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Processing and accessing mobility data #2
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data extraction from pdf to csv with python: |
These mobility data are generally far more useful as a time series, especially going backwards, so that modelers can calibrate their models to the change in mobility that occurred over the past month(s). So the task includes either
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If this becomes an Google API wrapping project, I might be of use. Unfortunately, it currently looks like a PDF parsing project, at least re: data ingest. |
I note there's an R workflow for parsing the PDF using |
full extraction including trend lines in R! |
+1 for this great repo and initiative! |
If someone could extend @nacnudus's repo/script/data above to include the county-level U.S. data it would be an enormous help. |
See also this one by the UK Office for National Statistics. |
Data problems have been fixed 🤞 https://github.com/nacnudus/google-location-coronavirus |
US counties now in the "region" file https://github.com/nacnudus/google-location-coronavirus/blob/master/2020-03-29-region.tsv. It hasn't been checked extensively though, so take care. |
Great, thanks a lot @nacnudus. |
@nacnudus, is your solution still working with the new mobility reports published yesterday? |
@ffinger, it seems to have run fine on the new reports. |
Brilliant, will close the issue then. |
Google has started providing mobility statistics derived from mobility data from smartphone users: https://www.google.com/covid19/mobility/.
Description
For public health officials and researchers it will be crucial to be able to follow the evolution of those mobility indicators through time and to integrate them in automated analyses. A means to automatically access those indicators (and their evolution) from within R code is thus needed.
Output
The proposed output is a data frame in long format with columns for country, date, indicator and values.
Impact
This will allow to follow mobility indicators automatically from within R code, which will allow for analysis of (for example) the impact of mobility reduction on transmissibility.
Proposed Timeline
First version of package available on Apr 10.
Focal Point
@ffinger
Links
Could be integrated into https://github.com/epiforecasts/NCoVUtils or live as a separate package.
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