code: # --------------
  #Importing header files
  import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  #Path of the file
  data = pd.read_csv(path)
  data.rename(columns={"Total":"Total_Medals"}, inplace=True)
  data.head(10)
  #Code starts here
  
  
  
  # --------------
  #Code starts here
  
  
  
  
  data['Better_Event'] = np.where(data['Total_Summer']>data['Total_Winter'],'Summer', 'Winter')
  data['Better_Event'] = np.where(data['Total_Summer']==data['Total_Winter'], 'Both', data['Better_Event'])
  
  better_event = data.Better_Event.value_counts().index[0]
  print(better_event)
  
  
  # --------------
  #Code starts here
  
  
  
  
  top_countries = data[['Country_Name', 'Total_Summer', 'Total_Winter', 'Total_Medals']]
  
  top_countries.drop(top_countries.tail(1).index, inplace=True, axis=0)
  print(top_countries)
  
  def top_ten(top_countries,c_name):
   country_list=[]
   df = top_countries.nlargest(10, [c_name]) 
   country_list = list(df['Country_Name'])
   return(country_list)
  
  top_10_summer = top_ten(top_countries,'Total_Summer')
  top_10_winter = top_ten(top_countries,'Total_Winter')
  top_10 = top_ten(top_countries,'Total_Medals')
  
  common = list(set(top_10_summer) & set(top_10_winter) & set(top_10))
  print(common)
  
  
  
  
  
  # --------------
  #Code starts here
  
  summer_df = data[data['Country_Name'].isin(top_10_summer)]
  winter_df = data[data['Country_Name'].isin(top_10_winter)]
  top_df = data[data['Country_Name'].isin(top_10)]
  
  summer_df.plot(kind='bar')
  winter_df.plot(kind='bar')
  top_df.plot(kind='bar')
  
  
  
  
  
  # --------------
  #Code starts here
  
  
  
  
  summer_df['Golden_Ratio'] = summer_df['Gold_Summer']/summer_df['Total_Summer']
  
  summer_max_ratio = summer_df.Golden_Ratio.max()
  summer_country_gold = summer_df.loc[summer_df.Golden_Ratio==summer_df.Golden_Ratio.max(), 'Country_Name'].values[0] 
  
  winter_df['Golden_Ratio'] = winter_df['Gold_Winter']/winter_df['Total_Winter']
  
  winter_max_ratio = winter_df.Golden_Ratio.max()
  
  winter_country_gold = winter_df.loc[winter_df.Golden_Ratio==winter_df.Golden_Ratio.max(), 'Country_Name'].values[0]
  
  top_df['Golden_Ratio'] = top_df['Gold_Total']/top_df['Total_Medals']
  
  top_max_ratio = top_df.Golden_Ratio.max()
  
  top_country_gold = top_df.loc[top_df.Golden_Ratio==top_df.Golden_Ratio.max(), 'Country_Name'].values[0]
  
  
  
  
  
  
  # --------------
  #Code starts here
  
  
  
  
  data_1=data[:-1]
  data_1['Total_Points']=data_1['Gold_Total']*3 + data_1['Silver_Total']*2 + data_1['Bronze_Total']*1
  most_points = data_1.Total_Points.max()
  best_country = data_1.loc[data_1.Total_Points==data_1.Total_Points.max(), 'Country_Name'].values[0] 
  
  
  
  
  
  
  # --------------
  #Code starts here
  
  best = data[data['Country_Name']==best_country]
  
  best=best[['Gold_Total','Silver_Total','Bronze_Total']]
  
  best.plot.bar(stacked=True)
  plt.xlabel('United States')
  plt.ylabel('Medals Tally')
  plt.xticks(rotation=45)
  
  
  
apis: matplotlib.pyplot.xticks pandas.read_csv matplotlib.pyplot.ylabel numpy.where matplotlib.pyplot.xlabel