import pandas import numpy
data = pandas.read_csv('_c10361280c0613304594ab464c014f47_nesarc_pds.csv',low_memory=False) #TO PRINT THE LENGTH OF DATA SET IN COLUMNS AND ROWS print(len(data)) print(len(data.columns)) #TO COUNT THE VARIABLE FEED C1 = data["TAB12MDX"].value_counts(sort = True) print(C1) # TO KNOW THE PERCENTAGE AND NO OF INOUT IN FOLLOWING VARIABLE. p1 = data["TAB12MDX"].value_counts(sort= False, normalize= True)*100/len(data) print(p1) #TO GET OUTPUR WITH A PEATICULAR CONFITION sub1 = data[(data["AGE"]>=18) & (data["AGE"]<=25) & (data["CHECK321"]==1)] print(sub1) s1 = sub1["AGE"].value_counts(sort = False) print(s1) s2 = sub1["CHECK321"].value_counts(sort = False) print(s2)
SUMMARY:
Here we have imported two python library which we use to analyse and visualize data present in our dataset. I have use keyword like print, data, value_counts to ease my task using python programming language. My dataset is based on NESARC nicotine consumtion and a specific entry where I have analyze the consumption of tobacco by age group of 18 to 25 years.
