Skip to content

Instantly share code, notes, and snippets.

View msure's full-sized avatar

Adrian Palacios msure

5 followers · 0 following
View GitHub Profile
@msukmanowsky
msukmanowsky / lookml_vs_materialized_views.md
Last active December 12, 2019 18:15

LookML vs Materialized Views

Say we're working with clickstream data:

CREATE TABLE pageviews (
  "timestamp"   timestamp,
  url           text,
  referrer      text,
 user_agent text,
@seanjtaylor
seanjtaylor / Optimal Launch Criterion.ipynb
Created September 6, 2019 06:02
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@halhen
halhen / joyplot-atus.R
Last active July 17, 2018 13:20
The daily grind - viz
library(tidyverse)
# data from https://www.kaggle.com/bls/american-time-use-survey
df.resp <- read_csv('../data/atus/atusresp.csv')
df.act <- read_csv('../data/atus/atusact.csv', col_types=cols(tustarttim = col_character(), tustoptime = col_character()))
df.sum <- read_csv('../data/atus/atussum.csv')
df.tmp <- df.act %>%
mutate(activity = case_when(trtier2p == 1301 ~ 'Exercise',
@wrobstory
wrobstory / postgres_to_redshift.csv
Created August 25, 2016 20:10
Postgres --> Redshift types via http://docs.aws.amazon.com/dms/latest/userguide/CHAP_Reference.Target.PostgreSQL.DataTypes.html
PostgreSQL Data Types AWS DMS Data Types Redshift Data Types
INTEGER INT4 INT4
SMALLINT INT2 INT2
BIGINT INT8 INT8
NUMERIC (p,s) If precision is 39 or greater, then use STRING. If the scale is => 0 and =< 37 then: NUMERIC (p,s) If the scale is => 38 and =< 127 then: VARCHAR (Length)
DECIMAL(P,S) If precision is 39 or greater, then use STRING. If the scale is => 0 and =< 37 then: NUMERIC (p,s) If the scale is => 38 and =< 127 then: VARCHAR (Length)
REAL REAL4 FLOAT4
DOUBLE REAL8 FLOAT8
SMALLSERIAL INT2 INT2
SERIAL INT4 INT4
@garybernhardt
garybernhardt / types.markdown
Last active May 22, 2024 10:02

This document has moved!

It's now here, in The Programmer's Compendium. The content is the same as before, but being part of the compendium means that it's actively maintained.

@TomAugspurger
TomAugspurger / Timeseries.ipynb
Created May 14, 2016 01:33
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@TomAugspurger
TomAugspurger / Visualization.ipynb
Created April 30, 2016 15:09
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@tdhopper
tdhopper / Concatenate Dataframes with Categoricals.ipynb
Created April 20, 2016 21:33
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@arfon
arfon / big_query_examples.md
Last active September 19, 2022 13:00
BigQuery Examples for blog post

How many times shouldn't it happen...

-- https://news.ycombinator.com/item?id=11396045

SELECT count(*)
FROM (SELECT id, repo_name, path
        FROM [bigquery-public-data:github_repos.sample_files]
 ) AS F
@fredbenenson
fredbenenson / kickstarter_sql_style_guide.md
Last active June 24, 2024 03:28
Kickstarter SQL Style Guide
layout title description tags
default
SQL Style Guide
A guide to writing clean, clear, and consistent SQL.
data
process

Purpose