import math
import os
import numpy
import pandas
from dash import dash, dcc, html, Output, Input
from collections import Counter
from dash_plot_generation.utils import split_companies, extract_unique_companies, convert_owners_to_limits, \
get_owner_means, round_to_three_largest_digits, replace_owner_number_with_symbol_real_numeric
from dash.exceptions import PreventUpdate
import plotly.graph_objects as go
import plotly.express as px
DEV_AVERAGE_RATING_LABEL = "dev_average_rating"
RIGHT_SIDE_TEXT_DICT = {'display': 'inline-block',
'float': 'right', 'margin-right': '10%'}
DARK_STEAM = "rgb(23,29,37)"
WHITE_STEAM = "rgb(235,235,235)"
TITLE_WHITE_STEAM = "rgb(197,195,192)"
DARK_BLUE_STEAM = "rgb(27,40,56)"
TAB_COLOR = "rgb(31,46,65)"
TAB_EDGE = "rgb(37,55,77)"
DROPDOWN_COLOR = "rgb(50,70,101"
SMALL_PANEL_COLOR = "rgb(22,32,45)"
DEFAULT_TABS_DICT = {'width': 'auto', 'display': 'flex',
'background-color': TAB_COLOR, 'border-color': TAB_EDGE}
TAB_HEADER_COLOR = "rgb(45,96,150)"
DEVELOPER_DROPDOWN = "developer_dropdown"
TAB_NORMAL_DICT = {'background-color': TAB_COLOR, 'color': TITLE_WHITE_STEAM,
'border': '0px solid',
'font-size': '15px',
'border_bottom': '2px solid ' + TAB_EDGE}
TAB_HIGHLIGHT_DICT = {'backgroundColor': TAB_HEADER_COLOR, 'color': 'white', "border-color": "transparent",
'font-size': '15px'}
PANEL_DEFAULT_DICT = {'display': 'inline-block',
'background-color': TAB_COLOR, 'border': '2px solid', 'border-color': TAB_EDGE,
'color': WHITE_STEAM}
SMALL_PANEL_DICT = {'float': 'left', 'background-color': SMALL_PANEL_COLOR, 'box-sizing': 'border-box',
'padding': '10px'}
SMALL_TAB_PANEL_DICT = SMALL_PANEL_DICT | {'width': '48%', 'height': '100%',
'margin-bottom': '50px',
'padding-top': '4%', 'padding-bottom': '5%', 'padding-left': '5%',
'padding-right': '5%',
'margin-top': '20px'
}
SMALL_PANEL_HEADER_DICT = {'text-align': 'center', 'padding-top': '5%', 'padding-bottom': '2%'}
DEV_TOP_GENRES_LABEL = "dev_top_genres"
LIST_DICT = {'display': 'inline-block'}
DEV_CCU_LABEL = "dev_ccu"
DEV_GAME_COUNT_LABEL = "dev_game_count"
DEV_REV_PER_GAME_LABEL = "dev_rev_per_game"
DEV_REVENUE_LABEL = "dev_revenue"
DEV_TOP_GAMES = "pub_top_games"
PUB_TOP_GENRES_LABEL = "pub_top_genres"
PUB_CCU_LABEL = "pub_ccu"
PUB_GAME_COUNT_LABEL = "pub_game_count"
PUB_REV_PER_GAME_LABEL = "pub_rev_per_game"
PUB_REVENUE_LABEL = "pub_revenue"
PUB_TOP_GAMES = "pub_top_games"
DEMO_PLOT_LABELS = ["Action", "Adventure", "RPG", "Puzzle", "Strategy", "Other"]
DEMO_PLOT_COLORS = list(zip(DEMO_PLOT_LABELS, px.colors.qualitative.G10))
csv_path = os.path.normpath(os.getcwd() + os.sep + os.pardir + os.sep + "api_exploration")
split_csv_path = os.path.join(csv_path, "file_segments")
# steam_dark_template = dict(layout=go.Layout(title_font))
df = None
DASH_ASSETS_PATH = "dash_assets"
APP = dash.Dash(
name=__name__,
assets_folder=DASH_ASSETS_PATH,
external_stylesheets=['https://codepen.io/chriddyp/pen/bWLwgP.css'],
)
def initialize_data():
global df
files = os.listdir(split_csv_path)
dataframe = None
for file in os.listdir(split_csv_path):
file_path = os.path.join(split_csv_path, file)
dataframe = pandas.concat([dataframe, pandas.read_csv(file_path)]) if dataframe is not None \
else pandas.read_csv(file_path)
df = dataframe
@APP.callback([Output(DEV_REVENUE_LABEL, "children"),
Output(DEV_TOP_GENRES_LABEL, "children"),
Output(DEV_CCU_LABEL, "children"),
Output(DEV_GAME_COUNT_LABEL, "children"),
Output(DEV_REV_PER_GAME_LABEL, "children"),
Output(DEV_TOP_GAMES, "children"),
Output(DEV_AVERAGE_RATING_LABEL, "children")],
inputs=[Input(DEVELOPER_DROPDOWN, "value")])
def update_dev_info(dev_name):
global df
if not dev_name:
raise PreventUpdate
mask = df.developer.apply(lambda x: dev_name in x if isinstance(x, str) else False)
dev_data = df[mask]
ccu = sum(dev_data["ccu"])
dev_data["owner_means"] = dev_data["owners"].apply(lambda x: get_owner_means(convert_owners_to_limits(x)))
