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//Based on http://www.samliew.com/icval/
function validateNRIC(str) {
    if (str.length != 9) 
        return false;

    str = str.toUpperCase();

    var i, 
        icArray = [];
    for(i = 0; i < 9; i++) {

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orders (3.4m rows, 206k users):

• order_id: order identifier
• user_id: customer identifier
• eval_set: which evaluation set this order belongs in (see SET described below)
• order_number: the order sequence number for this user (1 = first, n = nth)
• order_dow: the day of the week the order was placed on
• order_hour_of_day: the hour of the day the order was placed on
• days_since_prior: days since the last order, capped at 30 (with NAs for order_number = 1)

products (50k rows):

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#!/bin/python3
import math
import os
import random
import re
import sys
import pandas as pd
from statsmodels.tsa.arima_model import ARIMA
from typing import List

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import os
import random
import numpy as np 
import pandas as pd 
from sklearn.linear_model import Lasso
from sklearn.pipeline import Pipeline
from sklearn.model_selection import cross_val_score, GridSearchCV
from sklearn.preprocessing import RobustScaler
from sklearn.decomposition import PCA
from sklearn import metrics

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import re
from typing import List, Set

filename = ""
out_filename = ""
records: List[str] = []
ts_pattern = re.compile(r"^.+(\d{2}/\w{3}/\d{4}:\d{2}:\d{2}:\d{2})")
seen: Set[str] = set()

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from typing import Iterable, TypeVar

T = TypeVar("T")


def argmin(elements: Iterable[T]) -> int:
    """Returns first index of smallest element."""
    return min(enumerate(elements), key=lambda x: x[1])[0]

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My WSL Setup

A guide to setup your WSL with Hyper and zsh

Download & Install the WSL

• Follow the very thorough instructions here

Get a prettier terminal

• Download Hyper.js here - I went with the 'hyperblue' theme.

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Oh my zsh.

Install with curl

sh -c "$(curl -fsSL https://raw.githubusercontent.com/robbyrussell/oh-my-zsh/master/tools/install.sh)"

Enabling Plugins (zsh-autosuggestions & zsh-syntax-highlighting)

• Download zsh-autosuggestions by

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import pandas as pd
import pandas.io.sql as sqlio
import psycopg2

conn = psycopg2.connect("host='{}' port={} dbname='{}' user={} password={}".format(host, port, dbname, username, pwd))
sql = "select count(*) from table;"
dat = sqlio.read_sql_query(sql, conn)
conn = None

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AWSTemplateFormatVersion: 2010-09-09
Transform: AWS::Serverless-2016-10-31

Parameters:
  BucketPrefix:
    Type: String
    Description: "The prefix used for all S3 buckets."
    AllowedPattern: "[a-z-]+"

Resources: