Covid-19, also known as the coronavirus, is an infectious disease that has caused a global pandemic, with significant impacts on public health, the economy, and society. From an analytics perspective, the covid-19 pandemic presents a unique and challenging opportunity to analyze and understand the spread and impact of the disease, and to develop and apply data-driven approaches to mitigate its effects. Analyzing covid-19 data can help to identify trends and patterns in the spread of the disease, and to identify factors that may be associated with its transmission and severity. This can provide valuable insights into the dynamics of the pandemic, and can inform public health policies and interventions, such as social distancing measures and vaccination campaigns.
The spreading of COVID-19 has led to an increased interest in displaying region and country-specific information on geographic heat maps. Geographic heat maps use color shadings to visualize data that includes a spatial component and refers, for example, to countries, cities, towns, mountains, etc. The color shades are defined in … Read more
This article shows how you can create a correlation matrix in Python to visualize the correlation between various asset classes and COVID-19. Correlation is a statistical measure that describes the linear relationship between two independent variables. In financial market analysis, correlation plays an important role, as it measures how assets … Read more
REST APIs provide straightforward access to remote data sources. Data scientists should learn about REST APIs because APIs (Application Programming Interfaces) are an important way for data scientists to access data from other sources. By using REST APIs, data scientists can access data from a wide range of sources, including … Read more