One of the most widely used features of Python is pandas. The pandas are built-in libraries of data analysis packages that can be used freely. In this example, we will develop a Python script that uses pandas to see if there is any affect of using them in Jupyter.
I am using the Titanic dataset from https://www.kaggle.com/c/titanic/data. I am sure that the same data is available from a variety of sources.
Here is our Python script that we want to run in Jupyter:
from pandas import *
training_set = read_csv('train.csv')
training_set.head()
male = training_set[training_set.Sex == 'male']
female = training_set[training_set.Sex =='female']
womens_survival_rate = float(sum(female.Survived))/len(female)
mens_survival_rate = float(sum(male.Survived))/len(male)
womens_survival_rate, mens_survival_rateThe result is that we calculate the survival rates of the passengers based on sex.
We...