motivations lessons and sharing in writing a hands-on Matplotlib
motivations lessons and sharing in writing a hands-on Matplotlib

PROGRAMMING MOTIVATION

Lessons after Getting 11 Hours Reading Time in a Day

Sharing my concept in learning and writing

Did you realize that we will face the end of 2020? For me, 2020 is very bad. I could not remember what I have done this year because almost all of my activity stays home. There are only three moments that are impressed me: (1) I joined a summer school-internship at the National Astronomical Observatory of Japan (NAOJ) in January before lock-down, (2) I graduated in July, and (3)I got 11 hours of reading time in a day at the beginning of November, as shown in the header figure.

This story will share my learning concept in programming and tell the story before I got 11 hours of reading time. In the middle of October, I started to compose a ‘big project.’ I call it a ‘big project’ because I want to write a hands-on understanding and generate various plots using Matplotlib as complete as possible. As I mentioned in the hands-on, maybe what I have composed is not complete for you, but I have tried to complete it for people’s data visualization needs. The purpose is simple, to help many people visualizing their data into enormous styles. I planed to write the hands-on only in one story, but the expectation is not in-line with the reality :D I divided it into two parts. You can check it here (Part 1 and Part 2).

My first step in composing the hands-on is collecting various plotting types from many sources, from books, official documentation from Matplotlib, and discussion forums. Then, I build, revise, revise, and revise the code again to generate the plots. Before transforming it into a Medium story, I expect that the total figures I generated are about 60s figures from 11 different plotting types. It will take your time for less than 20 minutes. But, it beyond my expectation. The total figure is 42 in Part 1 and 61 in Part 2. You need to spend about 48 minutes, 23 minutes for Part 1, and 25 minutes for Part 2. I divided the hands-on into two parts because I considered that you would be bored if you had to spend more than 30 minutes and was not optimal in reading a story.

I got a standard reading time and views after I published Part 1. The unexpected moment came two days after publishing Part 2. I got 9 hours and 32 minutes of reading time, as shown in Figure 1.

motivations lessons and sharing in writing a hands-on Matplotlib
motivations lessons and sharing in writing a hands-on Matplotlib
Figure 1. Member reading time for Part 2 (Image by Author).

For me, a newcomer in Medium, the statistic was a very outstanding experience. It triggered my other stories. For Part 1, I got 1 hour and 22 minutes member reading time and about 2 hours from 12 other stories. I am not talking about how much earnings I got and how big the effect my story can help the readers visualize their data. With 4.4K views and 9.5 hours of reading time, I assume that Part 2 affects the readers significantly.

Based on my experience, I can learn and understand a programming language from trial and error. Some people may use the term learning by doing. A learner needs many resources to be put into practice. I want to become a supplier for it by writing many tutorials and completed hands-on. If I can reach many people from my writing and significantly affect them, I can achieve my goals. I also assume that they will share their experience and become the suppliers for the others. It is like multi-level marketing in learning, and I hope so. Maybe, some of them are enriching my hands-on to be better. When I read the enriched one, I will get new knowledge. It is why some people say that by sharing knowledge, you will get more knowledge. Let me write a quote from Dalai Lama,

Share your knowledge. It’s a way to achieve immortality.

To conclude, I hope I can be more creatives in writing Medium stories and you can obtain many lessons from it. Then, I also hope you can share it with others, and all of us will achieve immortality. In the future, I will write some stories about personalizing Jupyter Notebook using CSS, creating outstanding curriculum vitae with GitHub, and projects on analyzing real data using Bayesian inference. You can follow me, so you will be notified when I publish a new story.

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That’s all. Thanks.

Python Programmer || Data Scientist || Bayesian Astronomer

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