Added initial plot for Market Performance

dash_plot_generation/app.py

@@ -9,11 +9,13 @@ from dash_plot_generation.styles_and_handles import RATING_MIN_REVIEWS, RATING_S
     DEV_AVERAGE_RATING_LABEL, DENSITY_LAYOUT_STYLE, WHITE_STEAM, TAB_COLOR, TAB_EDGE, \
     TAB_HEADER_COLOR, DEVELOPER_DROPDOWN, DEV_TOP_GENRES_LABEL, DEV_CCU_LABEL, DEV_GAME_COUNT_LABEL, \
     DEV_REV_PER_GAME_LABEL, DEV_REVENUE_LABEL, DEV_TOP_GAMES, RATING_TABS, RATING_TABS_OUTPUT_AREA, \
-    GENRE_PREDICTION_GRAPH, GENRE_DROPDOWN, DEFAULT_PLOT_STYLE_DICT, GAMES_BY_DEV_GRAPH
+    GENRE_PREDICTION_GRAPH, GENRE_DROPDOWN, DEFAULT_PLOT_STYLE_DICT, GAMES_BY_DEV_GRAPH, MARKET_PERFORMANCE_SCATTER, \
+    MP_COMPANY_TYPE_DROPDOWN, create_market_scatter_plot_style
 from dash_plot_generation.utils import get_average_user_rating_label, get_game_count_label, get_top_revenue_game_labels, \
     get_total_revenue_label, get_top_genre_labels, get_ccu_label, get_average_game_rev_label
 from visual_presentation.Annual_release_games import get_game_release_figure
 from visual_presentation.Distribution_of_review_rating import get_rating_density_plot
+from visual_presentation.Market_performance_function import plot_market_performance
 
 APP = dash.Dash(
     name=__name__,
@@ -140,6 +142,13 @@ def get_genre_prediction_table(genre, **kwargs):
     return fig
 
 
+@APP.callback(Output(MARKET_PERFORMANCE_SCATTER, "figure"),
+             Input(MP_COMPANY_TYPE_DROPDOWN, "value"))
+def get_market_performance_scatter(company_type):
+    style = create_market_scatter_plot_style(company_type)
+    return plot_market_performance(FULL_DATA, company_type, 100, 0, **style)
+
+
 if __name__ == "__main__":
     initialize_data()
     APP.run_server(debug=True, host="0.0.0.0")

dash_plot_generation/assets/styles.css

@@ -137,6 +137,9 @@ body {
 .dash-dropdown .Select-menu-outer {
     background-color: var(--TAB_COLOR);
 }
+.dash-dropdown {
+    color: var(--WHITE_STEAM);
+}
 
 .jsx-4017309047.tab-container{
     border-bottom: 2px solid var(--TAB_EDGE);

dash_plot_generation/pages/dash_plot_generator.py

@@ -7,11 +7,9 @@ from dash_plot_generation.styles_and_handles import RATING_MIN_REVIEWS, RATING_S
     DEFAULT_PLOT_STYLE_DICT, WHITE_STEAM, TAB_COLOR, TAB_EDGE, DEVELOPER_DROPDOWN, \
     DEV_TOP_GENRES_LABEL, DEV_CCU_LABEL, DEV_GAME_COUNT_LABEL, DEV_REV_PER_GAME_LABEL, \
     DEV_REVENUE_LABEL, DEV_TOP_GAMES, RATING_TABS, RATING_TABS_OUTPUT_AREA, GENRE_DROPDOWN, GENRE_PREDICTION_GRAPH, \
-    GAMES_BY_DEV_GRAPH
+    GAMES_BY_DEV_GRAPH, MARKET_PERFORMANCE_SCATTER, MP_COMPANY_TYPE_DROPDOWN
 
 from dash_plot_generation.data_store import FULL_DATA, OWNER_RANGE_PARTS_SORTED
-from dash_plot_generation.utils import get_all_genres, extract_unique_companies, split_companies, \
-    get_genre_popularity_counts
 
