# GGPLOT LOG SCALE TRANSFORMATION

This article describes how to create a **ggplot** with a **log scale**. This can be done easily using the ggplot2 functions *scale_x_continuous*() and *scale_y_continuous*(), which make it possible to set log2 or log10 axis scale. An other possibility is the function *scale_x_log10*() and *scale_y_log10*(), which transform, respectively, the x and y axis scales into a *log scale: base 10*.

Note that, the scale functions transform the data. If you fit anything to the data it would probably change the fitted values.

An alternative is to use the function *coord_trans*() for transformed Cartesian coordinate system. *coord_trans*() is different to scale transformations in that it occurs after statistical transformation and will affect only the visual appearance of geoms.

In this R graphics tutorial, you will learn how to:

**Log transform x and y axes**into log2 or log10 scale**Show exponent after the logarithmic changes**by formatting axis ticks mark labels.**Display log scale ticks**. R function:*annotation_logticks*()

Contents:

- Key ggplot2 R functions
- Set axis into log2 scale
- Set axis into log10 scale
- Display log scale ticks mark
- Conclusion

## Key ggplot2 R functions

Start by creating a scatter plot using the `cars`

data set:

```
library(ggplot2)
p <- ggplot(cars, aes(x = speed, y = dist)) +
geom_point()
p
```

R functions to set a logarithmic axis:

- p + scale_x_log10(), p + scale_y_log10() : Plot x and y in log 10 scale, respectively.
- p + coord_trans(x = “log2”, y = “log2”): Transformed cartesian coordinate system. Possible values for x and y are “log2”, “log10”, “sqrt”, …
- p + scale_x_continuous(trans = “log2”), p + scale_y_continuous(trans = “log2”). Allowed value for the argument trans, include also ‘log10’.
- p + scale_y_log10() + annotation_logticks(): Display log scale ticks.

## Set axis into log2 scale

- Log2 transformation of x and y axes
- Format ticks label to show exponents

```
# Possible values for trans : 'log2', 'log10','sqrt'
p + scale_x_continuous(trans = 'log2') +
scale_y_continuous(trans = 'log2')
# Format y axis tick mark labels to show exponents
require(scales)
p + scale_y_continuous(trans = log2_trans(),
breaks = trans_breaks("log2", function(x) 2^x),
labels = trans_format("log2", math_format(2^.x)))
```

## Set axis into log10 scale

The following R code changes the y axis scale into log10 scale using the function `scale_y_log10()`

:

`p + scale_y_log10()`

Alternatively, you can use the function `scale_y_continuous()`

, which allows to transform breaks and the format of labels.

`p + scale_y_continuous(trans = "log10")`

## Display log scale ticks mark

Note that, log scale ticks make sense only for log scale base 10.

Key function: `annotation_logticks()`

Data: `Animals`

data sets, from the package `MASS`

- Create a log-log plot without log scale ticks:

```
# Load packages
require(MASS) # to access Animals data sets
require(scales) # to access break formatting functions
data(Animals) # load data
# x and y axis are transformed and formatted
p2 <- ggplot(Animals, aes(x = body, y = brain)) + geom_point() +
scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x))) +
scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x))) +
theme_bw()
p2
```

- Show log scale ticks:

`p2 + annotation_logticks() `

Note that, default log ticks are on bottom and left. To specify the sides of the log ticks :

```
# Log ticks on left and right
p2 + annotation_logticks(sides="lr")
# All sides
p2+annotation_logticks(sides="trbl")
```

Allowed values for the argument `sides`

are the combination of “t” (top), “r” (right), “b” (bottom), “l” (left).

## Conclusion

We introduce how to create a ggplot with log scale. Briefly, the steps are as follow:

- Create an example of ggplot:

```
library(ggplot2)
p <- ggplot(cars, aes(x = speed, y = dist)) +
geom_point()
```

- Log transformation of the axis scale:

```
# log base 2 scale
p + scale_x_continuous(trans = 'log2') +
scale_y_continuous(trans = 'log2')
# Log base 10 scale + log ticks (on left and bottom side)
p + scale_x_continuous(trans = 'log10') +
scale_y_continuous(trans = 'log10')+
annotation_logticks(sides="lb")
```

# Python Example for Beginners

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