit names if we have more than 50 text labels to add. Of course it is quite likely that the text labels will overlap. Moving labels so they don't overlap, and then adding arrows pointing to the data point they refer to is a complicated and tedious thing to get right. Fortunately adjustText makes that trivial.

The second plot is more straightforward: we simply plot all the data, and then add a rectangle showing the region the larger plot encompasses. Finally we need some connecting lines showing the zoom from the region of the full map to the cluster plot. We can make use of matplotlib's transforms to get all the coordinates right (switching between data, axis, and figure coordinates) and draw the relevant lines. That gives us the plot we want.

In[20]:
 def plot_cluster(dataframe, subreddit): # Build a color map to match the Bokeh plot colormap = dict(zip( np.unique(dataframe.cluster), ['#777777'] + sns.color_palette('plasma', dataframe.cluster.max() + 1).as_hex() )) subregion_defined = True # Figure and gridspec to layout axes fig = plt.figure() gs = GridSpec(3, 3) # First axes, spanning most of the figure # Contains just the points in a region  # around the points in the cluster ax1 = plt.subplot(gs[:,:2]) try: bounds = cluster_bounds(dataframe, subreddit) except IndexError: ax1.text(0.5, 0.5, 'Subreddit {} not found!'.format(subreddit), horizontalalignment='center', verticalalignment='center', transform=ax1.transAxes, fontsize=18) subregion_defined = False if subregion_defined: to_plot = data_in_bounds(dataframe, bounds) ax1.scatter(to_plot.x, to_plot.y, c=to_plot.cluster.map(colormap), s=30, alpha=0.5) # We want to add text labels. We subsample up to 50 labels # And then use adjustText to get them non-overlapping text_elements = [] for row in to_plot.sample(n=min(len(to_plot),50), random_state=0).values: if row[2] != subreddit: text_elements.append(ax1.text(row[0], row[1], row[2], alpha=0.5, fontsize=9)) row = to_plot[to_plot.subreddit == subreddit].values[0] text_elements.append(ax1.text(row[0], row[1], row[2], color='g', alpha=0.5, fontsize=11)) adjustText.adjust_text(text_elements, ax=ax1, lim=100, force_text=0.1, force_points=0.1, arrowprops=dict(arrowstyle="-", color='k', lw=0.5)) ax1.xaxis.set_ticklabels([]) ax1.yaxis.set_ticklabels([]) # Second axes, center right of the figure # Plots all the data and a rectangle # Showing the area selected out ax2 = plt.subplot(gs[1,2]) ax2.scatter(dataframe.x, dataframe.y, s=20, c=dataframe.cluster.map(colormap), alpha=0.05) if subregion_defined: ax2.add_patch(Rectangle(xy=(bounds[0], bounds[2]), width=(bounds[1] - bounds[0]), height=(bounds[3] - bounds[2]), edgecolor='k', facecolor='none', lw=1)) ax2.xaxis.set_ticklabels([]) ax2.yaxis.set_ticklabels([]) plt.tight_layout() if subregion_defined: # Now we make use of the power of matplotlib transforms # to draw line from the subselected rectangle in axes2 # all the way to the bounds of axes1 trans_figure = fig.transFigure.inverted() ax1_coord = trans_figure.transform(ax1.transAxes.transform((1,0))) ax2_coord = trans_figure.transform(ax2.transData.transform((bounds[1],bounds[2]))) connector1 = Line2D((ax1_coord[0],ax2_coord[0]),(ax1_coord[1],ax2_coord[1]), transform=fig.transFigure, lw=1, color='k') ax1_coord = trans_figure.transform(ax1.transAxes.transform((1,1))) ax2_coord = trans_figure.transform(ax2.transData.transform((bounds[1],bounds[3]))) connector2 = Line2D((ax1_coord[0],ax2_coord[0]),(ax1_coord[1],ax2_coord[1]), transform=fig.transFigure, lw=1, color='k') fig.lines = [connector1, connector2]

Okay, that was a fair amount of work, but with that taken care of we can now easily explore clusters in our subreddit map. Since I'm from Canada I thought it might be interesting to see where Canadian subreddits fall on the map.

