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# Motivation

Getting up to speed with R using dose-response for 32 drugs against 6
bacterial strains.

# Tasks

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In the following, we go through the most common steps in data analysis:
exploration and transformation (to derive new variables). Integral to
both steps is visualization i.e. making graphs.
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## Explore

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1.  Plot growth curves following raw OD in time. [Input
    data](doc/tasks/01_dat.csv) and expected [output
    plot](doc/tasks/01_out.pdf) are provided. The data is for
    azithromycin against *S. flexneri* M90T from day 2022-05-04 (first
    replicate). *A tip: Use `facet_wrap` with `ncol = 1` argument to
    have different concentrations on separate plots.*
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2.  Try again, now with [data](doc/tasks/02_dat.csv) from two days (let
    us plot days in different color). In addition, transform the y-axis
    to logarithmic scale. [Expected output](doc/tasks/02_out.pdf). \_A
    tip: you need to turn the `Date` variable into a factor.\`