Skip to main content

Python Advanced- Visualizing the Titanic Disaster

Another post starts with you beautiful people !
Today we will work on a famous dataset Titanic Dataset taken from kaggle.
This dataset gives information about the details of the passengers aboard the Titanic and a column on survival of the passengers. Those who survived are represented as “1” while those who did not survive are represented as “0”.

The columns in the dataset are as below-
PassengerId: Passenger Identity
Survived: Whether passenger survived or not
Pclass: Class of ticket
Name: Name of passenger
Sex: Sex of passenger (Male or Female)
Age: Age of passenger
SibSp: Number of sibling and/or spouse travelling with passenger
Parch: Number of parent and/or children travelling with passenger
Ticket: Ticket number
Fare: Price of ticket
Cabin: Cabin number

Let's starts some hands on-


Let's generates descriptive statistics-






Result:





Note: if you are seeing error- ImportError: No module named 'seaborn' then it mean you need to install the seaborn library using command- pip install seaborn in the command prompt.


Result:

Let's find out the children in the dataset-


Let's count the person individually-


Now plot Male, Female, Child in Pclass-

Result:





People Who Survived and Who Didn't:




How many Male and Female survived :
                                          
Result-More females survive than males.

Let's compute pairwise correlation of columns, excluding NA/null values:-




Result:

See with the help of above visualization how you can easily transform a dataset into a story telling.
Try in your notebook and share your thoughts in comment.

Comments

Popular posts from this blog

How to use opencv-python with Darknet's YOLOv4?

Another post starts with you beautiful people 😊 Thank you all for messaging me your doubts about Darknet's YOLOv4. I am very happy to see in a very short amount of time my lovely aspiring data scientists have learned a state of the art object detection and recognition technique. If you are new to my blog and to computer vision then please check my following blog posts one by one- Setup Darknet's YOLOv4 Train custom dataset with YOLOv4 Create production-ready API of YOLOv4 model Create a web app for your YOLOv4 model Since now we have learned to use YOLOv4 built on Darknet's framework. In this post, I am going to share with you how can you use your trained YOLOv4 model with another awesome computer vision and machine learning software library-  OpenCV  and of course with Python 🐍. Yes, the Python wrapper of OpenCV library has just released it's latest version with support of YOLOv4 which you can install in your system using below command- pip install opencv-pyt...

How to install and compile YOLO v4 with GPU enable settings in Windows 10?

Another post starts with you beautiful people! Last year I had shared a post about  installing and compiling Darknet YOLOv3   in your Windows machine and also how to detect an object using  YOLOv3 with Keras . This year on April' 2020 the fourth generation of YOLO has arrived and since then I was curious to use this as soon as possible. Due to my project (built on YOLOv3 :)) work I could not find a chance to check this latest release. Today I got some relief and successfully able to install and compile YOLOv4 in my machine. In this post I am going to share a single shot way to do the same in your Windows 10 machine. If your machine does not have GPU then you can follow my  previous post  by just replacing YOLOv3 related files with YOLOv4 files. For GPU having Windows machine, follow my steps to avoid any issue while building the Darknet repository. My machine has following configurations: Windows 10 64 bit Intel Core i7 16 GB RAM NVIDIA GeForce G...

How to convert your YOLOv4 weights to TensorFlow 2.2.0?

Another post starts with you beautiful people! Thank you all for your overwhelming response in my last two posts about the YOLOv4. It is quite clear that my beloved aspiring data scientists are very much curious to learn state of the art computer vision technique but they were not able to achieve that due to the lack of proper guidance. Now they have learnt exact steps to use a state of the art object detection and recognition technique from my last two posts. If you are new to my blog and want to use YOLOv4 in your project then please follow below two links- How to install and compile Darknet code with GPU? How to train your custom data with YOLOv4? In my  last post we have trained our custom dataset to identify eight types of Indian classical dance forms. After the model training we have got the YOLOv4 specific weights file as 'yolo-obj_final.weights'. This YOLOv4 specific weight file cannot be used directly to either with OpenCV or with TensorFlow currently becau...