> For the complete documentation index, see [llms.txt](https://ar-riyaz.gitbook.io/r-for-bioinformatics/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ar-riyaz.gitbook.io/r-for-bioinformatics/data-visualization-in-r/ggplot2-package/histogram.md).
# Histogram
## Draw a basic histogram
```r
# Load ggplot2 package
library(ggplot2)
# Load the diamonds dataset from the ggplot2 package
data(diamonds)
# Draw the basic histogram
ggplot(diamonds, aes(x = price)) +
geom_histogram()
```
A basic histogram in ggplot2
### Change the bin size
```
ggplot(diamonds, aes(x = price)) +
geom_histogram(bins = 50)
```
Here, bin size is changed to **50**.
A histogram with bin size 50
## Use `fill` and `col` as attribute:
Here, we will use `fill` and col as an attribute with the `geom_histogram()` function.
### Change the color of the histogram
```r
ggplot(diamonds, aes(x = price)) +
geom_histogram(bins = 50, fill = "turquoise4")
```
**Output:**
Histogram with color
### Add color to the boundary of the histogram
```r
ggplot(diamonds, aes(x = price)) +
geom_histogram(bins = 50, fill = "turquoise4", col = "deeppink2")
```
**Output:**
## Use `fill` as aesthetic:
Instead of using the `fill` with `geom_histogram()` function if we use them inside `aes()`, then we will get different visualization.
```r
# Use fill as aesthetic
ggplot(diamonds, aes(x = price, fill=cut)) +
geom_histogram()
```
Here, `fill=cut`, will color the histogram based on cut type in the diamonds dataset.
