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initial readme #13

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Feb 22, 2024
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initial readme #13

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42 changes: 26 additions & 16 deletions README.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -19,11 +19,9 @@ knitr::opts_chunk$set(
[![R-CMD-check](https://github.com/oxford-pharmacoepi/omock/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/oxford-pharmacoepi/omock/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The goal of omock is to ...

## Installation

You can install the development version of omock from [GitHub](https://github.com/) with:
You can install the development version of omock using:

``` r
# install.packages("devtools")
Expand All @@ -32,25 +30,37 @@ devtools::install_github("oxford-pharmacoepi/omock")

## Example

This is a basic example which shows you how to solve a common problem:
With omock we can quickly make a simple mock of OMOP CDM data.

```{r example}
```{r, warning=FALSE, message=FALSE}
library(omopgenerics)
library(omock)
## basic example code
library(dplyr)
```

What is special about using `README.Rmd` instead of just `README.md`? You can include R chunks like so:

```{r cars}
summary(cars)
We first start by making an empty cdm reference. This includes the person and observation tables (as they are required) but they are currently empty.
```{r}
cdm <- emptyCdmReference(cdmName = "mock")
cdm$person %>%
glimpse()
cdm$observation_period %>%
glimpse()
```

You'll still need to render `README.Rmd` regularly, to keep `README.md` up-to-date. `devtools::build_readme()` is handy for this.

You can also embed plots, for example:
Once we have have our empty cdm reference, we can quickly add a person table with a specific number of individuals.
```{r}
cdm <- cdm %>%
omock::mockPerson(nPerson = 1000)
```{r pressure, echo = FALSE}
plot(pressure)
cdm$person %>%
glimpse()
```

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.
We can then fill in the observation period table for these individuals.
```{r}
cdm <- cdm %>%
omock::mockObservationPeriod()
cdm$observation_period %>%
glimpse()
```
94 changes: 72 additions & 22 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -8,12 +8,9 @@
[![R-CMD-check](https://github.com/oxford-pharmacoepi/omock/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/oxford-pharmacoepi/omock/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The goal of omock is to …

## Installation

You can install the development version of omock from
[GitHub](https://github.com/) with:
You can install the development version of omock using:

``` r
# install.packages("devtools")
Expand All @@ -22,33 +19,86 @@ devtools::install_github("oxford-pharmacoepi/omock")

## Example

This is a basic example which shows you how to solve a common problem:
With omock we can quickly make a simple mock of OMOP CDM data.

``` r
library(omopgenerics)
library(omock)
## basic example code
library(dplyr)
```

What is special about using `README.Rmd` instead of just `README.md`?
You can include R chunks like so:
We first start by making an empty cdm reference. This includes the
person and observation tables (as they are required) but they are
currently empty.

``` r
summary(cars)
#> speed dist
#> Min. : 4.0 Min. : 2.00
#> 1st Qu.:12.0 1st Qu.: 26.00
#> Median :15.0 Median : 36.00
#> Mean :15.4 Mean : 42.98
#> 3rd Qu.:19.0 3rd Qu.: 56.00
#> Max. :25.0 Max. :120.00
cdm <- emptyCdmReference(cdmName = "mock")
cdm$person %>%
glimpse()
#> Rows: 0
#> Columns: 18
#> $ person_id <int>
#> $ gender_concept_id <int>
#> $ year_of_birth <int>
#> $ month_of_birth <int>
#> $ day_of_birth <int>
#> $ birth_datetime <date>
#> $ race_concept_id <int>
#> $ ethnicity_concept_id <int>
#> $ location_id <int>
#> $ provider_id <int>
#> $ care_site_id <int>
#> $ person_source_value <chr>
#> $ gender_source_value <chr>
#> $ gender_source_concept_id <int>
#> $ race_source_value <chr>
#> $ race_source_concept_id <int>
#> $ ethnicity_source_value <chr>
#> $ ethnicity_source_concept_id <int>
cdm$observation_period %>%
glimpse()
#> Rows: 0
#> Columns: 5
#> $ observation_period_id <int>
#> $ person_id <int>
#> $ observation_period_start_date <date>
#> $ observation_period_end_date <date>
#> $ period_type_concept_id <int>
```

You’ll still need to render `README.Rmd` regularly, to keep `README.md`
up-to-date. `devtools::build_readme()` is handy for this.
Once we have have our empty cdm reference, we can quickly add a person
table with a specific number of individuals.

You can also embed plots, for example:
``` r
cdm <- cdm %>%
omock::mockPerson(nPerson = 1000)

cdm$person %>%
glimpse()
#> Rows: 1,000
#> Columns: 7
#> $ person_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15…
#> $ gender_concept_id <dbl> 8507, 8507, 8532, 8532, 8507, 8507, 8507, 8532, 8…
#> $ year_of_birth <chr> "1997", "1963", "1986", "1978", "1973", "1961", "…
#> $ month_of_birth <chr> "8", "1", "3", "11", "3", "2", "12", "9", "7", "6…
#> $ day_of_birth <chr> "22", "27", "10", "8", "2", "1", "16", "5", "23",…
#> $ race_concept_id <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
#> $ ethnicity_concept_id <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
```

<img src="man/figures/README-pressure-1.png" width="100%" />
We can then fill in the observation period table for these individuals.

In that case, don’t forget to commit and push the resulting figure
files, so they display on GitHub and CRAN.
``` r
cdm <- cdm %>%
omock::mockObservationPeriod()

cdm$observation_period %>%
glimpse()
#> Rows: 1,000
#> Columns: 5
#> $ observation_period_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1…
#> $ person_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1…
#> $ observation_period_start_date <date> 2008-02-25, 2002-10-22, 1991-12-17, 201…
#> $ observation_period_end_date <date> 2010-08-14, 2019-11-12, 2013-05-08, 201…
#> $ period_type_concept_id <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
```