# Installation, Initialization, and Data Cleaning

## Prerequisites

leadeR relies on spaCy, a Python NLP library, via the spacyr R package. You will need:

- Python (3.8 or later)
- spaCy with an English language model

Install spaCy and the English model from a terminal:

    pip install spacy
    python -m spacy download en_core_web_sm

## Installing leadeR

Install leadeR from GitHub:

    # install.packages("remotes")
    remotes::install_github("mmukaigawara/leadeR")

## Initialization

Before using any leadeR function, initialize spaCy and (optionally) set a seed for reproducibility of bootstrap results.

    library(leadeR)
    library(data.table)

    spacyr::spacy_initialize()

    set.seed(02138)

## Sample data

The package ships with three speeches by John F. Kennedy:

Dataset | Date | Occasion
--- | --- | ---
`jfk19610120` | January 20, 1961 | Inaugural Address
`jfk19610925` | September 25, 1961 | Address Before the UN General Assembly
`jfk19630610` | June 10, 1963 | Commencement Address at American University

    head(jfk19571101)

## Text cleaning

Speech transcripts often contain editorial annotations in brackets, parentheses, or curly braces. The `clean_text()` function removes these and normalizes whitespace.

    jfk1 <- clean_text(jfk19610120)
    jfk2 <- clean_text(jfk19610925)
    jfk3 <- clean_text(jfk19630610)

Users may need additional cleaning steps depending on the source of their text data (e.g., removing headers, footers, or speaker labels).