johnwcothran

• Patagonia Lightweight Merino Daily Crew Socks, Feather Grey or Navy Blue, Large
  • J&H might have these
• puzzle
• Sushi Go Party!
• JCrew Flannel Slim Medium [example](https://www.jcrew.com/p/mens_category/shirts/slimshirtshop/slim-m

johnwcothran

ssh-rsa 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 jcothran@edjsports.com

johnwcothran

import R from 'ramda';

function ewa (decay, data, arr=[]) {
  const beta = Math.E**(-1/decay);
  const checkArr = (b) => {
    return arr.length === 0 
    ? R.prop('value', data[1])
    : R.prop('value', arr[R.length(arr)-1]) * b + R.prop('value', data[1]) * (1-b)
  };
  

johnwcothran

import R from 'ramda';
import fetch from 'node-fetch';

const getData = async () => {
  const response = await fetch("https://api.iextrading.com/1.0/stock/aapl/batch?types=quote,news,chart&range=5y&last=1");
  const json = await response.json();
  return json.chart.map(({date, close}) => ({date: new Date(date), value: close}));
};

getData().then(res => console.log(R.head(res)));

johnwcothran

import R from 'ramda';

const sma = (num, data, arr = []) => {
  if (R.length(data) === 0) {
    console.log(`arr: [${arr}] data: [${data}]`);
    return arr;
  } else if (R.length(data) < num) {
    console.log(`arr: [${arr}] data: [${data}]`);
    return sma(num, R.tail(data), R.prepend('not yet!', arr));
  }

johnwcothran

import pandas as pd

# Part 1 functions
def mean(arr):
  return sum(arr) / len(arr)

def isEven (arr):
  return arr % 2 == 0

def half (arr):

johnwcothran

import pandas as pd

def mean(arr):
  return sum(arr) / len(arr)

def isEven (arr):
  return arr % 2 == 0

def half (arr):
  if isEven(len(arr)):

johnwcothran

import pandas as pd
import seaborn as sns

# Part 1 functions
def mean(arr):
  return sum(arr) / len(arr)

def isEven (arr):
  return arr % 2 == 0

johnwcothran

import pandas as pd
import seaborn as sns

weekData = [
  { "name": "John",    "distance": 35.4,   "high-speed-running": 3.65,   "week": 1 },
  { "name": "Mike",    "distance": 32.9,   "high-speed-running": 3.77,   "week": 1 },
  { "name": "Chad",    "distance": 27.2,   "high-speed-running": 3.02,   "week": 1 },
  { "name": "Phil",    "distance": 20.5,   "high-speed-running": 2.01,   "week": 1 },
  { "name": "Tyler",   "distance": 15.3,   "high-speed-running": 2.09,   "week": 1 },
  { "name": "John",    "distance": 38.4,   "high-speed-running": 4.95,   "week": 2 },

johnwcothran

def mean(arr):
  return sum(arr) / len(arr)

# New code:
def isEven (arr):
  return arr % 2 == 0

def half (arr):
  if isEven(len(arr)):
    return int(len(arr)/2) - 1