def update_dropdown_team_options(season, competition):
if season and competition:
df = filter_competition(df_players, competition)
df = filter_season(df, season)
teams = sorted(df["team_url"].unique())
return get_dash_dropdown_options(teams, teams)
else:
return []
def update_datatable_raw(competition, season, team, player_url):
df = df_players
if competition:
df = filter_competition(df, competition)
if season:
df = filter_season(df, season)
if team:
df = filter_team_url(df, team)
if player_url:
df = filter_player_url(df, player_url)
return df[VISIBLE_COLUMNS].to_dict("records")
def update_dropdown_team_options(team, competition, season):
if season and competition and team:
df = filter_competition(df_players, competition)
df = filter_season(df, season)
df = filter_team_url(df, team)
player_urls, player_names = (df[[
"player_url", "player_name"
]].drop_duplicates().sort_values("player_name").values.transpose())
return get_dash_dropdown_options(player_urls, player_names)
else:
return []
def main():
player_url_to_name = helpers.get_map_from_url_to_name(df_players, "player")
team_url_to_name = helpers.get_map_from_url_to_name(df_players, "team")
st.title("Goal Difference Project")
st.write("Explore datasets from big 5 leagues.")
st.header("gd90 calculation")
st.markdown("""
(Sum of the goal differences (GD) during each of the appearances) / (total playing time) x 90
""")
# st.write("As formula:")
# st.latex(
# r"""
# \text{gd90} = \frac{\sum{\text{GD}}}{\sum{\text{min'}} \cdot 90}
# """
# )
# The `gd90` value in plots below is calculated for each player as 90 * SUM(goal difference while player is on field) / SUM(minutes played)
st.header("Analysis for selected season, player and team")
VISIBLE_COLUMNS = [
"competition",
"year",
"matchday",
"team_name",
"player_name",
"goal_difference",
"duration",
]
competitions = sorted(df_players["competition"].unique())
competition = st.sidebar.selectbox("Select Competition", competitions)
df_competition = data.filter_competition(df_players, competition)
seasons = sorted(df_competition["year"].unique())
season = st.sidebar.selectbox("Select Season", seasons)
df_season = data.filter_season(df_competition, season)
teams = sorted(df_season.sort_values("team_name")["team_url"].unique())
team = st.sidebar.selectbox(
"Select Team",
teams,
format_func=team_url_to_name.get,
)
df_team = data.filter_team_url(df_season, team)
min_appearances = st.sidebar.number_input(
"Filter players with less than input appearances",
min_value=0,
max_value=34,
value=5,
step=1,
)
fig_season = visualization.scatter_players_for_season(
df_players,
df_matches,
competition,
season,
x_column="gd90",
y_column="full_games",
min_appearances=min_appearances,
team=team,
)
st.plotly_chart(fig_season)
fig_team = visualization.scatter_players_for_team(
df_players=df_players,
df_matches=df_matches,
team=team,
competition=competition,
season=season,
x_column="gd90",
y_column="full_games",
min_appearances=min_appearances,
)
st.plotly_chart(fig_team)
fig_team_bar = visualization.bar_players_for_team(
df_players=df_players,
df_matches=df_matches,
team=team,
competition=competition,
season=season,
weight_column="full_games",
min_appearances=min_appearances,
)
st.plotly_chart(fig_team_bar)
players = df_team.sort_values("player_name")["player_url"].unique()
player = st.selectbox("Select Player",
players,
format_func=player_url_to_name.get)
df_player = data.filter_player_url(df_team, player)
default_columns = [
"matchday",
"goal_difference",
"duration",
]
selected_columns = st.multiselect("Columns to display",
options=VISIBLE_COLUMNS,
default=default_columns)
st.write(df_player[selected_columns].reset_index(drop=True))
def bar_players_for_team(
df_players,
df_matches,
competition,
season,
team,
column="gd90",
weight_column="full_games",
min_appearances: int = 5,
):
df_players = filter_competition(df_players, competition)
df_players = filter_season(df_players, season)
df_players = filter_team_url(df_players, team)
team_name = helpers.get_map_from_url_to_name(df_players, "team")[team]
df_players = get_players_goal_differences(df_players)
df_players = filter_appearances(df_players, min_appearances)
df_players = df_players.sort_values(column)
values = df_players[column]
players = df_players.index.get_level_values(2)
width_weights = df_players[weight_column]
# get mean value for team
df_matches = filter_competition(df_matches, competition)
df_matches = filter_season(df_matches, season)
