Growth of data is exponential compare to number of data scientist. With so much information being collected through data analysis in the business world today, we must have a way to analyze and understand the data more quickly and extract its value to business to have an edge against the competitor.

Data visualization has a vital role in decision-making process. With the help of interactive visual representation of data, businesses can now recognize patterns and make decisions according to it. …


I started data visualization with python matplotlib, making a static charts to convey the results of the analysis. But the Exploratory Data Analysis stage becomes too tedious if you have too many features to consider. To address this issue, interactive viz comes into play.

My first interactive viz experience is with python module: Dash|Plotly. It requires basic knowledge on HTML and CSS.

Next is with ipython widget. It is easier to use compare to Dash.

Then comes Tableau. Exploring the data and creating an interactive viz with it in a very intuitive way. Especially if the data includes geographical data…


Data visualization with spreadsheets and python is becoming more common. It is no longer about a picture or a graph that represents the numbers but an application with user interaction in which the graph updates or changes according to user input. Communicating insight is never been so flexible. Ability to change the graph and the data on it in a few clicks is handy to effectively convey the information on a different perspective.

I am studying Data Science and I am struggling to deliver the insights and the analysis I gather about the data. So I ask myself why not…

Emmanuel Pagayonan

Data Science Student, Electronics Engineer, Software Developer

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