M. Farrajota farrajota

Missing values in data

Types of missing values

Missing completely at random (MCAR)

MCAR exists when missing values are randomly distributed across all observations. Missingness in given variable does not depend on any other variable, whether observed or unobserved. MCAR can be confirmed by dividing respondents into those with and without missing data, then using t-tests of mean differences on income, age, gender, and other key variables to establish that the two groups do not

I've been working with Apache Kafka for over 7 years. I inevitably find myself doing the same set of activities while I'm developing or working with someone else's system. Here's a set of Kafka productivity hacks for doing a few things way faster than you're probably doing them now. 🔥

Show me all my Kafka topics and their partitions, replicas, and consumers
Show me the contents of a topic
Create a Kafka topic
Produce messages to a Kafka topic
Validate the schema of messages before producing to a topic
Do all of this at a distance

Get the tools

Here I've put the most important data structures I could find with the most efficient implementations in Python I am aware of. Although this is a continuous process and many structures do not have any implementation reference available yet, if you happen to know a more efficient algorithm to implement one or more of this structures in Python (or any language) feel free to ping me :).

Basic Data Structures

Data Structure	Python
Arrays	numpy Tensorflow PyTorch

	"""
	Using dask's multithreaded scheduler to speedup download of multiple files from
	an s3 bucket
	"""

	import os
	from functools import partial

	import botocore
	import boto3