In BrookfieldIIE/BFTheme: Brookfield R Theme
knitr::opts_chunk$set(echo = TRUE)
Introduction
This package, and associated data visualization style guide lays out the style elements for data visualization used at the Brookfield Institute.
Anatomy of a graphic at the Brookfield Institute
Available graph types in the current version of the package
| Graph Type | Function | Use Cases |
|---------------------------|----------------------|------------------------|
| Bar graph | plot.column.bf() | Comparing single metric across different groups |
| Scatter graph | plot.scatter.bf() | Plot relationship between two metrics across observations |
| Waffle chart | plot.waffle.bf() | Represent the shares of different groups in a population |
| Line chart | plot.line.bf() | Compare change in metric across multiple period (usually) for different groups |
| Pyramid chart | plot.pyramid.bf() | Commonly used to represent age pyramid and similar data |
| Mekko chart | plot.mekko.bf() | A variant of a bar graph where the width of each bar represents a different metric |
| Arrow Change chart | plot.change.arrow.bf() | Show change in a metric across two time periods across different groups |
| Area chart | plot.area.bf() | Used commonly to show how shares of different groups shift over time |
| Province map | plot.map.prov.bf() | Maps out data at the provincial level |
| ER map | plot.map.er.bf() | Maps out data at the Economic Region level |
| CMA map | plot.map.cma.bf() | Maps out data at the Census Metropolitan Area/Census Agglomeration level |
| CSD map | plot.map.csd.bf() | Maps out data at the Census Subdivision level |
Colours
At the Brookfiled Institute, we use three primary colours:
- Magenta:
#dd347a
- Cyan:
#8ad4df
- Indigo:
#14365d
Magenta is often used as a highlight colour, in highlighting important data points, and is not recommended to use as the base colour of comparison.
In addition, we use the following secondary colours:
- Yellow:
#faaf19
- Green:
#3c7d78
- Pink:
#ffa5b9
- Brown:
#c37546
- Ecru:
#ebe6de
- Grey:
#626466
Any graphic will use at least one colour from the primary palette. The secondary palette should not be used without any colours from the primary palette. Programmatically, the function that will generate colours is set.colours(). You can specify in a vector the specific combination of colours you'd like in the order they appear, and pass it in the colours argument in most graphing functions.
set.colours(3, categorical.choice = c("magenta","ecru","green"))
Discrete Colour combinations
The following gives suggested colour combinations for specific number of colours.
2 colours
One from the primary palette + one from secondary. For example:
- Indigo
#14365d + Green #3c7d78
- Indigo
#14365d + Ecru #ebe6de
- Magenta
#dd347a + Grey #626466
- Magenta
#dd347a + Pink #ffa5b9
- Cyan
#8ad4df + Green #3c7d78
- Cyan
#8ad4df + Pink #ffa5b9
3 colours
One primary colour + two secondary colours. For example:
- Indigo
#14365d + Green #3c7d78 + Pink #ffa5b9
- Indigo
#14365d + Brown #c37546 + Ecru #ebe6de
- Cyan
#8ad4df + Ecru #ebe6de + Grey #626466
- Magenta
#dd347a + Ecru #ebe6de + Green #3c7d78
4+ colours
When you have more than 4 colours, you are able to use more than one primary colour, and include gradient as appropriate. Note that you should never exceed more than 7 separate colours.
- Indigo
#14365d + Brown #c37546 + Pink #ffa5b9 + Yellow #faaf19
- Magenta
#dd347a + Pink #ffa5b9 + Cyan #8ad4df + Indigo #14365d
Colour gradients
In addition to discrete colours, the style guide (and the package), provide the following gradients that can be used. Gradients are especially useful in representing data that has a monotonic range interpretation (for example in heatmaps). Programmatically, you just need to specify in set.colours() how many colours you're looking for, and from which gradient you'd like the colours to come from:
set.colours(5, type = "gradient", gradient.choice="indigo")
In our official style guide, it is recommended that when gradients are used, the following three are prioritized:
- Indigo:
#14365d 
#284469 
#4f6885 
#4c6282 
#6f829b 
#8a9bae 
#8192a8 
#94a3b5
- Green:
#3c7d78 
#528b86 
#6d9e9a 
#679894 
#7ca6a2 
#9ebebc 
#a5c2bf 
#CEDFDD
- Grey:
#626466 
#7d8890 
#8a949b 
#939598 
#9a9fa3 
#a4acb1 
#a5abaf 
#b1b8bc
However, the package provides the following additional gradients for used when appropriate:
- Magenta:
#dd347a 
#e04686 
#e35892 
#e66b9e 
#e97daa 
#ec90b6 
#efa2c2 
#f2b5ce
- Cyan:
#8ad4df 
#94d7e1 
#9fdbe4 
#a9dfe7 
#b4e3ea 
#bfe7ed 
#c9ebf0 
#d4eff3
- Yellow:
#ffc800 
#ffcd17 
#ffd22e 
#ffd745 
#ffdc5c 
#ffe173 
#ffe68b 
#ffeba2
- Pink:
#ffa5b9 
#ffafc1 
#ffb9c9 
#ffc3d0 
#ffccd8 
#ffd6df 
#ffdfe7 
#ffe9ee
- Brown:
#f7941e 
#f79d32 
#f8a746 
#f9b15b 
#f9ba6f 
#fac484 
#fbce98 
#fcd8ad
Fonts
The Brookfield Institute styleguide uses 2 main family of fonts, Pressura, and Rooney. The following general conventions will determine the correct font usage when making non-standard graphics. In general, default to showing numbers using Pressura (except for cases when the numbers are integrated inside a text).
