fpl-app/fpl-app.py at master · uobinnao/fpl-app · GitHub

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import pandas as pd
import numpy as np
import streamlit as st

df = pd.read_csv('fpldata.csv')

# print(df)

# # per90 = df["minutes"]/90
# # print(per90)

df["90s"] = df["minutes"]/90
calc_elements = ["goals", "assists", "points"]
for each in calc_elements:
    df[f"{each}_p90"] = df[each] / df["90s"]

print(df.columns)

print(df.head(20))

positions = list(df["position"].drop_duplicates())
teams = list(df["team"].drop_duplicates())

# print(df.name == 'Willock')

position_choice = st.sidebar.multiselect(
    'Choose position:', positions, default=positions)

teams_choice = st.sidebar.multiselect(
    "Teams:", teams, default=teams)

price_choice = st.sidebar.slider(
    'Max Price:', min_value=4, max_value=15.0, step=.5, value=15.0)

df = df[df['position'].isin(position_choice)]
df = df[df['team'].isin(teams_choice)]
df = df[df['cost'] < price_choice]

st.title(f"Fantasy Football Analysis")
st.markdown("### Player Dataframe")

st.dataframe(df.sort_values('points',
             ascending=False).reset_index(drop=True))

st.vega_lite_chart(df, {
     'mark': {'type': 'circle', 'tooltip': True},
     'encoding': {
         'x': {'field': 'goals_p90', 'type': 'quantitative'},
         'y': {'field': 'assists_p90', 'type': 'quantitative'},
         'color': {'field': 'position', 'type': 'nominal'},
         'tooltip': [{"field": 'name', 'type': 'nominal'}, {'field': 'cost', 'type': 'quantitative'}, {'field': 'points', 'type': 'quantitative'}],
     },
     'width': 700,
     'height': 400,
 })