 global APP, FULL_DATA
 
@@ -229,14 +227,27 @@ layout = html.Div(
                             children=[
                                 html.Div(
                                     children=[
-                                        html.Div(id="Market performance_top",
-                                                 children=[
-                                                     html.Div(children=[dcc.Graph()],
-                                                              style={"width": "60%", "display": "inline-block"}),
-                                                     html.Div(children=[html.H5("First plot text")],
-                                                              style={"width": "30%", "display": "inline-block"})
-                                                 ]
-                                                 ),
+                                        html.Div(children=[
+                                            html.Div(children=[dcc.Graph(id=MARKET_PERFORMANCE_SCATTER,
+                                                                         figure=go.Figure(
+                                                                             layout=DEFAULT_PLOT_STYLE_DICT |
+                                                                                    dict(
+                                                                                        title="Market performance",
+                                                                                        margin=dict(l=20, r=20,
+                                                                                                    t=50,
+                                                                                                    b=20)))
+                                                                         )],
+                                                     style={"width": "60%", "vertical-align": "top",
+                                                            "display": "inline-block", "margin-right":"5%"}),
+                                            html.Div(children=[html.H5("First plot text"),
+                                                               dcc.Dropdown(id=MP_COMPANY_TYPE_DROPDOWN,
+                                                                            className='dash-dropdown',
+                                                                            value="developer",
+                                                                            options=["developer", "publisher"])],
+                                                     style={"width": "30%", "vertical-align": "top",
+                                                            "display": "inline-block"})
+                                        ], style={"display": "flex", "align-items": "flex-start", "margin-bottom":"50px"}
+                                        ),
                                         html.Div(id="Market performance_second",
                                                  children=[
                                                      html.Div(children=[dcc.Graph()],
@@ -265,7 +276,7 @@ layout = html.Div(
                                 dcc.Dropdown(id=DEVELOPER_DROPDOWN, value="Valve",
                                              options=[{"label": html.Span([developer], style={'color': WHITE_STEAM}),
                                                        "value": developer} for developer in unique_developers],
-                                             style={'margin-top': '20px', 'color': WHITE_STEAM},
+                                             style={'margin-top': '20px'},
                                              className='dash-dropdown',
                                              ),
                                 html.Div(children=[

dash_plot_generation/styles_and_handles.py

-
 # html handles
 RATING_MIN_REVIEWS = "min_reviews_id"
 RATING_SLIDER = "rating_slider"
@@ -24,7 +23,6 @@ GENRE_DROPDOWN = "genre_dropdown"
 GENRE_PREDICTION_GRAPH = "Genre_prediction_graph"
 GAMES_BY_DEV_GRAPH = "game_releases_by_dev_graph"
 
-
 SPACE_NORMAL_ENTRY = 35
 
 # Colors
@@ -48,6 +46,18 @@ DEFAULT_PLOT_STYLE_DICT = dict(
 
 DENSITY_LAYOUT_STYLE = DEFAULT_PLOT_STYLE_DICT | dict(
     title='Distribution of Game Review Rating',
-    xaxis_title="Game user rating",
+    xaxis_title="Game User Rating",
     yaxis_title="Proportion"
-)
+)
\ No newline at end of file
+
+MARKET_PERFORMANCE_SCATTER = "Market_performance_scatter"
+MP_COMPANY_TYPE_DROPDOWN = "market_performance_company_type_dropdown"
+
+
+def create_market_scatter_plot_style(company_type):
+    return {
+        **DEFAULT_PLOT_STYLE_DICT,
+        'title': f'Market Performance for {company_type} companies',
+        "xaxis_title": "Revenue",
+        "yaxis_title": "Number of Game Owners",
+    }

visual_presentation/Market_performance_function.py

@@ -7,7 +7,7 @@ from dash_plot_generation.utils import get_owner_means, convert_owners_to_limits
 
 # The function to plot the bubble chart of market performance
 
-def plot_market_performance(df, company_type: str, game_number_max: int, game_number_min: int):
+def plot_market_performance(df, company_type: str, game_number_max: int, game_number_min: int, **layout_arguments):
     
     """
     This function creates a bubble chart of market performance.
@@ -33,7 +33,7 @@ def plot_market_performance(df, company_type: str, game_number_max: int, game_nu
     # Bubble chart
     fig = px.scatter(filter_company_stats, x='revenue', y='owner_number', size='game_number', log_y=True, log_x=True,size_max = 40,
                  hover_name='company_split', title=f'Market Performance of {company_type}')
-
+    fig.update_layout(**layout_arguments)
     return fig