Data types are one of those things that you don’t tend to care about until you get an error or some unexpected results. It is also one of the first things you should check once you load a new data into pandas for further analysis.
In this short tutorial, Chris shows how to the pandasdtypes map to the numpy and base Python data types.
Moreover, Chris demonstrates how to handle and convert data types so you can speed up your data analysis. Both using custom functions and anonymous lambda functions.
A very handy guide indeed, after which you will be able to read in your datasets into Python in the right format from the get-go!
How do scurvy, astronomy, alchemy and data science relate to each other?
In this goto conference presentation, Lucas Vermeer — Director of Experimentation at Booking.com — uses some amazing storytelling to demonstrate how the value of data (science) is largely by organizations capability to gather the right data — the data they actually need.
It’s a definite recommendation to watch for data scientists and data science leaders out there.
Here are the slides, and they contain some great oneliners:
Suppose you operate a warehouse where workers work 11-hour shifts. In order to meet your productivity KPIs, a significant number of them need to take painkillers multiple times per shift. Do you…
Decrease or change the KPI (goals)
Make shifts shorter
Increase the number or duration of breaks
Increase the medical staff
Install vending machines to dispense painkillers more efficiently
Nobody in their right mind would take option 5… Right?
Yet, this is precisely what Amazon did according to Emily Guendelsberger in her insanely interesting and relevant book “On the clock” (note the paradoxal link to Amazon’s webshop here).
Emily went undercover as employee at several organizations to experience blue collar jobs first-hand. In her book, she discusses how tech and data have changed low-wage jobs in ways that are simply dehumanizing.
These days, with sensors, timers, and smart nudging, employees are constantly being monitored and continue working (hard), sometimes at the cost of their own health and well-being.
I really enjoyed the book, despite the harsh picture it sketches of low wage jobs and malicious working conditions these days. The book poses several dilemma’s and asks multiple reflective questions that made me re-evaluate and re-appreciate my own job. Truly an interesting read!
Some quotes from the book to get you excited:
“As more and more skill is stripped out of a job, the cost of turnover falls; eventually, training an ever-churning influx of new unskilled workers becomes less expensive than incentivizing people to stay by improving the experience of work or paying more.”
Emily Guendelsberger, On the Clock
“Q: Your customer-service representatives handle roughly sixty calls in an eighty-hour shift, with a half-hour lunch and two fifteen-minute breaks. By the end of the day, a problematic number of them are so exhausted by these interactions that their ability to focus, read basic conversational cues, and maintain a peppy demeanor is negatively affected. Do you:
A. Increase staffing so you can scale back the number of calls each rep takes per shift — clearly, workers are at their cognitive limits
B. Allow workers to take a few minutes to decompress after difficult calls
C. Increase the number or duration of breaks
D. Decrease the number of objectives workers have for each call so they aren’t as mentally and emotionally taxing
E. Install a program that badgers workers with corrective pop-ups telling them that they sound tired.
Seriously—what kind of fucking sociopath goes with E?”