In[21]:
 plot_cluster(subreddit_map_df, 'canada')

That's interesting, but it seems very Toronto-centric (although I'm sure many Torontonians consider Toronto to be the only part of Canada that matters). We do see the core Toronto subreddits clustered more to the bottom right corner, with more general Ontario subreddits (r/Guelph, r/KingstonOntario, r/kitchener and r/waterloo) further up and to the left. Interestingly my Alma Mater, the University of Western Ontario (r/uwo), falls in amongst the Toronto subreddits, and not up in the top left next to r/londonontario (the city in which the university is actually located). Perhaps that says something about the subculture that populates the uwo subreddit, such as the fact that many UWO students are from Toronto. A final interesting point: the r/toronto subreddit itself doesn't feature here. Where did it end up?

In[22]:
See Also
Interactive Map of Reddit and Subreddit Similarity CalculatorMethods for Finding Related Reddit Subreddits with Simple Set TheoryMapping the Underlying Social Structure of Reddit
 plot_cluster(subreddit_map_df, 'toronto')

Ah, we found the rest of Canada! From the overview map (and even from the context in the bottom right corner) we can see that it is right next to the previous canada cluster, just a little separated. We can also note that we get a general westward trend as me move to the left, with BC related subreddits making up the upper left corner. We also have r/canadaguns somewhere between r/Edmonton and r/UCalgary -- one can perhaps speculate about gun enthusiasts and conservative Alberta. The final thing to note here is that the actual r/toronto subreddit is a bit of an outlier even here. Perhaps the subreddit has a slightly different subculture than the rest of the more specific Toronto subreddits? Certainly a question that might be delving into in more depth with a specific analysis of that subreddit.

Let's move on to other things I'm interested in. How about machine learning -- where does that live?

In[23]:
 plot_cluster(subreddit_map_df, 'MachineLearning')

Now we're much more in the middle of the map, and we have a strong math and science bent to things. There's plety of math related subreddits, with a mix of stats, data science and computer science mixed in. Perhaps more interesting are some of the other subreddits that appear here: right in the middle of the clump is the r/chess subreddit. Perhaps not unexpected? How about r/SwingDancing and r/Fencing in the lower portion? There might be some interesting overlap in those communities. My personal anecdotal experience has most of the mathematicians I know also interested in rock climbing -- that doesn't appear here though. So where do we find climbing?

In[24]:
 plot_cluster(subreddit_map_df, 'climbing')

It's in the outdoors cluster -- although we can see the specific hiking/camping cluster in the top right corner is separate and more tightly packed together. Also worth noting is how explicitly North American this all is. Why r/salesforce shows up in this cluster is a mystery to me; perhaps that is another opportunity for drilling down into more specific data as there may well be an interesting explanation. Finally, apparently related to outdoors in the upper left is ... beer?

In[25]:
 plot_cluster(subreddit_map_df, 'beer')

It seems we just caught the corner of the beer cluster last time -- the actual cluster includes not just beer, but general alcoholic drinks with different parts of the cluster devoted to beer and spirits. Oddly enough the upper left part of this cluster seems to be all about smoking food and barbecuing. It would seem that the sort of users who enage in beer and alcohol specific subreddits also enjoy outdoor cooking.

Enough with following that particular line of coincidences; let's move somewhere else. How about programming?

In[26]:
 plot_cluster(subreddit_map_df, 'programming')

Well this looks much like one might reasonably expect -- a great many of the programming and programming related subreddits all fall closely together here, with the popular programming subreddit near the center of it all. In practice the fringes of this cluster provide some of the more interesting information. Things that are nearby but don't quite make the main cluster include r/programmerreactions and r/Database, but also r/swift, r/iOSprogramming and r/androiddev. It seems that developing for mobile devices has a slightly different subcommunity associated to it than the bulk of programming subreddits. It's also worth noting that, as seen in the overview plot to the right, we are looking at a subcluster of a large group that is somewhat disjoint from the main body of subreddits. We might reasonably expect some of the other clusters amongst that group to also be tech oriented. Since mobile device communities seemed to be a little distinct let's search for some of those ...

