Hi! Welcome to this data visualization.
We will explore how the survival rate changes with age, gender, and passenger class of passengers.
First let's look at age. The age information of passengers (out of the total passengers) are available in the dataset.
We will be able to see how survival rate changes with varying age range selection out of these records.
The selection first starts with 0, and gradually increases up to 10 (exclusive).
We can see the survival age of passengers below 10 is pretty high. It is always above 60%.
The selection now slowly increases up to the maximum age. Watch how the survival rate changes with the expanding selection.
Since the selection includes age 10 onwards, the survival rate has never been more than 60%.
We can see the overall trend is that, as the upper bound of the selection increases with age, survival rate decreases.
We can see the overall trend is that, as the upper bound of the selection increases with age, survival rate decreases.
Let's go back to the whole set of data (of all passengers). Next, we will see which gender group has the highest survival rate.
First we look only at the data of male passengers.
Next, only the data of female passengers.
It is obvious that the survival rate of female passengers is much higher than that of male passengers.
Finally, we are going to explore which passenger class has the highest survival rate.
First, only the data of passengers in lower class are selected.
Then, only the data of passengers in middle class are selected.
Lastly, only the data of passengers in upper class are selected.
It is clear that the survival rate of passengers in upper class is much higher than those of other two classes.
We have finished watching the visualization of how survival rate changes with each of the three attributes.
You can now freely use the brush or click on the class label to explore the data in different combination of selection. Thanks for watching!