# A procedure to create a disparity matrix between categories.

### Description

Takes a data frame or a matrix to create a disparity matrix

### Usage

1 | ```
dis_categories(data, method = "euclidean", category_row = FALSE)
``` |

### Arguments

`data` |
A numeric matrix with entities |

`method` |
A distance or dissimilarity method available in "proxy" package as for example "Euclidean", "Kullback" or "Canberra". This argument also accepts a similarity method available in the "proxy" package, as for example: "cosine", "correlation" or "Jaccard" among others. In the latter case, a correspondent transformation to a dissimilarity measure will be retrieved. A list of available methods can be queried by using the function |

`category_row` |
A flag to indicate that categories are in the rows. The analysis assumes that the categories are in the columns of the matrix. If the categories are in the rows and the entities in the columns, then the argument "category_row" has to be set to TRUE. The default value is FALSE. |

### Value

A distance or dissimilarity square matrix

### Examples

1 | ```
Xdis <- dis_categories(pantheon)
``` |