roycoding

roycoding

# -*- coding: utf-8 -*-

import datetime

from numpy import asarray, ceil
import pandas
import rpy2.robjects as robjects

def stl(data, ns, np=None, nt=None, nl=None, isdeg=0, itdeg=1, ildeg=1,
        nsjump=None, ntjump=None, nljump=None, ni=2, no=0, fulloutput=False):

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4 Core attributes of a data scientist

Roy Keyes

17 Jan 2016 - This is a post on my blog.

Note: I wrote this short post a few years ago and recently found it floating around. It seems more obvious now (and probably trite), but I thought it was still worth posting on the old 'net.

1. Thinking statistically. Things tend to come in distributions. Understanding this make a huge difference in how (data) problems are approached. See #2.
2. Strong grasp of the fundamentals. By having a strong base of math, stats, experimentation, and computer science, the job of the data scientist is much easier. For a specific problem, the fundamentals may not be enough, but they will get you very far.

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A year of working remotely

Roy Keyes

29 Feb 2016 - This is a post on my blog

October 2015 marked my first year of working as a data scientist on a remote team at Zoomer (we help restaurants deliver food, fast). I have always thought that remote work was an obvious choice given the penetration of the internet into all aspects of our lives. In this post I'm going to talk about some of the experiences I've had and lessons learned working on a remote data science team.

Zoomer's main offices are in Philadelphia and San Francisco, but, by the nature of our business, we are a fundamentally distributed company. While I live in San Francisco and work out of the SF office a few days a week, I spend most of the time working from my apartment, collaborating with my team remotely.

Remote data science is not fundamentally different than working on other remote teams, but it has its own set of challenges and difficulties. Done right, remote data s

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Multi-armed banditry in Python with slots

Roy Keyes

22 Aug 2016 - This is a post on my blog.

I recently released slots, a Python library that implements multi-armed bandit strategies. If that sounds like something that won't put you to sleep, then please pip install slots and read on.

Multi-armed bandits

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Keybase proof

I hereby claim:

• I am roycoding on github.
• I am roycoding (https://keybase.io/roycoding) on keybase.
• I have a public key ASCG1vUl8yOBMIxO_ZbxVQMM_o4o82YhmpLQ7lhGZiqtHAo

To claim this, I am signing this object:

roycoding

def sandwich(df, rows=3):
    '''
    Display n rows of head and tail of dataframe.

    Input:
        df - dataframe of interest
        rows - integer number of rows from each end of dataframe to display

    Output:
        dataframe

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