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9 1 0 0 0 10.546
11 0 0 0 0 34.943
13 0 0 0 1 2.834
15 0 0 0 1 17.532
33 1 0 0 0 1.418
36 0 0 0 0 48.033
43 2 0 0 0 16.706
47 0 0 0 0 24.999
50 0 0 0 0 24.999
56 0 1 0 0 3.869

mcohen01

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",

mcohen01

        1        189          0        189          0          0              1         1         1   1              1         0       100        169         39         34  

        2        287          0        287          0          0              1         1         2   2              1         0        90      149.5         15         34  

        3        242          0        242          0          1              2         0         1   1              1         1       100       23.5          9         20  

        4        199          0        199          0          0              1         1         1   1              1         0        90         46         53         48  

        5        286          0        286          0          1              2         0         1   1              3         0        90         10         12         46  

mcohen01

import re
import PyPDF2
from collections import defaultdict
import matplotlib.pyplot as plt
import warnings
import seaborn as sns

sns.set()

warnings.filterwarnings('ignore')

mcohen01

---

title: CS 519 Exercise 1 author: Michael Cohen date: 4/14/2018

fontsize: 12pt margin-left: 60pt margin-right: 60pt margin-bottom: 30pt margin-top: 20pt

mcohen01

from collections import Counter, defaultdict
from pandas import DataFrame, Series
import json
import seaborn
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FuncFormatter, MaxNLocator
from sklearn.linear_model import LinearRegression

from sklearn.preprocessing import PolynomialFeatures

mcohen01

library(ggplot2)

observations <- 5
mu = 10
trials <- 100

confidence.interval <- function(threshold = .975, variance = 4) {
  x <- rnorm(observations, mean = mu, sd = sqrt(variance))
  df <- length(x) - 1
  SE <- sd(x) / sqrt(length(x))

mcohen01

import websocket # pip install websocket_client
import _thread
import json

def main():
    def on_open(ws):
        def run(*args):
            msg = {
                'type': 'subscribe',
                'product_ids': ['ETH-USD']

mcohen01

import hmac, hashlib, locale, math, time, requests, base64
from requests.auth import AuthBase


class CoinbaseExchangeAuth(AuthBase):
    def __init__(self, api_key, secret_key, passphrase):
        self.api_key = api_key
        self.secret_key = secret_key
        self.passphrase = passphrase

mcohen01

library(dplyr)
library(readr)
library(reshape2)
library(stringr)
library(ggplot2)
library(pdftools)

setwd('/Users/mcohen/Downloads/Scratch/codeplay/R/motogp/lap_times')