diff --git a/dash_plot_generation/dash_plot_generator.py b/dash_plot_generation/dash_plot_generator.py
index e88bddb9bec75c6688c0df97c755bd4e292895a6..3a05b81728e95e650a41b6a6dfdad02cbe14c0be 100644
--- a/dash_plot_generation/dash_plot_generator.py
+++ b/dash_plot_generation/dash_plot_generator.py
@@ -12,6 +12,8 @@ from dash.exceptions import PreventUpdate
import plotly.graph_objects as go
import plotly.express as px
+SPACE_NORMAL_ENTRY = 35
+
DEV_AVERAGE_RATING_LABEL = "dev_average_rating"
RIGHT_SIDE_TEXT_DICT = {'display': 'inline-block',
@@ -124,7 +126,7 @@ def update_dev_info(dev_name):
dev_top_games_label = get_top_revenue_game_labels(dev_data)
# Dev total revenue
- dev_revenue = "$" + get_total_revenue(dev_data)
+ dev_revenue = get_total_revenue_label(dev_data)
# Dev revenue per game
dev_game_revenue_per_game = get_average_game_rev_label(dev_data)
@@ -145,12 +147,12 @@ def update_dev_info(dev_name):
def get_average_user_rating_label(dev_data):
value_str = str(round(100 * dev_data["Review_rating"].mean())) + "%"
- label = label_with_text("Average game rating", value_str, 40, ".")
+ label = label_with_text("Average game rating", value_str, SPACE_NORMAL_ENTRY, ".")
return label
def get_game_count_label(dev_data):
- return label_with_text("Number of games", str(dev_data.shape[0]), 40, ".")
+ return label_with_text("Number of games", str(dev_data.shape[0]), SPACE_NORMAL_ENTRY, ".")
def add_game_revenues_and_owner_means(data):
@@ -162,7 +164,7 @@ def add_game_revenues_and_owner_means(data):
def get_top_revenue_game_labels(data):
top_games = data.sort_values(by=["game_revenue"], ascending=False).head(3)
- top_games_processed = top_games.apply(lambda x: label_with_rev(x["name"], x["game_revenue"], 35,
+ top_games_processed = top_games.apply(lambda x: label_with_rev(x["name"], x["game_revenue"], SPACE_NORMAL_ENTRY,
".", "$"), axis=1)
dev_top_games_with_dot = [" ".join(["•", game]) for game in top_games_processed]
dev_top_games_label = html.Div("\n".join(dev_top_games_with_dot),
@@ -170,8 +172,9 @@ def get_top_revenue_game_labels(data):
return dev_top_games_label
-def get_total_revenue(data):
- return convert_to_numeric_str(numpy.nansum(data["game_revenue"]))
+def get_total_revenue_label(data):
+ top_games_processed = label_with_rev("• Total", numpy.nansum(data["game_revenue"]), SPACE_NORMAL_ENTRY, ".", "$")
+ return top_games_processed
def get_top_genre_labels(data):
@@ -189,12 +192,12 @@ def get_ccu_label(data):
ccu = sum(data["ccu"])
dev_ccu = convert_to_numeric_str(ccu)
- return label_with_text("Concurrent users", dev_ccu, 40, ".")
+ return label_with_text("Concurrent users", dev_ccu, SPACE_NORMAL_ENTRY, ".")
