sajoku

# change prefix to Ctrl-a (like in gnu-screen)

unbind C-b
set-option -g prefix C-a
bind-key C-a send-prefix


# shell
set -g default-command /bin/zsh
set -g default-shell /bin/zsh

ramhiser

import pandas as pd
import numpy as np
from sklearn.feature_extraction import DictVectorizer
 
def encode_onehot(df, cols):
    """
    One-hot encoding is applied to columns specified in a pandas DataFrame.
    
    Modified from: https://gist.github.com/kljensen/5452382
    

brentp

# -*- coding: utf-8 -*-

u"""
Beta regression for modeling rates and proportions.

References
----------
Grün, Bettina, Ioannis Kosmidis, and Achim Zeileis. Extended beta regression
in R: Shaken, stirred, mixed, and partitioned. No. 2011-22. Working Papers in
Economics and Statistics, 2011.

igrigorik

require 'open-uri'
require 'zlib'
require 'yajl'

# References
# - https://developers.google.com/bigquery/preparing-data-for-bigquery#dataformats
# - https://developers.google.com/bigquery/docs/data#nested
#

def type(t)

clarkdave

-- when you have a record which looks like this 
--
--   id: 5,
--   properties: {
--     ages: [20, 30]
--   }
--
-- it is a bit of a pain if you need to query based on the contents of the "ages" array inside the JSON object "properties"
-- because PG currently lacks easy to use operators to work with JSON arrays 

matheusoliveira

CREATE OR REPLACE FUNCTION public.json_append(data json, insert_data json)
RETURNS json
IMMUTABLE
LANGUAGE sql
AS $$
    SELECT ('{'||string_agg(to_json(key)||':'||value, ',')||'}')::json
    FROM (
        SELECT * FROM json_each(data)
        UNION ALL
        SELECT * FROM json_each(insert_data)

yihui

options(warn = -1)
# cannot really suppress warnings from the root level
withCallingHandlers(warning("hi"), warning = function(w) {
    print(w)
})
# the warning can still be captured:

## <simpleWarning in withCallingHandlers(warning("hi"), warning = function(w) {    print(w)}): hi>

# however, this always works

frankrowe

 import shapefile
   # read the shapefile
   reader = shapefile.Reader("my.shp")
   fields = reader.fields[1:]
   field_names = [field[0] for field in fields]
   buffer = []
   for sr in reader.shapeRecords():
       atr = dict(zip(field_names, sr.record))
       geom = sr.shape.__geo_interface__
       buffer.append(dict(type="Feature", \

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD