There is a lot of free content available online which teaches you the basics of a Jupyter Notebook and the shortcuts which can save you a lot of time.Īfter typing the Python code in the code cell in the browser-based notebook it should look something like Fig. The prototyping phase is super quick and intuitive. It is very useful for data science and visualization tasks because you can see the output on the same screen. Now create a new Python 3 notebook by clicking the “new” button on the right corner.įor those who have never heard of Jupyter Notebook before, it is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text (taken from official website). This last command will open up a browser window with a Jupyter notebook session.
Just append new data at the end of this file. You can paste the URLs from more than one month. You should end up with one URL on each line. Now go ahead and paste this in a new file using your favorite text editor (mine is Sublime Text). 9.5 Copy the history for a specific period ¶ Go to the history tab of your browser and export the history. You can export the history from almost every browser. In this chapter, I will just take you through the process of completing an end-to-end project using these tools. There is a lot of information online about that. I will not go into too much detail about what Jupyter Notebook is and why you should be using it or what Matplotlib is and why you should use it. Throughout this project, we will learn about Jupyter notebooks and Matplotlib and the process of animating the visualization and saving it as a mp4 file. 9.1 Personal browsing history visualization ¶ You can see what the final visualization looks like in Fig. I decided to use my web browsing history for the last two months to generate the visualization. Everyone likes personalized visualization and I am no different. ) maps to an IP address.Īrmed with this knowledge I asked myself if I could somehow map locations of servers on a map.īut using any random set of IP addresses is not fun. For instance, if you are from Brazil, you have a specific set of unique IP addresses and if you are from Russia, you have a specific set of unique IP addresses. I had learned that the IP addresses are geo-location specific. Coincidently, I was taking a networking course at that time. I knew that I wanted to visualize something involving maps but I did not know what to visualize. I had never done any map visualization before this project so I decided to do something with maps.
I wanted to be like one of the cool people and create a visualization that was not available online. Hi people! I love data visualization! Who doesn’t like pretty graphs? If you go to /r/dataisbeautiful, you can spend a whole day just browsing through the posts.
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