def get_average_game_rev_label(data):
game_revenue_per_game_raw = numpy.nansum(data["game_revenue"]) / len(data["game_revenue"])
- dev_game_revenue_per_game_row = label_with_rev("Average", game_revenue_per_game_raw, 35, ".", "$")
+ dev_game_revenue_per_game_row = label_with_rev("Average", game_revenue_per_game_raw, SPACE_NORMAL_ENTRY, ".", "$")
dev_game_revenue_per_game = " ".join(["•", dev_game_revenue_per_game_row])
return dev_game_revenue_per_game
@@ -212,10 +215,10 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
global APP, df, DEMO_PLOT_COLORS, DEMO_PLOT_LABELS
- # unique_publishers = extract_unique_companies(df["publisher"].apply(lambda x: split_companies(x)))
- # unique_developers = extract_unique_companies(df["developer"].iloc[0:10].apply(lambda x: split_companies(x)))
- unique_publishers = ["Valve"]
- unique_developers = ["Valve"]
+ unique_publishers = extract_unique_companies(df["publisher"].apply(lambda x: split_companies(x)))
+ unique_developers = extract_unique_companies(df["developer"].iloc[0:10].apply(lambda x: split_companies(x)))
+ # unique_publishers = ["Valve"]
+ # unique_developers = ["Valve"]
APP.css.append_css({
'external_url': 'styles.css'
@@ -224,7 +227,7 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
children=[
html.Nav(className="nav nav-pills", children=[
html.H6("SteamSavvy - Steam game data insights",
- style={"margin-left": "30px", "width": "20%", "display": "inline-block"}),
+ style={"margin-left": "60px", "width": "20%", "display": "inline-block"}),
html.A('About', className="nav-item nav-link btn", href='/apps/App1',
style={"margin-left": "300px"}),
html.A('Technical report', className="nav-item nav-link active btn", href='/apps/App2',
@@ -233,7 +236,7 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
style={"background-color": "rgb(23,29,37)", "color": "rgb(197,195,192)", 'width': '100%'}),
html.Div(className="row", children=[
html.Div(children=[
- dcc.Tabs(id="tabs_main_plots1", value="tab1", children=[
+ dcc.Tabs(id="main_plots", value="tab1", children=[
dcc.Tab(label="Genre performance", value="tab1",
style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT,
children=[
@@ -355,20 +358,20 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
],
style=DEFAULT_TABS_DICT),
- ], style=PANEL_DEFAULT_DICT | {'width': 'calc(45% - 10px)',
- 'margin-right': '100px', 'padding-left': '4%',
- 'padding-right': '4%', 'padding-bottom': '4%',
- 'padding-top': '3%', 'margin-bottom': '20px'
+ ], style=PANEL_DEFAULT_DICT | {'width': '900px',
+ 'margin-right': '100px', 'padding-left': '50px',
+ 'padding-right': '50px', 'padding-bottom': '50px',
+ 'padding-top': '50px', 'margin-bottom': '50px'
}),
html.Div(children=[
- dcc.Tabs(id="tabs_main_plots2", value="tab3", children=[
+ dcc.Tabs(id="company_information", value="tab3", children=[
dcc.Tab(label="Developer infromation", value="tab3", children=[
html.Div(children=[
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},
- className='dash-dropdown', # Add the CSS class here
+ className='dash-dropdown',
),
html.Div(children=[
html.Div(
@@ -382,14 +385,10 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
html.P("Game sale revenue estimates"),
html.Div(children=[
html.Div(children=[
- html.P("• Total ....................",
- style=LIST_DICT | {'padding-left': '5%'}),
html.P(id=DEV_REVENUE_LABEL, children="$524 M",
- style=RIGHT_SIDE_TEXT_DICT)
+ style=LIST_DICT | {'padding-left': '5%'})
]),
html.Div(children=[
- # html.P("• Average ...............",
- # style=LIST_DICT | {'padding-left': '5%'}),
html.P(id=DEV_REV_PER_GAME_LABEL, children="$925 M",
style=LIST_DICT | {'padding-left': '5%'})
]),
@@ -403,7 +402,7 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
], style={'padding-left': '5%', 'padding-right': '5%',
'padding-bottom': '5%'})
],
- style=SMALL_TAB_PANEL_DICT | {'margin-right': '20px'}
+ style=SMALL_TAB_PANEL_DICT | {'margin-right': '20px', 'margin-left': '0px'}
),
html.Div(children=[
html.Div(
@@ -441,10 +440,11 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
])
])
- ], style=SMALL_TAB_PANEL_DICT | {'width': '45%', 'height': '100%'}
+ ], style=SMALL_TAB_PANEL_DICT | {'width': '45%', 'height': '100%',
+ 'margin-right': '0px', 'margin-left': '20px'}
)
], style={'height': '100%'})
- ], style={'margin-left': '20px', 'margin-right': '20px'}
+ ], style={'margin-left': '20px', 'margin-right': '0px'}
)
], style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
dcc.Tab(label="Publisher information", value="tab4", children=[
@@ -458,13 +458,13 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
],
style=DEFAULT_TABS_DICT),
],
- style=PANEL_DEFAULT_DICT | {'width': 'calc(30% - 10px)', 'margin-right': '4%',
- 'padding-left': '3%',
- 'padding-right': '3%', 'padding-bottom': '4%',
- 'padding-top': '3%', 'margin-bottom': '20px'
+ style=PANEL_DEFAULT_DICT | {'width':'700px',
+ 'padding-left': '50px',
+ 'padding-right': '50px', 'padding-bottom': '50px',
+ 'padding-top': '50px', 'margin-bottom': '50px'
})
],
- style={'width': '100%', "padding-top": "15px", 'padding-left': "50px"}),
+ style={'width': '100%', "padding-top": "30px", 'padding-left': "50px"}),
],
style={"font-family": "Tahoma"}
)
@@ -474,6 +474,6 @@ def initialize_dash(host: str = "0.0.0.0", **kwargs):
if __name__ == "__main__":
initialize_data()
- initialize_dash(debug=False)
+ initialize_dash(debug=True)
print(csv_path)