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        "author": "Alex Walker",
        "author_email": "alex.walker@phc.ox.ac.uk",
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        "description": "# Change detection in prescribing data\n\nDetects changes in time series with a python wrapper around the R package gets (https://cran.r-project.org/web/packages/gets/index.html). Uses a combination of Google BigQuery and Python to query data, which is then fed to the R change detection code. Outputs a table containing results.\n\n## Installation\n`pip install change_detection`\n\nAnaconda users may have to `conda install rpy2` and `conda install geopandas` if not already installed.\n\n## Usage\nSee https://github.com/ebmdatalab/change_detection/blob/master/examples/examples.ipynb for examples of use.\n\n## Data flow\n1. Get data, by:\n    - using a csv in `data/<name>`, which must have only the fields `code`, `month`, `numerator` and `denominator`\n    - creating a BigQuery SQL query in the same folder as the notebook that you're using, query must produce a table with only the fields `code`, `month`, `numerator` and `denominator`\n    - querying any number of the OpenPrescribing measures in BigQuery\n2. Reshapes data with Pandas\n3. Splits data into chunks and passes each chunk to the R change detection code\n4. The resulting output is then extracted with further R code\n5. The R outputs are then concatenated\n\n\n## Output table\n\n### Timing Measures\n`is.tfirst` First negative break\n`is.tfirst.pknown` First negative break after a known intervention date\n`is.tfirst.pknown.offs` First negative break after a known intervention date not offset by a XX% increase\n`is.tfirst.offs` First negative break not offset by a XX% increase\n`is.tfirst.big` Steepest break as identified by `is.slope.ma`\n\n### Slope Measures\n`is.slope.ma` Average slope over steepest segment contributing at least XX% of total drop\n`is.slope.ma.prop` Average slope as proportion to prior level\n`is.slope.ma.prop.lev` Percentage of the total drop the segment used to evaluate the slope makes up\n\n### Level Measures\n`is.intlev.initlev` Pre-drop level\n`is.intlev.finallev` End level\n`is.intlev.levd` Difference between pre and end level\n`is.intlev.levdprop` Proportion of drop\n\n\n## Requirements\n\nPython with an associated install of R. Python dependencies should be dealt with on installation (though for my install, I had to install rpy2 separately. R packages should be installed with the package is first loaded.\n\n### Python installation requires:\n- ebmdatalab library https://github.com/ebmdatalab/datalab-pandas\n- rpy2 (to install R and the below libraries)\n- pandas\n- pandas-gbq\n- numpy\n\n### R installation requires:\n- zoo\n- caTools\n- gets\n\n",
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