Introduction to R and RStudio
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Visualisation with ggplot2Setting valuesGeometrical objects
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Controlling the transparency can be a great way to “mute” the visual
effect of certain data, while still keeping it visible. Its a great tool
when you have many data points or if you have several geoms together,
like we will see soon.
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In the graph above, each geom inherited all three mappings: x, y and
colour. If we want only single linear model to be built, we would need
to limit the effect of colour aesthetic to only
geom_point() function, by moving it from the “parent”
function to the layer where we want it to apply. Note, though, that
because we want the colour to be still mapped to the
island variable, it needs to be wrapped into
aes() function and supplied to mapping
argument.
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Look at that! The data actually reveals something called the “simpsons
paradox”. It’s when a relationship looks to go in a specific direction,
but when looking into groups within the data the relationship is the
opposite. Here, the overall relationship between bill length and depths
looks negative, but when we take into account that there are different
species, the relationship is actually positive.
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Subsetting data with dplyrWrap-up
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Data sorting and pipes dplyrWrap-up
Data visualisation and scalesPiping into ggplotAdding colourChanging colourChanging the overall lookWrap up
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Data manipulation with dplyrAdding new variables,Wrap up
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Reshaping data with tidyrCreating longer dataWrap up
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Data summaries with dplyrMotivation
Complex data pipelinesMotivation
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The last plot is misleading because the data we have summary data by
species and island. Ignoring the island in the plot, means that the
values for the different measurements cannot be distinguished from
eachother.
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ok, so we got what we asked, the year part makes more sense, but its a
very “busy” plot. Its really quite hard to compare everything from
Bisoe, or all the Adelie’s, to each other. How can we make it
easier?
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facet_grid is more complex than facet_wrap as
it will always force the y-axis for rows, and x-axis for columns remain
the same. So wile setting scales to free will help a little, it will
only do so within each row and column, not each subplot. When the
results do not look as you like, swapping what are rows and columns in
the grid can often create better results.
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the classic theme is preferred by many journals, but for facet grid, its
not super nice, since we loose grid information.
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Theme light could be a nice option, but the white text of light grey
makes the panel text hard to read.
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