team_goal_difference = goal_difference_for_team(df_matches, team)
trace = go.Bar(
x=players,
y=df_players[column],
width=0.05 + 0.7 * ((width_weights / width_weights.max())),
orientation="v",
hoverinfo="text",
hovertext=[
f"<b>{player}</b><br>{column}={value:.1f}<br>{weight_column}={weight:.1f}"
for player, value, weight in zip(players, values, width_weights)
],
marker={"color": "mediumvioletred", "line": {"width": 0}},
)
layout = get_default_layout(f"{team_name} {season}", "Player", column)
annotations = [
go.layout.Annotation(
x=-0.1,
y=0.95,
xref="paper",
xanchor="left",
yanchor="middle",
yref="paper",
text="Bar width scaled with minutes played",
font=ANNOTATION_TEXT_FONT,
)
]
shapes = [
go.layout.Shape(
type="line",
xref="paper",
x0=0,
y0=team_goal_difference,
x1=1,
y1=team_goal_difference,
line=dict(color="mediumvioletred", width=4, dash="dash",),
)
]
layout.update(annotations=annotations, shapes=shapes)
layout.xaxis.update(showgrid=False)
layout.yaxis.update(showgrid=True)
data = [trace]
fig = go.Figure(data=data, layout=layout)
return fig
def scatter_players_for_team(
df_players,
df_matches,
competition,
season,
team,
x_column="gd90",
y_column="full_games",
min_appearances: int = 5,
):
column = "gd90"
df_players = filter_competition(df_players, competition)
df_players = filter_season(df_players, season)
df_players = filter_team_url(df_players, team)
team_name = helpers.get_map_from_url_to_name(df_players, "team")[team]
df_players = get_players_goal_differences(df_players)
df_players = filter_appearances(df_players, min_appearances)
# display(df.head())
# get mean value for team
df_matches = filter_competition(df_matches, competition)
df_matches = filter_season(df_matches, season)
team_goal_difference = goal_difference_for_team(df_matches, team)
# df_team = df_grouped[df_grouped.index.get_level_values(0) == team]
player_names = df_players.index.get_level_values(2)
trace = go.Scatter(
x=df_players[x_column],
y=df_players[y_column],
mode="markers+text",
name="Players",
text=player_names,
textposition="top center",
marker={"color": "mediumvioletred", "size": 12, "symbol": "diamond",},
textfont=PLAYER_TEXT_FONT,
)
# get mean value for team
df_matches = filter_competition(df_matches, competition)
df_matches = filter_season(df_matches, season)
team_goal_difference = goal_difference_for_team(df_matches, team)
# for goal difference of team
shapes = [
go.layout.Shape(
type="line",
yref="paper",
x0=team_goal_difference,
y0=0,
x1=team_goal_difference,
y1=1,
line=dict(color="mediumvioletred", width=3, dash="dash",),
)
]
layout = get_default_layout(f"{team_name} {season}", x_column, y_column)
layout.yaxis.update(rangemode="tozero")
layout.update(shapes=shapes)
fig = go.Figure([trace], layout=layout)
return fig
def scatter_players_for_season(
df_players,
df_matches,
competition: str,
season: str,
x_column: str,
y_column: str,
min_appearances: int = 5,
team: "str" = None,
):
df_players = filter_competition(df_players, competition)
df_players = filter_season(df_players, season)
df_grouped = get_players_goal_differences(df_players)
df_grouped = filter_appearances(df_grouped, min_appearances)
teams = df_grouped.index.get_level_values(0)
players = df_grouped.index.get_level_values(2)
data = []
if team is not None:
team_name = helpers.get_map_from_url_to_name(df_players, "team")[team]
trace_team = get_scatter_for_df(
df_grouped.loc[[team]],
x_column,
y_column,
name=team_name,
marker_color="mediumvioletred",
marker_symbol="diamond",
)
data.append(trace_team)
df_grouped = df_grouped.drop(index=team)
trace_all = get_scatter_for_df(
df_grouped, x_column, y_column, name="All / other teams"
)
data.append(trace_all)
layout = get_default_layout(f"{competition} {season}", x_column, y_column)
layout.yaxis.update(rangemode="tozero")
if team is not None:
# get mean value for team
df_matches = filter_competition(df_matches, competition)
df_matches = filter_season(df_matches, season)
team_goal_difference = goal_difference_for_team(df_matches, team)
# for goal difference of team
shapes = [
go.layout.Shape(
type="line",
yref="paper",
x0=team_goal_difference,
y0=0,
x1=team_goal_difference,
y1=1,
line=dict(color="mediumvioletred", width=4, dash="dash",),
)
]
layout.update(shapes=shapes)
# fig.update_xaxes(ticks="outside", tickwidth=2, tickcolor='crimson', ticklen=10)
# fig.update_yaxes(ticks="outside", tickwidth=2, tickcolor='crimson', ticklen=10, col=1)
fig = go.Figure(data, layout=layout)
return fig