#!/usr/bin/env python
# coding: utf-8

# In[8]:


#import packages
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt


# In[3]:


#read in data from csv this is from a premier league game Southampton vs Bournemouth in 2019
#I scrpaed this data from understat. I would recommend checking out the tutorial on scraping understat on my Youtube channel
#https://www.youtube.com/c/McKayJohns
df = pd.read_csv('xgtutorial.csv')


# In[4]:


df


# In[7]:


#now that we have our dataframe set up, we are going to create some lists to plot the different xG values
#4 lists - home and away xg and minutes
#We start these with zero so our charts will start at 0
a_xG = [0]
h_xG= [0]
a_min = [0]
h_min = [0]


#this finds our team names from the dataframe. This will only work as long as both teams took a shot
hteam = df['team'].iloc[0]
ateam = df['team'].iloc[-1]

for x in range(len(df['xG'])):
    if df['team'][x]==ateam:
        a_xG.append(df['xG'][x])
        a_min.append(df['minute'][x])
    if df['team'][x]==hteam:
        h_xG.append(df['xG'][x])
        h_min.append(df['minute'][x])
        
#this is the function we use to make our xG values be cumulative rather than single shot values
#it goes through the list and adds the numbers together
def nums_cumulative_sum(nums_list):
    return [sum(nums_list[:i+1]) for i in range(len(nums_list))]

a_cumulative = nums_cumulative_sum(a_xG)
h_cumulative = nums_cumulative_sum(h_xG)

#this is used to find the total xG. It just creates a new variable from the last item in the cumulative list
alast = round(a_cumulative[-1],2)
hlast = round(h_cumulative[-1],2)


# In[12]:


fig, ax = plt.subplots(figsize = (10,5))
fig.set_facecolor('#3d4849')
ax.patch.set_facecolor('#3d4849')

#set up our base layer
mpl.rcParams['xtick.color'] = 'white'
mpl.rcParams['ytick.color'] = 'white'

ax.grid(ls='dotted',lw=.5,color='lightgrey',axis='y',zorder=1)
spines = ['top','bottom','left','right']
for x in spines:
    if x in spines:
        ax.spines[x].set_visible(False)
        
plt.xticks([0,15,30,45,60,75,90])
plt.xlabel('Minute',fontname='Andale Mono',color='white',fontsize=16)
plt.ylabel('xG',fontname='Andale Mono',color='white',fontsize=16)

#plot the step graphs
ax.step(x=a_min,y=a_cumulative,color='#d3d3d3',label=ateam,linewidth=5,where='post')
ax.step(x=h_min,y=h_cumulative,color='#fd3607',label=ateam,linewidth=5,where='post')


# In[ ]: