hernamesbarbara

#db/seeds.rb

# Run 'rake db:seed' from terminal to create an Admin User in your database
    
    #Seed DB with at least 1 Admin User
    admin=User.new({ name: "Admin User", email: 'admin@rubyonrails.com',
               password: 'password', password_confirmation: 'password'})
    
    admin.toggle!(:admin)

hernamesbarbara

#ack is a tool like grep, designed for programmers with large trees of heterogeneous source code

#to install ack, see http://betterthangrep.com/
#to use ack, launch terminal (mac osx) and type 'ack <some_keywords>'
#ack will search all files in the current directory & sub-directories

#here's how I have my config file setup. this file is located on mac osx here
# ~/.ackrc 

# Always sort the files

hernamesbarbara

#!/bin/bash
export TERM=xterm-color
export CLICOLOR=1
export GREP_OPTIONS='--color=auto'
# export LSCOLORS=Exfxcxdxbxegedabagacad
export LSCOLORS=gxfxcxdxbxegedabagacad # Dark lscolor scheme
# Don't put duplicate lines in your bash history
export HISTCONTROL=ignoredups
# increase history limit (100KB or 5K entries)
export HISTFILESIZE=100000

hernamesbarbara

#!/bin/bash

set completion-ignore-case on

#use up arrow to search history backwards
"\e[A": history-search-backward
"\e[B": history-search-forward
$if Bash
  Space: magic-space
$endif

hernamesbarbara

library(RPostgreSQL)                          #import the library
driver <- dbDriver('PostgreSQL')              #define the database driver
db <- dbConnect(driver, host='foobar_host',   #set the host to the postgreSQL IP or alias
                user='foo_bar',               #input username
                password='my_secret_code',    #input your password
                dbname='my_gp_db')            #input the name of the databse



myquery <- "SELECT 

hernamesbarbara

#extract words in parens from a string
value.match(/(.+)\((.*)\)(.+)/)[1].split(' ')[1]

#replace the following characters with empty string:  , .  - ( )
toUppercase(value).replace(/\,|\.|\-|\(|\)|\[|\]/, '')

hernamesbarbara

#/usr/bin/env python

# Handling NA values in pandas

import pandas as pd

# replace all NA values with your own missing value
my_data_frame['my_column'].fillna('MY_MISSING_VAL')

# return a subset of your dataframe

hernamesbarbara

import numpy as np
import pandas as pd

# look at free reports
free = df[df.report_name.isin(free)]

# look at paid reports only
paid = df[df.report_name.apply(lambda x: x not in free)]

hernamesbarbara

from yhat import Yhat, BaseModel
from sklearn import datasets
from sklearn.svm import SVC

class IrisModel(yhat.BaseModel):
    def transform(self, data):
        data = [
        data['SepalLength'],
        data['SepalWidth'] / 2.0,
        data['PetalLength'],

hernamesbarbara

pip install yhat