# --------------
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

#Path of the file
path

#Code starts here
data=pd.read_csv(path)
data.rename(columns = {"Total": "Total_Medals"}, inplace = True) 
data.head(10)


# --------------
#Code starts here
data['Better_Event']=np.where(data['Total_Summer']>data['Total_Winter'],'Summer',np.where(data['Total_Summer']==data['Total_Winter'],'Both','Winter'))
better_event=data['Better_Event'].value_counts().idxmax()
print(better_event)


# --------------
#Code starts here
top_countries=data[['Country_Name','Total_Summer', 'Total_Winter','Total_Medals']]
top_countries=top_countries[:-1]
def top_ten(data,col):
    country_list=[]
    country_list= list((data.nlargest(10,col)['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))



# --------------
#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)]
plt.figure(figsize=(20, 6))
plt.bar(summer_df['Country_Name'], summer_df['Total_Summer'])
plt.title('Top 10 Summer')
plt.xlabel('Country Name')
plt.ylabel('Total Medals')



# --------------
#Code starts here
summer_df['Golden_Ratio']=summer_df['Gold_Summer']/summer_df['Total_Summer']
summer_max_ratio=max(summer_df['Golden_Ratio'])
summer_country_gold=summer_df.loc[summer_df['Golden_Ratio'].idxmax(),'Country_Name']

winter_df['Golden_Ratio']=winter_df['Gold_Winter']/winter_df['Total_Winter']
winter_max_ratio=max(winter_df['Golden_Ratio'])
winter_country_gold=winter_df.loc[winter_df['Golden_Ratio'].idxmax(),'Country_Name']

top_df['Golden_Ratio']=top_df['Gold_Total']/top_df['Total_Medals']
top_max_ratio=max(top_df['Golden_Ratio'])
top_country_gold=top_df.loc[top_df['Golden_Ratio'].idxmax(),'Country_Name']





# --------------
#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']
most_points=max(data_1['Total_Points'])
best_country=data_1.loc[data_1['Total_Points'].idxmax(),'Country_Name']



# --------------
#Code starts here
best=data[data['Country_Name']==best_country]
best.reset_index(drop = True, inplace = True)
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)
l=plt.legend()
l.get_texts()[0].set_text('Gold_Total :' + str(best['Gold_Total'].values))
l.get_texts()[1].set_text('Silver_Total :' + str(best['Silver_Total'].values))
l.get_texts()[2].set_text('Bronze_Total :' + str(best['Bronze_Total'].values))





