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require(ggplot2); require(gridExtra)

# Set the colours for the graphs
barfill <- "#4271AE"
barlines <- "#1F3552"
line1 <- "black"
line2 <- "#FF3721"

# Plotting histogram of sample of daily page views
g1 <- ggplot(data=as.data.frame(sample), aes(sample)) + 

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# Defining lambda and n
lambda <- 220
n <- 30

# Calculating SEM
sem <- sqrt(lambda / n)

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set.seed(567)

# Sample of 30 (29 from the Poisson distribution and an outlier of 260)
sample1 <- c(rpois(29, lambda = 220), 260)

# Sample of 10 (9 from the Poisson distribution and an outlier of 260)
sample2 <- c(rpois(9, lambda = 220), 260)

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# Function designed to strip out all numbers (alphabetic - English only - and numeric) from a string as part of a
# text normalisation process.

# Based on the text2num package (https://github.com/ghewgill/text2num) and using code from 
# here (http://stackoverflow.com/questions/25346058/removing-list-of-words-from-a-string)

from string import digits

# List of number terms
nums = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine', 'ten', 'eleven',

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library(ggplot2)

positions = c("Travel and Holidays", "Finances", "Learning and Career", "Mental Wellbeing",
              "Relationships", "Physical Health")

# What are the most popular resolutions?
p1 <- ggplot(twitter_df[twitter_df$Resolution.type != "",], aes(x = Resolution.type, fill = Resolution.type)) +
        geom_bar() +
        coord_flip() +
        ggtitle("Number of tweets by resolution type") +

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package main

import (
	"fmt"
)

type Saiyan struct {
	Name   string
	Power  int
	Father *Saiyan

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import urllib2
import json
import math

import numpy as np
from pandas import Series, DataFrame
import pandas as pd
import matplotlib.pyplot as plt

def expired_listings(site, searchterm):

t-redactyl

-- Create tables
DROP TABLE IF EXISTS ratingsdata;
CREATE TABLE ratingsdata ( 
   userid INT, 
   itemid INT, 
   rating INT, 
   timestamp INT, 
   PRIMARY KEY (userid, itemid)); 

DROP TABLE IF EXISTS movies;

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import lxml.html
from lxml.cssselect import CSSSelector
import requests

def get_title(node):
    '''
    Extracts the movie title from the URL http://www.timeout.com/london/film/the-50-best-christmas-movies
    taking into account that some titles are tagged as h3, and some as h3 a.
    '''
    h3_elem = node.cssselect('div.feature-item__text h3')[0]

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def name_print(cat):
    '''Print the name of the cat.'''
    print "The cat is called %s." % cat.name

name_print(felix)