Update app.py

app.py

@@ -36,9 +36,9 @@ warnings.filterwarnings('ignore')
 # import yahoo_oauth
 import json
 #import openpyxl
-#from sklearn import preprocessing
+# from sklearn import preprocessing
 from datetime import timedelta
-#import dataframe_image as dfi
+# import dataframe_image as dfi
 # from google.colab import drive
 def percentile(n):
     def percentile_(x):
@@ -46,25 +46,25 @@ def percentile(n):
     percentile_.__name__ = 'percentile_%s' % n
     return percentile_
 
-import os
-#import praw
-import matplotlib.pyplot as plt
-import matplotlib.colors
-import matplotlib.colors as mcolors
-cmap_sum = matplotlib.colors.LinearSegmentedColormap.from_list("", ["#4285f4","#FFFFFF","#F0E442"])
+# import os
+# import praw
+# import matplotlib.pyplot as plt
+# import matplotlib.colors
+# import matplotlib.colors as mcolors
+# cmap_sum = matplotlib.colors.LinearSegmentedColormap.from_list("", ["#4285f4","#FFFFFF","#F0E442"])
 #import pybaseball
 import math
-import matplotlib.ticker as mtick
-import matplotlib.ticker as ticker
+# import matplotlib.ticker as mtick
+# import matplotlib.ticker as ticker
 
-colour_palette = ['#FFB000','#648FFF','#785EF0',
-                  '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']
-import matplotlib.colors as mcolors
-from  matplotlib.ticker import FuncFormatter
-from matplotlib.font_manager import FontProperties
+# colour_palette = ['#FFB000','#648FFF','#785EF0',
+                #   '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']
+# import matplotlib.colors as mcolors
+# from  matplotlib.ticker import FuncFormatter
+# from matplotlib.font_manager import FontProperties
 
 import numpy as np
-import matplotlib.pyplot as plt
+# import matplotlib.pyplot as plt
 import matplotlib.colors
 
 #x,y,c = zip(*np.random.rand(30,3)*4-2)
@@ -387,7 +387,7 @@ def server(input, output, session):
             'L'+str(n_2)+' PP%': '{:.0%}',
             'L'+str(n_3)+' PP%': '{:.0%}',
             'Roster%': '{:.0%}',
-            },).background_gradient(cmap=co, subset=[x for x in cols if x.endswith('PP%')]+['Roster%']).hide_index()
+            },).background_gradient(cmap=co, subset=[x for x in cols if x.endswith('PP%')]+['Roster%'])
 
         return df_style_bang