# Mutarise transformation

{ mutarise: ... }

mutarise is a combination of mutate and summarise. Its syntax is identical to summarise, but instead of collapsing the dataframe to a single row or one row per group, it will add one or more new columns with the summarised values. This might seem strange, but is actually very powerful in combination with mutate to calculate all sorts of useful values. For example, if you have a dataframe with one column containing dates, and one column containg sales turnover of that day. It could be interesting to calculate what percentage of your total turnover over the entire period was made on which day. To do this, you would have to get the sum of the entire column, and divide each row by that amount. This can be solved by using mutarise followed by mutate.

# Instructions

# Usage

As mentioned before, the syntax to mutarise is the same as summarise. The difference, however, is the result of the operation. When summarising an entire dataframe (i.e. ungrouped data), the result will always be a new dataframe with only one row. While mutarise, instead, adds a column to the existing dataframe for each new column mentioned in the instructions Object.

<vgg-data
  :data="{ a: [1, 2, 3, 4] }"
  :transform="{ summarise: { sumA: { a: 'sum' } } }"
>

  <!-- Data scope: { a: [1, 2, 3, 4], sumA: [10, 10, 10, 10] } -->

</vgg-data>

Moreover, when working with grouped data, summarise will return a new dataframe with one row for each group. mutarise will add the same number of columns regardless of how many groups- the only difference is that the values inside of the added column will differ per group:

<vgg-data
  :data="{ value: [1, 2, 3, 4], fruit: ['apple', 'banana', 'apple', 'banana'] }"
  :transform="[
    { groupBy: 'fruit' },
    { mutarise: { totalFruit: { value: 'sum' } } }
  ]"
>

  <!-- Data scope: {
    value: [1, 2, 3, 4],
    fruit: ['apple', 'banana', 'apple', 'banana'],
    totalFruit: [4, 6, 4, 6]
  } -->

</vgg-data>