Some interesting things I did the last few days:
List Comprehensions
The function below can be written with a single line of code:
ints = [1, 2, 3, 4]
times_ten = []
for i in ints:
times_ten.append(i * 10)
print(times_ten)
[10, 20, 30, 40]
It can be written like this:
times_ten = [(i * 10) for i in ints]
So on order to transform a loop to a list comprehension, in brackets we:
- Start with the code that transforms each item.
- Continue with our for statement (without a colon).
Lambda functions
To create a lambda function (temporary) equivalent of another function, we:
- Use the lambda keyword, followed by
- The parameter and a colon, and then
- The transformation we wish to perform on our argument
I also refreshed my memory on some statistics topics :
There are four different scales of measurement: nominal, ordinal, interval, and ratio. The characteristics of each scale, pivot around three main questions:
- Can we tell whether two individuals are different?
- Can we tell the direction of the difference?
- Can we tell the size of the difference?
What sets apart ratio scales from interval scales is the nature of the zero point.
And finally, I did some handling of missing values:
The technical name for filling in a missing value with a replacement value is called imputation.
Here are some pages that contain interesting data for analysis
https://www.reddit.com/r/datasets/
https://github.com/awesomedata/awesome-public-datasets
https://rs.io/100-interesting-data-sets-for-statistics/
And especially this http://www.data.gov.gr/ has a ton of data from Greece. Really interesting!