dev_data["game_prices"] = dev_data["price"]
dev_data["game_revenue"] = dev_data.apply(lambda x: x["owner_means"] * x["game_prices"] if
not (pandas.isna(x["owner_means"]) or pandas.isna(x["game_prices"]))
else 0, axis=1)
# dev_data["game_revenue"] = pandas.Series([owner_count * game_price for (owner_count, game_price) in
# zip(dev_data["owner_means"], dev_data["game_prices"]) if
# not (pandas.isna(game_price) or pandas.isna(owner_count))])
genre_totals = [genre for genre_list in dev_data["genres"] if isinstance(genre_list, str)
for genre in genre_list.split(", ")]
genre_counts = Counter(genre_totals).most_common(3)
top_games = dev_data.sort_values(by=["game_revenue"], ascending=False)["name"].head(3)
# top_genres = dict(sorted(genre_totals.items(), key=lambda x: x[1], reverse=True)[:4])
dev_revenue = "$" + replace_owner_number_with_symbol_real_numeric(round_to_three_largest_digits(
int(round(numpy.nansum(dev_data["game_revenue"]), -1))))
dev_top_genre_labels = html.Div("\n".join([genre_c[0] for genre_c in genre_counts]),
style={'white-space': 'pre-line', 'padding-left': '5%'})
dev_ccu = replace_owner_number_with_symbol_real_numeric(round_to_three_largest_digits(ccu))
dev_game_count = str(dev_data.shape[0])
dev_game_revenue_per_game = "$" + replace_owner_number_with_symbol_real_numeric(round_to_three_largest_digits(
int(round(numpy.nansum(dev_data["game_revenue"]) / len(dev_data["game_revenue"]), -1))))
dev_top_games_label = html.Div("\n".join(top_games), style={'white-space': 'pre-line', 'padding-left': '5%'})
user_rating_value = str(round(100*dev_data["Review_rating"].mean())) + "%"
return dev_revenue, dev_top_genre_labels, dev_ccu, dev_game_count, dev_game_revenue_per_game, dev_top_games_label, \
user_rating_value
def initialize_dash(host: str = "0.0.0.0", **kwargs):
"""
Runs the Dash server.
Args:
host: IP address of the server
kwargs: Variables which are passed down to APP.run function as named arguments.
Note:
The server IP is not actually 0.0.0.0; if the dash app is not accessible via this address, use the same port
number but replace the IP address with your local network IP instead.
"""
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"]
APP.css.append_css({
'external_url': 'styles.css'
})
APP.layout = html.Div(
children=[
html.Nav(className="nav nav-pills", children=[
html.H6("SteamSavvy - Steam game data insights",
style={"margin-left": "30px", "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',
style={"margin-left": "150px"})
],
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.Tab(label="Genre performance", value="tab1",
style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
dcc.Tab(label="Game popularity", value="tab2",
style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
dcc.Tab(label="Company revenues", value="tab3",
style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
dcc.Tab(label="Market performance", value="tab4",
style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
],
style=DEFAULT_TABS_DICT),
html.Div(children=[
html.Div(style=SMALL_PANEL_DICT | {'width': '60%', 'height': '100%', 'margin-right': '5%',
'padding-left': '5%',
'background-color': TAB_COLOR},
children=[dcc.Graph(
figure=go.Figure(data=[
{'x': ["Action", "Adventure", "RPG", "Puzzle", "Strategy"],
'y': [0.7, 0.4, 0.8, 1.2, 1.3],
'type': 'bar'},
],
layout=dict(template="plotly_dark",
title="Relative genre perfomance",
plot_bgcolor=TAB_COLOR,
paper_bgcolor=TAB_COLOR)),
),
html.P(f"""Genre performance measures the assessed exploitability of the
specific game genre. The assesment is done by estimating the genre popularity,
and games developed in the next two years and showing the relative differences
between the genres.""")]),
html.Div(style=SMALL_PANEL_DICT | {'width': '35%', 'height': '100%',
'background-color': TAB_COLOR},
children=[