In[27]:
 plot_cluster(subreddit_map_df, 'Android')

If you check the right hand overview plot you can see we are still in that large separated group, but now down closer to the bottom of it. And indeed we have a cluster focussed around mobile devices -- but broader than that. r/Hometheater, r/fireTV and r/Tivo all appear nearby at the top of the frame. Similarly, part of another nearby cluster to the left, we can see laptops just making the frame. But enough of Android -- one would reasonably expect the iphone community to be fairly disjoint so let's see if that's the case.

In[28]:
 plot_cluster(subreddit_map_df, 'iphone')

From the overview we see that we are in a nearby (but clearly slightly separate) part of the larger separated group -- and it contains not just iphone, but all things apple. Also getnarwhal, whatever that is (perhaps someone more in tune with the appropriate subculture could fill me in on that one).

I think I've demonstrated how well the dimension reduction and clustering have worked, but you shouldn't take my word for it. You can explore further yourself in the interactive plot. I'm sure there are plenty more interesting stories to tell, especially if you're willing to go and dig a little deeper into the source data on BigQuery to follow up on some of the things we've found here. Some suggestions for things to look for: gun enthusiasts form their own cluster, and that may have interesting structure; photography enthusiasts are also a fairly distinct group; looking more mainstream, the structure of clusters associated to, say, film and TV (hint genres provide structure), or music, also might be interesting. If you're following along in an active notebook then we can make use of ipywidgets to make a one-line with text input for you to search out subreddit clusters yourself -- just run the cells below to get it started, and search away. Unfortunately this won't work for those reading on nbviewer, but perhaps that's motivation to get Jupyter notebook running and try it our for yourself!

In[29]:
 from ipywidgets import interact_manual, fixed, Text

In[30]:
 interact_manual(plot_cluster, dataframe=fixed(subreddit_map_df), subreddit=Text());

For those not following along in a live notebook we'll pick out some interesting clusters and display all of them. How do we find interesting clusters? The clustering algorithm HDBSCAN* supports a notion of cluster coherence -- how strongly or tightly a cluster holds together before breaking apart (either into subclusters, or noise). We can sort the cluster coherence scores and look at the top ten most coherent clusters. These should be the clusters that are the most cleanly grouped as distinct from everything else around them. To start we'll look at a bar plot of the cluster coherence scores (in descending order of coherence) for the top 10 most coherent clusters.

In[31]:
 coherent_clusters = np.argsort(clusterer.cluster_persistence_)[-10:][::-1]coherence = np.sort(clusterer.cluster_persistence_)[-10:][::-1]ax = plt.subplot(111)ax.bar(np.arange(10), coherence)ax.set_xticks(np.arange(10))ax.set_xticklabels(coherent_clusters);

So cluster 2 is very coherent, and after that things tend to fall away and level off. Now that we have the list of the ten most coherent clusters we can have a look at them all. A quick function will make the process much easier.

In[32]:
 def plot_cluster_by_id(dataframe, cluster_id): subreddits_in_cluster = np.array(dataframe.subreddit[cluster_ids == cluster_id]) plot_cluster(dataframe, subreddits_in_cluster[0]) plt.gcf().text(0.5, 0.98, 'Cluster {}'.format(cluster_id), ha='center')

In[33]:
 plot_cluster_by_id(subreddit_map_df, 2)

It would appear that the German subreddits, way out on the right hand side of the map, are the subreddits that clump together very tightly and share little in the common with any other subreddits. Perhaps this is to be expected, especially if they are German language subreddits. One presumes that other foreign language subreddits didn't make the top 10,000, or potentially have users that venture more into English language subreddits as well.

In[34]:
 plot_cluster_by_id(subreddit_map_df, 11)

It is perhaps not surprising that a cult card game like Magic the Gathering has a distinctive and dedicated subculture. There may be some interesting stories to tell about those few subreddits that made the cluster but are floating away from the group: r/EDH, r/mtgcube and r/mtgvorthos.

