Machine Learning Random Forest with Python from Scratch - Using Matplotlib for Data Visualization (1)

The video tutorial introduces data visualization using Python, focusing on Matplotlib. It covers basic plotting techniques and demonstrates how to visualize Titanic dataset survival data by gender, class, and age. The tutorial concludes with an assignment to plot data on singles and families who died on the Titanic.

Which library is highlighted in the tutorial for 2D data plotting in Python?

• Seaborn

• Matplotlib

• Plotly

• Pandas

What is the first step in using Matplotlib for plotting?

• Load the dataset

• Import Matplotlib

• Define the axes

• Create a new Python script

In the Titanic dataset example, what does the code 'survived == 1' filter?

• Passengers who did not survive

• Passengers in first class

• All passengers

• Passengers who survived

What type of plot is used to visualize the number of survivors by gender?

• Scatter plot

• Pie chart

• Bar chart

• Line plot

What hypothesis is suggested about the survival rates of different passenger classes?

• All classes had equal survival rates

• Class 3 had the highest survival rate

• Class 2 had the lowest survival rate

• Class 1 had the highest survival rate

How many passenger classes are analyzed in the Titanic dataset example?

• Five

• Four

• Three

• Two

What age is used as the cutoff to define a child in the age group analysis?

• 10

• 12

• 15

• 18

How many children are identified as survivors in the age group analysis?

• 30

• 40

• 50

• 60

What is the assignment given at the end of the tutorial?

• Visualize survival by age

• Visualize survival by family status

• Visualize survival by ticket price

• Visualize survival by embarkation point

Which columns are suggested to help complete the assignment on family status?

• Age and Fare

• Embarked and Ticket

• SibSp and Parch

• Name and Cabin