From b7316839890df748dad63fc830bc416617ae7a49 Mon Sep 17 00:00:00 2001
From: Koushik R Kirugulige <koushikkirugulige@gmail.com>
Date: Mon, 12 Oct 2020 17:17:54 +0530
Subject: [PATCH] laliga 538 prediction storage

copies all the la liga prediction after completion of each match day and stores in a csv https://projects.fivethirtyeight.com/soccer-predictions/la-liga/
---
 laliga.py | 98 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 98 insertions(+)
 create mode 100644 laliga.py

diff --git a/laliga.py b/laliga.py
new file mode 100644
index 0000000..76039ca
--- /dev/null
+++ b/laliga.py
@@ -0,0 +1,98 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]:
+
+
+import pandas as pd
+import datetime
+import logging
+#yesterday gets yesterday's date in MMDDYYYY format and compare if that is a laliga matchday max date and proceed to get the prediction from 538 website
+
+logging.basicConfig(filename="laliga.log",format='%(asctime)s %(message)s',filemode='w')
+
+yesterday = (datetime.date.today() - datetime.timedelta(days=1)).strftime("%m/%d/%Y")
+
+df_match_day = pd.read_csv('LaLigaMatchday.csv')
+
+logger=logging.getLogger()
+logger.setLevel(logging.DEBUG)
+
+if yesterday not in df_match_day.Date.values:
+    logger.info("not an end of matchday")
+    exit()
+# In[81]:
+#else part
+matchday_no = df_match_day.index[df_match_day['Date'] == yesterday].to_list()[0]
+logger.info("it is end of matchday number: %d",matchday_no)
+df = pd.read_html('https://projects.fivethirtyeight.com/soccer-predictions/la-liga/',attrs={'class': 'forecast-table'},header=2)
+df = pd.DataFrame(df[0])
+
+
+# In[83]:
+
+
+df = df[['team','win La Ligawin league']]
+#df.head()
+
+
+# In[79]:
+
+
+import re
+def clean(team_name):
+    #print(team_name)
+    #print(re.sub("pts","",team_name))
+    team_name = re.sub("\ pts","",team_name)
+    return re.sub("[0-9]+","",team_name)
+
+
+
+# In[91]:
+
+
+def merge_col(row):
+    if 'list' in str(type(row['Win League'])):
+        lst = list(row['Win League'])
+    else:
+        lst = []
+        lst.append(int(row['Win League']))
+
+    lst.append(int(row['new column']))
+    return lst
+
+
+
+import re
+df['win La Ligawin league'] = df['win La Ligawin league'].str.replace(r'\%','')
+df['win La Ligawin league'] = df['win La Ligawin league'].str.replace(r'\<','')
+df = df.rename(columns={'2':'rows','win La Ligawin league':'Win League'})
+df['team'] = df['team'].apply(clean)
+df = df.sort_values(by=['team'])
+#df.head()
+
+
+import glob
+filename  = 'la liga.csv'
+ispresent = glob.glob(filename)
+if not ispresent:
+    df.to_csv(filename,index=False,encoding='utf-8-sig')
+    # exit here
+    exit()
+else:
+    main_df = pd.read_csv(filename)
+    print(main_df.head())
+
+# In[88]:
+
+
+main_df = pd.merge(main_df,df,on='team')
+main_df = main_df.rename(columns = {'Win League_x':'Win League','Win League_y':'new column'})
+
+
+
+main_df['Win League'] = main_df.apply(merge_col,axis = 1)
+main_df = main_df.drop(['new column'],axis = 1)
+main_df.to_csv(filename,index=False,encoding='utf-8-sig')
+#main_df.head()
+logger.info("Done writing to laliga.csv")