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- import numpy as np
- import pandas as pd
- import matplotlib.pyplot as plt
- import seaborn as sns
- import warnings
- warnings.filterwarnings('ignore')
- data=pd.read_csv('D:/Ajay/input/Suicide.csv')
- data=data.drop(['HDI for year','country-year'],axis=1) #dropping these two columns
- #-----Table------------------------------------------------------------------------------------------------------------------------------------------------------------
- grouop_data=data.groupby(['age','sex'])['suicides_no'].sum().unstack() #collecting data and making table using 'unstack()' function
- grouop_data=grouop_data.reset_index().melt(id_vars='age') #arranging according to age
- grouop_data_female=grouop_data.iloc[:6,:] #retrieving 6 rows using 'iloc' function
- print("\n--Table of Suicides according to Female Age Groups--\n")
- from IPython.display import display
- display(grouop_data_female) #displaying table
- print("\n")
- #-----Country vs. suicide_no-------------------------------------------------------------------------------------------------------------------------------------------
- suicidesNo=[]
- for country in data.country.unique():
- suicidesNo.append(sum(data[data['country']==country].suicides_no)) #getting total no of suicides of all countries
- suicidesNo=pd.DataFrame(suicidesNo,columns=['suicides_no'])
- country=pd.DataFrame(data.country.unique(),columns=['country'])
- data_suicide_countr=pd.concat([suicidesNo,country],axis=1) #definind data and axis to plot
- data_suicide_countr=data_suicide_countr.sort_values(by='suicides_no',ascending=False)#displaying plot in descending order(i.e. from highest no. of suicides to lowest)
- sns.barplot(y=data_suicide_countr.country[:20],x=data_suicide_countr.suicides_no[:20]) #displaying bars of only 20 countries with highest no. of suicides
- plt.title("20 Countries with Higest Suicide Number from 1985 to 2016")
- plt.show()
- #-----Population vs. Age_group-----------------------------------------------------------------------------------------------------------------------------------------
- index_suicide=[]
- for age in data['age'].unique():
- index_suicide.append(sum(data[data['age']==age].suicides_no)/len(data[data['age']==age].suicides_no)) #getting suicide rate of each age group
-
- plt.bar(['5-14 years', '15-24 years', '25-34 years', '35-54 years', '55-74 years', '75+ years'],index_suicide,align='center',alpha=0.5) #defining xticks
- plt.xticks(rotation=45) #rotating xticks by 45 degree anticlockwise
- plt.title("Suicide rates of Different Age Groups")
- plt.show()
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