In[35]:
 plot_cluster_by_id(subreddit_map_df, 8)

Again, we have another dedicated cult subculture making up a tightly knit and distinct cluster of subreddits. This time it is the e-cigarette subculture. Plausibly the subreddit r/Vaping is the more mainstream subreddit shunned by the hardcare devotees?

In[36]:
 plot_cluster_by_id(subreddit_map_df, 0)

We found the photographers! All stretched out in a line rather than clumped together it ranges from general photography (r/itookapicture, 'r/Polaroid, and r/AskPhotography) up to brand specific subreddits like r/Leica, r/fujix and r/Nikon.

In[37]:
 plot_cluster_by_id(subreddit_map_df, 4)

This is clearly the gun subculture subreddits all grouped together. It forms a tightly knit group well separated from the bulk of subreddits and has no particular internal structure (compared to, for example, the photography cluster which spread out linearly). It's interesting that r/Hunting and r/bowhunting made it into the cluster, albeit distant from the main mass.

In[38]:
 plot_cluster_by_id(subreddit_map_df, 28)

North American soccer makes up the next cluster. The neighboring cluster just below (as seen the the overview map on the right) is European soccer subreddits -- however they are close to clusters of European subreddits, making the stretched linear clump you see in the map. In contrast the Noth American soccer subreddit it well separated from everything else. It doesn't have much similarity to other US sport subreddits, and yet is quitea distinct subculture fro the general soccer subreddits (European soccer followers apparently have little interest in North American soccer).

In[39]:
 plot_cluster_by_id(subreddit_map_df, 6)

Here is a distinct fitness subreddit. As it happens this is a very male dominated set of subreddits (as can be inferred from r/Testosterone, r/Brogress, and the focus on weightlifting). You can find a different cluster of fitness subreddits that are more focussed on geenral fitness much closer to the general mass in the center.

In[40]:
 plot_cluster_by_id(subreddit_map_df, 18)

Bitcoin and related crypto-currencies are certainly something we would potentially expect to be a very separate subculture, and indeed they are here. It might be interesting to explore what makes r/BitcoinCA and r/peercoin somewhat different from the other cryptocurrency subreddits.

In[41]:
 plot_cluster_by_id(subreddit_map_df, 63)

Parenting, esepcially of newborns (as can be noted by the pregnancy and 'baby bump' related subreddits in the top left corner) is a challeneging task indeed, something for which one can delve into whatever support subcultures one can find. They all cluster together very tightly here with various pregancy support subreddits making up th uppe left, spreading into newborns and general parenting as we move down and to the right, including r/homeschool and r/atheistparents quite close to each other .

In[42]:
 plot_cluster_by_id(subreddit_map_df, 40)

Reddit, at least as far as the top 10,000 subreddits are concerned, is very English language dominated. You can see that in effect here with a cluster that is ostensibly European in the upper right corner, but as we move along the linear cluster down and to the let we move toward the tightly knit heart of the cluster which is almost entirely British subreddits. Interestingly Irish subreddits spearate off to the right somewhat, while Scottish subreddits (such as r/glasgow and r/Edinburgh) are in amongst the other British subreddits despite potential independence votes.

This brings us to a close of the top 10 most coherent clusters, and a close on our analysis for now. I hope this has been a useful demonstration of the power of machine learning in analysing data and finding useful or interesting stories to tell about the data amidst the large mass of information. Remember data science is a team sport, and we can all play!

As a final note, this notebook presents a fairly direct path that quickly gives us the analysis we want. In case you thought it all went just as smoothly as the final presentation here, fear not -- I explored several different approaches before settling on the one presented here. My initial efforts were very similar to what you see here, but used t-SNE not LargeVis; I also explored using positive pointwise mutual information instead of l1 normalized vectors, and simply taking variations of the conditional probability matrix of the overlaps as the starting point for t-SNE (no distance computations required). Each of these options were inferior in some way, but I've preserved the experiments in notebooks on github so you can see what I tried and failed before embarking on your own analysis superior to this one.

In[]: