# Python package statistics - addition

In my earlier post today, I published some statistics about Python packages. Someone from Python users mailing lists pointed out that mean and standard deviation for such a highly skewed data was meaningless and better summary could be obtained from non-parametric statistics. So, I will publish some new statistics in this post.

### File Sizes

First, second and third quartiles are 4KB, 11.5KB and 38KB respectively. Here is a histogram of `log(size)`

### Downloads

#### Daily

First, second and third quartiles are 0, 2 and 8 respectively. I couldn't normalize the data so no histogram here.

#### Weekly

First, second and third quartiles are 16,39 and 100 respectively.

#### Monthly

First, second and third quartiles are 56, 147 and 375 respectively.

### Lines of Python code

I am not quite sure how exactly would skewness affect my predictions about population mean. I will just publish quartile parameters in my sample. First, second and third quartiles were 48, 199 and 498 respectively. It appears that most packages on PyPI are quite small. I also made a boxplot of this, but it was very squeezed and looked meaningless so I didn't post it.