- Figure numbering: Use Pressura Bold typeface, 13pt
- Figure title: Use RooneySans Regular typeface, 11pt
- Axis titles: Use RooneySans Regular typeface, 11pt
- Axis labels: Use Pressura Light typeface, 10pt
- Legend title: Use RooneySans Light typeface, 11pt
- Legend label: Use RooneySans Light typeface, 10pt
- Annotation: Use RooneySans Regular typeface, appropriate type size.
Installation
As the fonts used by the Brookfield Institute in data visualization is licensed only for our use - you will notice that those font files are missing from this public repository. To download the package binary, go to the Policy Team Resources folder on our Google Drive and you will be able to find it here. This public version is available for reference purposes.
Installing the package is fairly straightforward, except for a fact that if you are working on a Mac, you will have to switch your RStudio graphical device to Ragg. This ensures that fonts are rendered correctly.
Update logs
Current Version: 1.2.1 (updated March 16th 2023)
New in version 1.2.1
- Fixed a bug in plot.column.bf that prevented labels to plot from stacked column
- A few minor bugs here and there
New in Version 1.2.0 (updated November 29th, 2022)
- Added option in plot.line.bf to fit loess line instead of just connecting dots
New in Version 1.1.0 (November 4th 2022)
- Added 2021 Census geographies (namely for CMA and CSD). Mapping functions default to 2021 geographies.
- Changed pacakge structure slightly, splitting each function into its own R file.
New in Version 1.0.1
- Fixed a small bug with plot.column.bf() displaying Rooney font when it should be showing Pressura font.
- Ensured every external package reference is updated.
New in Version 1.0.0
- Completely revamped font support - uses showtext now instead of extrafont
- Added option to add BIIE logo to generated graphics
- Updated graph styles to match revamped Brookfield style and font guide as of August 2022
- Note that for Caption to work properly, R graphical device has to be set to RAGG
New in Version 0.3.0
- Add new plot.area.bf Function
- Add options for ordering of column
- Fixes some irregularities in input name for plot.scatter.bf
BrookfieldIIE/BFTheme documentation built on March 24, 2023, 12:42 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
knitr::opts_chunk$set(echo = TRUE)
Introduction
This package, and associated data visualization style guide lays out the style elements for data visualization used at the Brookfield Institute.
Anatomy of a graphic at the Brookfield Institute
Available graph types in the current version of the package
| Graph Type | Function | Use Cases |
|---------------------------|----------------------|------------------------|
| Bar graph | plot.column.bf() | Comparing single metric across different groups |
| Scatter graph | plot.scatter.bf() | Plot relationship between two metrics across observations |
| Waffle chart | plot.waffle.bf() | Represent the shares of different groups in a population |
| Line chart | plot.line.bf() | Compare change in metric across multiple period (usually) for different groups |
| Pyramid chart | plot.pyramid.bf() | Commonly used to represent age pyramid and similar data |
| Mekko chart | plot.mekko.bf() | A variant of a bar graph where the width of each bar represents a different metric |
| Arrow Change chart | plot.change.arrow.bf() | Show change in a metric across two time periods across different groups |
| Area chart | plot.area.bf() | Used commonly to show how shares of different groups shift over time |
| Province map | plot.map.prov.bf() | Maps out data at the provincial level |
| ER map | plot.map.er.bf() | Maps out data at the Economic Region level |
| CMA map | plot.map.cma.bf() | Maps out data at the Census Metropolitan Area/Census Agglomeration level |
| CSD map | plot.map.csd.bf() | Maps out data at the Census Subdivision level |
Colours
At the Brookfiled Institute, we use three primary colours:
- Magenta:
#dd347a - Cyan:
#8ad4df - Indigo:
#14365d
Magenta is often used as a highlight colour, in highlighting important data points, and is not recommended to use as the base colour of comparison.
In addition, we use the following secondary colours:
- Yellow:
#faaf19 - Green:
#3c7d78 - Pink:
#ffa5b9 - Brown:
#c37546 - Ecru:
#ebe6de - Grey:
#626466
Any graphic will use at least one colour from the primary palette. The secondary palette should not be used without any colours from the primary palette. Programmatically, the function that will generate colours is set.colours(). You can specify in a vector the specific combination of colours you'd like in the order they appear, and pass it in the colours argument in most graphing functions.
set.colours(3, categorical.choice = c("magenta","ecru","green"))
Discrete Colour combinations
The following gives suggested colour combinations for specific number of colours.
