World Cup example patch (#427)

Co-authored-by: maximlt <mliquet@anaconda.com>

world_cup/anaconda-project.yml

@@ -3,12 +3,12 @@ description: Analysis of key events in the 2018 FIFA World Cup
 examples_config:
   created: 2024-06-24
   maintainers:
-  - maximlt
   - azaya89
   categories:
   - Sports
   labels:
   - hvplot
+  - holoviews
   - panel
   title: "FIFA World Cup 2018"
   deployments:

world_cup/world_cup.ipynb

@@ -61,7 +61,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "events_df.head()"
+    "events_df.head(2)"
    ]
   },
   {
@@ -71,7 +71,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "players_df.tail()"
+    "players_df.tail(2)"
    ]
   },
   {
@@ -94,8 +94,10 @@
    "outputs": [],
    "source": [
     "event_type_count = events_df['eventName'].value_counts()\n",
-    "event_type_distribution = event_type_count.hvplot.bar(title='Distribution of Event Types', height=400,\n",
-    "                                                      responsive=True, rot=45)\n",
+    "event_type_distribution = event_type_count.hvplot.bar(\n",
+    "    title='Distribution of Event Types', height=400,\n",
+    "    responsive=True, rot=45,\n",
+    ")\n",
     "event_type_distribution"
    ]
   },
@@ -180,9 +182,11 @@
     "        hv.Text(10, 6, 'Attack', 11) # attack text\n",
     "    ]\n",
     "    \n",
-    "    field = hv.Overlay(pitch_elements).opts(frame_width=pitch_plot_width, frame_height=pitch_plot_height,\n",
-    "                                            xlim=(-5, field_length + 5), ylim=(-5, field_width + 5),\n",
-    "                                            xaxis=None, yaxis=None)\n",
+    "    field = hv.Overlay(pitch_elements).opts(\n",
+    "        frame_width=pitch_plot_width, frame_height=pitch_plot_height,\n",
+    "        xlim=(-5, field_length + 5), ylim=(-5, field_width + 5),\n",
+    "        xaxis=None, yaxis=None\n",
+    "    )\n",
     "    return field"
    ]
   },
@@ -235,7 +239,7 @@
    "outputs": [],
    "source": [
     "events_df = transform_positions(events_df, field_length, field_width)\n",
-    "events_df.head()"
+    "events_df.head(2)"
    ]
   },
   {
@@ -286,9 +290,10 @@
     "    \n",
     "    event_heatmap = event_df.hvplot.hexbin(x='x', y='y', cmap=cmap, min_count=1, title=title)\n",
     "    \n",
-    "    event_heatmap_plot = (event_heatmap * pitch).opts(frame_width=pitch_plot_width, frame_height=pitch_plot_height,\n",
-    "                                                      xlim=(-5, 110), ylim=(-5, 73),\n",
-    "                                                      xaxis=None, yaxis=None)\n",
+    "    event_heatmap_plot = (event_heatmap * pitch).opts(\n",
+    "        frame_width=pitch_plot_width, frame_height=pitch_plot_height,\n",
+    "        xlim=(-5, 110), ylim=(-5, 73), xaxis=None, yaxis=None\n",
+    "    )\n",
     "\n",
     "    return event_heatmap_plot"
    ]
@@ -434,12 +439,14 @@
     "    \"\"\"\n",
     "    top_players = find_top_players(events_df, players_df, event_type, top_n)\n",
     "    event_type = event_type.lower()\n",
-    "    \n",
+    "\n",
     "    title = f'Top {top_n} Players for {event_type.capitalize()}'\n",
-    "    \n",
-    "    bar_plot = top_players.hvplot.bar(title=title, x='shortName', y=f'{event_type} count',\n",
-    "                                      xlabel='', ylabel=f'Number of {event_type}', rot=45)\n",
-    "    \n",
+    "\n",
+    "    bar_plot = top_players.hvplot.bar(\n",
+    "        title=title, x='shortName', y=f'{event_type} count',\n",
+    "        xlabel='', ylabel=f'Number of {event_type}', rot=45\n",
+    "    )\n",
+    "\n",
     "    return bar_plot"
    ]
   },
@@ -473,7 +480,7 @@
     "top_n_selector = pn.widgets.IntSlider(name='Top', start=1, end=20, value=10)\n",
     "\n",
     "bar_chart = pn.bind(plot_top_players, events_df=events_df, players_df=players_df,\n",
-    "                                event_type=event_type_selector, top_n=top_n_selector)\n",
+    "                    event_type=event_type_selector, top_n=top_n_selector)\n",
     "\n",
     "pn.Column(pn.Row(top_n_selector, event_type_selector), bar_chart)"
    ]
@@ -563,12 +570,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "player_name_selector = pn.widgets.AutocompleteInput(name='Player Name', options=list(players_df['shortName']),\n",
-    "                                                    placeholder='Type player name...', case_sensitive=False,\n",
-    "                                                   search_strategy='includes', value='L. Messi')\n",
+    "player_name_selector = pn.widgets.AutocompleteInput(\n",
+    "    name='Player Name', options=list(players_df['shortName']),\n",
+    "    placeholder='Type player name...', case_sensitive=False,\n",
+    "    search_strategy='includes', value='L. Messi'\n",
+    ")\n",
     "\n",
     "player_events = pn.bind(plot_player_events, events_df=events_df,\n",
-    "                         players_df=players_df, player_name=player_name_selector)\n",
+    "                        players_df=players_df, player_name=player_name_selector)\n",
     "\n",
     "pn.Column(player_name_selector, player_events, sizing_mode='stretch_width')"
    ]
@@ -608,7 +617,10 @@
     "    pass_positions = [(pos[0]['x'], pos[0]['y']) for pos in passes['positions'] if len(pos) > 1]\n",
     "    pass_df = pd.DataFrame(pass_positions, columns=['x', 'y'])\n",
     "    \n",
-    "    pass_scatter = pass_df.hvplot.points(x='x', y='y', color='#1D78B4', title=f\"Click for Pass Trajectories of {player_name}\")\n",
+    "    pass_scatter = pass_df.hvplot.points(\n",
+    "        x='x', y='y', color='#1D78B4',\n",
+    "        title=f\"Click for Pass Trajectories of {player_name}\"\n",
+    "    )\n",
     "    total_passes = hv.Text(75, 70, f'Total number of passes: {len(pass_df)}', halign='center', fontsize=12)\n",
     "    \n",
     "    # Callback to filter passes based on click location\n",