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We can cut and paste this table into Excel to enable further analysis and visualization. Also the summary data is analyzed on a regular basis and the results made available as CSV files at https://www-iepm.slac.stanford.edu/pinger/prmout/. The file names (e.g.average_rtt-EDU.SLAC.STANFORD.PINGER-continent-allmonthly.csv) provide the metric (average_rtt in example), the Monitoring Agent (EDU-SLAC.STANFORD.PINGER in example), the region (continent or country) and the time window of each data point (or Tick, e.g. monthly (=last 12 months), allmonthly, or allyearly).

Using Motion Charts to look at PingER data versus Covid cases

One attempt to explore and correlate the impacts is to use a Motion Charts tool to look for correlations between say Covid-19 cases (cases, hospital admissions, deaths etc.) and PingER metrics as a function of time, by country, continent, plus population or density of population. The idea is that as Covid-19 cases pass say 100, the country will impose interventions such as school closing,  social distancing etc. which will change the usage patterns of the Internet which may have noticeable impacts on the PingER measurements. We use the PingER 'Lasat120days' data measured from SLAC as provided and updated daily in https://www-iepm.slac.stanford.edu/pinger/prmout/. The data is available by metric, country Monitoring Agent (in this case pinger.slac.stanford.edu)' as Excel csv files, e.g. ipdv-EDU.SLAC.STANFORD.PINGER-country-last120days.csv.  By means of a script covid.pl we create Excel csv files available at https://www-iepm.slac.stanford.edu/pinger/covid/ by PingER Metric and Covid-19 Confirmation cases and deaths, e.g. ipdv-confirmed.txt. These covid/ files are suitable for copying into www.charte.ca to create motion charts for  selected Pinger metric vs Covid-19  case by country by day.

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See Using Chart.ca and an example.

Examining using PingER metrics from pingtable.pl

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