Exploring time-series data with Keshif

What is Time-Series Data?

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.

Preparing Time-Series Data


Seeing all time-series data of a single record

The record panel includes all time-series information of the selected record, along with other attributes. The pop-up window is also animated to show the progression over time more intuitively.


Exploring time-series trends of all records with time-series view


Exploring relations between time-series data with synced scatter-plot view


Exploring relations in time-series data by location with map view


Troubleshooting and caveats with time-series data


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