2 colours
One from the primary palette + one from secondary. For example:
- Indigo
#14365d+ Green #3c7d78 - Indigo
#14365d+ Ecru #ebe6de - Magenta
#dd347a+ Grey #626466 - Magenta
#dd347a+ Pink #ffa5b9 - Cyan
#8ad4df+ Green #3c7d78 - Cyan
#8ad4df+ Pink #ffa5b9
3 colours
One primary colour + two secondary colours. For example:
- Indigo
#14365d+ Green #3c7d78+ Pink #ffa5b9 - Indigo
#14365d+ Brown #c37546+ Ecru #ebe6de - Cyan
#8ad4df+ Ecru #ebe6de+ Grey #626466 - Magenta
#dd347a+ Ecru #ebe6de+ Green #3c7d78
4+ colours
When you have more than 4 colours, you are able to use more than one primary colour, and include gradient as appropriate. Note that you should never exceed more than 7 separate colours.
- Indigo
#14365d+ Brown #c37546+ Pink #ffa5b9+ Yellow #faaf19 - Magenta
#dd347a+ Pink #ffa5b9+ Cyan #8ad4df+ Indigo #14365d
Colour gradients
In addition to discrete colours, the style guide (and the package), provide the following gradients that can be used. Gradients are especially useful in representing data that has a monotonic range interpretation (for example in heatmaps). Programmatically, you just need to specify in set.colours() how many colours you're looking for, and from which gradient you'd like the colours to come from:
set.colours(5, type = "gradient", gradient.choice="indigo")
In our official style guide, it is recommended that when gradients are used, the following three are prioritized:
- Indigo:
#14365d #284469 #4f6885 #4c6282 #6f829b #8a9bae #8192a8 #94a3b5 - Green:
#3c7d78 #528b86 #6d9e9a #679894 #7ca6a2 #9ebebc #a5c2bf #CEDFDD - Grey:
#626466 #7d8890 #8a949b #939598 #9a9fa3 #a4acb1 #a5abaf #b1b8bc
However, the package provides the following additional gradients for used when appropriate:
- Magenta:
#dd347a #e04686 #e35892 #e66b9e #e97daa #ec90b6 #efa2c2 #f2b5ce - Cyan:
#8ad4df #94d7e1 #9fdbe4 #a9dfe7 #b4e3ea #bfe7ed #c9ebf0 #d4eff3 - Yellow:
#ffc800 #ffcd17 #ffd22e #ffd745 #ffdc5c #ffe173 #ffe68b #ffeba2 - Pink:
#ffa5b9 #ffafc1 #ffb9c9 #ffc3d0 #ffccd8 #ffd6df #ffdfe7 #ffe9ee - Brown:
#f7941e #f79d32 #f8a746 #f9b15b #f9ba6f #fac484 #fbce98 #fcd8ad
Fonts
The Brookfield Institute styleguide uses 2 main family of fonts, Pressura, and Rooney. The following general conventions will determine the correct font usage when making non-standard graphics. In general, default to showing numbers using Pressura (except for cases when the numbers are integrated inside a text).
- Figure numbering: Use Pressura Bold typeface, 13pt
- Figure title: Use RooneySans Regular typeface, 11pt
- Axis titles: Use RooneySans Regular typeface, 11pt
- Axis labels: Use Pressura Light typeface, 10pt
- Legend title: Use RooneySans Light typeface, 11pt
- Legend label: Use RooneySans Light typeface, 10pt
- Annotation: Use RooneySans Regular typeface, appropriate type size.
Installation
As the fonts used by the Brookfield Institute in data visualization is licensed only for our use - you will notice that those font files are missing from this public repository. To download the package binary, go to the Policy Team Resources folder on our Google Drive and you will be able to find it here. This public version is available for reference purposes.
Installing the package is fairly straightforward, except for a fact that if you are working on a Mac, you will have to switch your RStudio graphical device to Ragg. This ensures that fonts are rendered correctly.
Update logs
Current Version: 1.2.1 (updated March 16th 2023)
New in version 1.2.1
- Fixed a bug in plot.column.bf that prevented labels to plot from stacked column
- A few minor bugs here and there
New in Version 1.2.0 (updated November 29th, 2022)
- Added option in plot.line.bf to fit loess line instead of just connecting dots
New in Version 1.1.0 (November 4th 2022)
- Added 2021 Census geographies (namely for CMA and CSD). Mapping functions default to 2021 geographies.
- Changed pacakge structure slightly, splitting each function into its own R file.
New in Version 1.0.1
- Fixed a small bug with plot.column.bf() displaying Rooney font when it should be showing Pressura font.
- Ensured every external package reference is updated.
New in Version 1.0.0
- Completely revamped font support - uses showtext now instead of extrafont
- Added option to add BIIE logo to generated graphics
- Updated graph styles to match revamped Brookfield style and font guide as of August 2022
- Note that for Caption to work properly, R graphical device has to be set to RAGG
New in Version 0.3.0
- Add new plot.area.bf Function
- Add options for ordering of column
- Fixes some irregularities in input name for plot.scatter.bf
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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