Exploring time-series data with Keshif

Your data will sometimes include measurements of a numeric data at different time points (e.g. per year). You can then analyze trends and changes over time for that measurement type. For example, datasets can describe changes of wealth or development of a country over time (commonly called “indicators” or “indexes”), changes in daily stock prices, changes in temperature in your city or in your building, or even your weight or blood pressure over time.

Above, you see a time-series data describing life-expectancy in a country. Your dataset can include multiple countries, and multiple time-series data (indicators). 

Understanding and exploring rich time-series data requires carefully designed charts and interactions. And, that’s the perfect job for Keshif! After you prepare your data, sit-back and let Keshif automatically organize time-series data for quick, effective, visual exploratory analysis. You can see the big picture, and drill down your analysis to a single time-key (such as year), or a specific record. Below, we have a series of help pages that walks through various steps in time-series analysis.