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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): |
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-- 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) |
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mtcars$am.f <- as.factor(mtcars$am); levels(mtcars$am.f) <- c("Automatic", "Manual") | |
mtcars$cyl.f <- as.factor(mtcars$cyl); levels(mtcars$cyl.f) <- c("4 cyl", "6 cyl", "8 cyl") | |
mtcars$vs.f <- as.factor(mtcars$vs); levels(mtcars$vs.f) <- c("V engine", "Straight engine") | |
mtcars$gear.f <- as.factor(mtcars$gear); levels(mtcars$gear.f) <- c("3 gears", "4 gears", "5 gears") | |
mtcars$carb.f <- as.factor(mtcars$carb) |
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library(ggplot2); library(gridExtra) | |
g1 <- ggplot(data=mtcars, aes(x=wt, y=mpg)) + | |
geom_point(alpha = 0.7, colour = "#0971B2") + | |
ylab("Miles per gallon") + | |
ylim(10, 35) + | |
xlab("Weight (`000 lbs)") + | |
ggtitle("Untransformed Weight") + | |
geom_vline(xintercept = 0) + | |
theme_bw() |
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av_peds_2 <- ddply(p.subset, c("date", "collapsed_sensors_2"), summarise, | |
n_peds = sum(Hourly_Counts)) | |
# Extract weekday versus weekend | |
av_peds_2$day <- weekdays(av_peds_2$date, abbreviate = FALSE) | |
av_peds_2$weekend <- ifelse((av_peds_2$day == "Saturday" | av_peds_2$day == "Sunday"), | |
"Weekend", "Weekday") | |
av_peds_2$weekend <- as.factor(av_peds_2$weekend) | |
# Extract time of day |
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# Load required packages | |
require(ggplot2); require(gridExtra) | |
# Set the colours for the graphs | |
barfill <- "#4271AE" | |
barlines <- "#1F3552" | |
line1 <- "black" | |
line2 <- "#FF3721" | |
# Plotting histogram of sample 1 |
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use http://www.ats.ucla.edu/stat/stata/library/depress, clear | |
reshape long dep, i(subj) | |
rename _j time | |
drop pre |
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# Generate the 95% confidence interval. | |
lci <- -1 * qt(c(.975), 78) | |
uci <- qt(c(.975), 78) |