If you don’t try, you will never know.
After almost 6 months of preparation and hard work, it finally paid off with two job offers in data science. Looking back over the past half-year (11/2019–05/2020), it was one of the most uncertain periods of my life, forwent a 3-year postdoc…
On 2nd Feb, I launched a web dashboard for tracking the spread of recent coronavirus (COVID-19) outbreak, which provides a real-time view of global confirmed, recovered, and death cases.
It so far has attracted more than 17,000 active users and was shared almost 3,500 times on social media. I am…
Correlation is one of the most fundamental statistical concepts used in almost any sectors.
For example, as in portfolio management, correlation is often used to measure the amount of diversification among the assets contained in a portfolio. Choosing assets with low or negative correlation with each other can help to…
Python is slow.
I bet you might encounter this counterargument many times about using Python, especially from people who come from
Java world. This is true in many cases, for instance, looping over or sorting Python arrays, lists, or dictionaries can be sometimes slow. After all…
The prerequisite for doing any data-related operations in Python, such as data cleansing, data aggregation, data transformation, and data visualisation, is to load data into Python. Depends on the types of data files (e.g.
.json, Excel spreadsheets, relational databases etc.) and their size, different methods should…
Last week, I shared with you how to make a dashboard to track the spread of coronavirus using Dash in python, from which you can have a real-time overview of the numbers of global coronavirus cases, including confirmed, recovered and deaths cases, and their distribution on a world map.
Update: the dashboard has changed a lot since this post, check it out!
From my previous posts about the hierarchical structure of
matplotlib plotting and the many ways to instantiate
axes, we can see that these features render
matplotlib a great potential for creating highly complex and customisable visualisations. …
matplotlib is extremely powerful and the only limitation might be our imagination, it is a bit challenging for new users to find the right path, as there is always more than one way to achieve the same goal in
axes is one of them.
I believe one of the main current events you have read about must be the Australian Bushfire Crisis. The devastating disaster has affected more than 10 million hectares of land, which is compatible to the land area of Portugal, and an estimated 1 billion wild mammals, birds and reptiles have…