- #Q1. Find the data in the dataframe below. c
- dic = {'country': ['India', 'Japan', 'China', 'USA', 'Russia'],
- 'population': [1425.7, 123.3, 1425.4, 340, 144.4],
- 'growthrate': [6.72, 1.47, 8.5, 8.8, 4.7],
- 'gdp':[3730,4231,17786,70248,12194]}
- df = pd.DataFrame(dic)
- df
- # Create Pie charts for countries with population, growthrate, and gdp. Exclude any one by 15%.
- # Sample is given below
- plt.subplot(2,2,1)
- plt.title('countries with population')
- df.groupby('country')['population'].mean().plot(kind='pie',explode=[0.15,0,0,0,0])
- plt.subplot(2,2,2)
- plt.title('countries with growthrate')
- df.groupby('country')['growthrate'].mean().plot(kind='pie',explode=[0.15,0,0,0,0])
- plt.subplot(2,2,3)
- plt.title('countries with gdp')
- df.groupby('country')['gdp'].mean().plot(kind='pie', explode=[0.15,0,0,0,0])
- plt.legend(loc='upper left') #lower left #lower right
- plt.savefing('chart1.jpg')
- plt.show
- # Q2. Create vertical bar charts for countries with population, growthrate, and gdp.
- # Sample is given below
- plt.subplot(2,2,1)
- plt.title("count by popula")
- df.groupby('country')['population'].mean().plot(kind='bar')
- plt.subplot(2,2,2)
- plt.title("cont by growthwte")
- df.groupby('country')['growthrate'].mean().plot(kind='bar')
- plt.subplot(2,2,3)
- plt.title("cont by gdp")
- df.groupby('country')['gdp'].mean().plot(kind='bar')
- #plt.show()
- # Q3. Do the following in matplotlib
- plt.bar(df['country'],df['population'], color='b')
- for i in range (len(df['country'])):
- plt.text(i,df['population'][i],str(df['population'][i]),ha='center', va='bottom')
- plt.show()
[text] data1
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