Plot alignment scatterplot — plot_scatter_animated • pacta.multi.loanbook

Plot alignment scatterplot

Usage

plot_scatter_animated(
  data,
  data_level = c("company", "group_var"),
  sector = NULL,
  scenario_source = NULL,
  scenario = NULL,
  region = NULL,
  title = NULL,
  subtitle = NULL,
  alignment_limit = NULL,
  cap_outliers = NULL,
  floor_outliers = NULL
)

prep_scatter_animated(
  data_bopo,
  data_net,
  data_level = c("group_var", "company"),
  sector,
  region,
  group_var,
  groups_to_plot = NULL
)

Arguments

data: data.frame. Should have the same format as output of prep_scatter_animated() and contain columns: 'name', 'buildout', 'phaseout', 'net' and 'year'.
data_level: Character. Level of the plotted data. Can be 'group_var' or 'company'.
sector: Character. Sector to filter data on.
scenario_source: Character. Scenario source to be used in the plot caption.
scenario: Character. Scenario name to be used in the plot caption.
region: Character. Region to filter data on.
title: Character. Custom title if different than default.
subtitle: Character. Custom subtitle if different than default.
alignment_limit: Numeric. Limit to be applied to the x- and y-axis scales and to alignment values for colouring. By default the maximum absolute alignment value from data is used.
cap_outliers: Numeric. Cap which should be applied to the alignment values in the data. Values bigger than cap are plotted on the border of the plot.
floor_outliers: Numeric. Floor which should be applied to the alignment values in the data. Values smaller than floor are plotted on the border of the plot.
data_bopo: data.frame. Data containing buildout and phaseout alignment values. Must contain columns: 'year', 'sector', 'region', 'direction' and either 'name_abcd' and 'alignment_metric' or 'exposure_weighted_net_alignment' plus any column implied by group_var.
data_net: data.frame. Data containing net alignment values. Must contain columns: group_var, 'year', 'sector', 'region', 'direction' and either 'name_abcd' and 'alignment_metric' or 'exposure_weighted_net_alignment'.
group_var: Character. Vector of length 1. Variable to group by.
groups_to_plot: Character vector. Groups to filter on.

Value

object of type "plotly"

data.frame

Examples

# TODO