advanced data processing python

Pro tips: Writing lean Python code

Python is one of the most important programming languages, especially for data scientists.

Sometimes I find myself going through hundreds of lines of code for my projects. So I spent some hours researching on how to trim the massive code and make the overall coding leaner. Here are 5 tricks I learned.

1. Lean conditional statements

Conditional statements can be really clumsy:

if a == 0:
print("0")
else:
print("not 0")

But this can cost several lines of code. There’s a more lean way to write conditional statements:

print("0") if a ==0 else print("not 0")

2. Simple String-cutting

I work a lot with time-series data. Some of them are Unix timestamps, which look like this:

date = "1553197926UTC"

Converting the number itself into a date would not be a problem, but the remainder of the timestamp–the ‚UTC ‚ part–needs to be removed before we can do anything with the timestamp. Python offers a straightforward way to get rid of some parts of strings (here the trailing three characters):

date = "1553197926UTC"
date = date[:-3]
>>> 1553197926

3. Convert a Nested Array into One Array

Sometimes we get a nested array, especially when dealing with JSON responses from APIs:

array = [[1, 2], [3, 4], [5, 6]]

If we want to transform the nested array into one array, here’s a little trick that does it:

import itertools
list(itertools.chain.from_iterable(array))
>>> [1, 2, 3, 4, 5, 6]

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