html.Div(style={'width': '100%', 'height': '50%'},
children=[dcc.Graph(
figure=go.Figure(data=[go.Pie(
labels=["Action", "Adventure", "RPG", "Puzzle", "Strategy",
"Other"],
values=[0.8, 0.3, 0.4, 0.4, 0.3, 0.55],
sort=False)],
layout=dict(template="plotly_dark",
title="Genre popularity",
plot_bgcolor=TAB_COLOR,
paper_bgcolor=TAB_COLOR,
margin=dict(l=20, r=20, t=50, b=20))),
style={'width': '100%', 'height': '100%'})]),
html.Div(style={'width': '100%', 'height': '50%'},
children=[dcc.Graph(
figure=go.Figure(data=[go.Pie(
labels=["Action", "Adventure", "RPG", "Puzzle", "Strategy",
"Other"],
values=[0.7, 0.5, 0.1, 0.4, 0.3, 0.7],
sort=False, )],
layout=dict(template="plotly_dark",
title="Genre revenue share",
plot_bgcolor=TAB_COLOR,
paper_bgcolor=TAB_COLOR,
margin=dict(l=20, r=20, t=50, b=20))),
style={'width': '100%', 'height': '100%'})]
)])],
style={'height': '88%', 'width': '100%', 'margin': '0'})
], style=PANEL_DEFAULT_DICT | {'width': 'calc(45% - 10px)', 'height': '600px',
'margin-right': '100px', 'padding-left': '4%',
'padding-right': '4%', 'padding-bottom': '4%',
'padding-top': '3%', 'margin-bottom': '20px'
}),
html.Div(children=[
dcc.Tabs(id="tabs_main_plots2", 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
),
html.Div(children=[
html.Div( # Revenue
children=[
html.Div(
children=[html.P("Revenue", style=SMALL_PANEL_HEADER_DICT)],
style={'margin-bottom': '10%',
'border-bottom': '2px solid ' + TAB_EDGE}),
html.Div(children=[
html.Div(children=[
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)
]),
html.Div(children=[
html.P("Game average:",
style=LIST_DICT | {'padding-left': '5%'}),
html.P(id=DEV_REV_PER_GAME_LABEL, children="$925 M",
style=RIGHT_SIDE_TEXT_DICT)
])
],
style={'margin-bottom': '10px'}),
html.Div(children=[
html.P("Top games by revenue:"),
html.Small(id=DEV_TOP_GAMES, children="Half life 2"),
])
]),
], style={'padding-left': '5%', 'padding-right': '5%',
'padding-bottom': '5%'})
],
style=SMALL_TAB_PANEL_DICT | {'margin-right': '20px'}
),
html.Div(children=[
html.Div(
children=[
html.Div(
children=[html.P("General information",
style=SMALL_PANEL_HEADER_DICT)],
style={'margin-bottom': '30px',
'border-bottom': '2px solid ' + TAB_EDGE}),
html.Div(children=[
html.Div(children=[
html.P("Number of games:", style=LIST_DICT),
html.P(id=DEV_GAME_COUNT_LABEL, children="5",
style=RIGHT_SIDE_TEXT_DICT),
],
style={'margin-bottom': '10px'}
),
html.Div(children=[
html.P("Concurrent users:", style=LIST_DICT),
html.P(id=DEV_CCU_LABEL, children="92.625.000€",
style=RIGHT_SIDE_TEXT_DICT),
],
style={'margin-bottom': '10px'}
),
html.Div(children=[
html.P("Most common game genres:"),
html.Small(id=DEV_TOP_GENRES_LABEL,
children="FPS, Action, Puzzle"),
],
style={'margin-bottom': '10px'}
),
html.Div(children=[
html.P("Average game rating", style=LIST_DICT),
html.P(id=DEV_AVERAGE_RATING_LABEL,
children="0%",
style=RIGHT_SIDE_TEXT_DICT)
])
])
])
], style=SMALL_TAB_PANEL_DICT | {'width': '45%', 'height': '100%'}
)
])
], style={'margin-left': '20px', 'margin-right': '20px'}
)
], style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT),
dcc.Tab(label="Publisher information", value="tab4", children=[
dcc.Dropdown(id="publisher_dropdown", value="Valve",
options=[{"label": publisher, "value": publisher} for publisher in
unique_publishers],
),
], style=TAB_NORMAL_DICT, selected_style=TAB_HIGHLIGHT_DICT)
],
style=DEFAULT_TABS_DICT),
],
style=PANEL_DEFAULT_DICT | {'width': 'calc(30% - 10px)', 'height': '600px', 'margin-right': '4%',
'padding-left': '3%',
'padding-right': '3%', 'padding-bottom': '4%',
'padding-top': '3%', 'margin-bottom': '20px'
})
],
style={'width': '100%', "padding-top": "15px", 'padding-left': "50px"}),
],
style={"font-family": "Tahoma"}
)
APP.run(host=host, **kwargs)
print("The server has closed!")
if __name__ == "__main__":
initialize_data()
initialize_dash(debug=True)
print(csv_path)