One common warning you may encounter in R is:

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

This warning appears when you use geom_histogram() to create a histogram in ggplot2 and fail to specify the number of bins to use in the histogram.

To avoid this warning, you can use the bins argument to specify the number of bins to use:

ggplot(df, aes(x=my_variable)) +
  geom_histogram(bins=10)

The following example shows how to avoid this warning in practice.

Example: How to Avoid Warning stat_bins() using bins = 30

Suppose we use the geom_histogram() function from ggplot2 to create a histogram for some variable in a data frame:

library(ggplot2)

#make this example reproducible
set.seed(0)

#create data frame
df <- data.frame(my_values = rnorm(1000))

#view head of data frame
head(df)

   my_values
1  1.2629543
2 -0.3262334
3  1.3297993
4  1.2724293
5  0.4146414
6 -1.5399500

#create histogram
ggplot(df, aes(x=my_values)) +
  geom_histogram(col='black', fill='steelblue')

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Notice that we receive the warning `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

It’s worth noting that this is just a warning and the histogram is still created by ggplot2.

However, we can avoid the warning altogether by using the bins argument within geom_histogram() to specify the number of bins to use in the histogram.

For example, we can use the following code to use 10 bins for the histogram:

#create histogram with 10 bins
ggplot(df, aes(x=my_values)) +
  geom_histogram(col='black', fill='steelblue', bins=10)

Notice that we don’t receive any warning message this time and the histogram contains exactly 10 bins.

For example, we could instead use 5 bins:

#create histogram with 5 bins
ggplot(df, aes(x=my_values)) +
  geom_histogram(col='black', fill='steelblue', bins=5)

Notice that there are fewer but wider bins in this histogram.

Feel free to use as many bins as you’d like in your histogram.

The following tutorials explain how to troubleshoot other common errors in R:

How to Fix in R: NAs Introduced by Coercion