Ruhong seahrh

Oh my zsh.

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

A guide to setup your WSL with Hyper and zsh

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):

	from tensorflow import keras
	from tensorflow.python.lib.io import file_io


	class ModelCheckpointInGcs(keras.callbacks.ModelCheckpoint):
	def __init__(
	self,
	filepath,
	gcs_dir: str,
	monitor="val_loss",

	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:

	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

	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]

	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()

	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

	#!/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