README.rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# generalconference

[General Conference](https://www.churchofjesuschrist.org/study/general-conference?lang=eng) is a semi-annual event where members of The Church of Jesus Christ of Latter-day
Saints gather to listen to church prophets, apostles, and other leaders.

This package both scrapes General Conference talks and provides all talks
in a data package for analysis in R. 


## Install the package

```{r, eval=F}
# install.packages('devtools')
devtools::install_github("bryanwhiting/generalconference")
```

Load the package:

```{r, message = FALSE}
library(generalconference)
```

Load the General Conference corpus, which is a tibble with nested data
for each conference, session, talk, and paragraph.

```{r}
data("genconf")
head(genconf)
```

## Getting Started

Unnest it to analyze individual talks, which can be unnested further to
the paragraph level.

```{r}
library(dplyr)
library(tidyr)
genconf %>%
  tidyr::unnest(sessions) %>%
  tidyr::unnest(talks) %>%
  head()
```

Analyze individual paragraphs that contain the word "faith":

```{r}
library(gt)
genconf %>%
  # unpack/unnest the dataframe, which is a tibble of lists
  tidyr::unnest(sessions) %>%
  tidyr::unnest(talks) %>%
  tidyr::unnest(paragraphs) %>%
  # extract just the date, title, author and paragraph
  # date, title, and author will be repeated fields, with paragraph unique
  select(date, title1, author1, paragraph) %>%
  # Filter to just the paragraphs that mention the word "faith"
  filter(stringr::str_detect(paragraph, "faith")) %>%
  # take top 5 records
  head(5) %>%
  # convert into a gt() table with row groups for date/title/author
  # (use row groups since these data are replicated by paragraph)
  group_by(date, title1, author1) %>%
  gt() %>%
  tab_options(
    row_group.background.color = 'lightgray'
  ) %>%
  tab_header(
    title='Paragraphs on Faith',
    subtitle='Grouped by talk'
  )
```


* See [Example Analysis](articles/example-analysis.html) for more examples on how to analyze the data.
* See [genconf](reference/genconf.html) for a schema of the data.

See documentation for scrapers, if you need them. But you shouldn't need them since all the data is available.