pre-print - Hadley Wickham's

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ggplot(data, aes(x = var1, y = var2, colour = var3) + Saturday, July 23, 2011 geom_point() + geom_smooth() Visualise
subset mutate arrange summarise * by operator (ddply) + join match_df Saturday, July 23, 2011 Transform
Page 1 and 2: June 2011 Saturday, July 23, 2011 E
Page 3 and 4: Data analysis Data analysis is the
Page 5 and 6: Saturday, July 23, 2011
Page 7 and 8: Access Saturday, July 23, 2011 Unde
Page 9 and 10: Understand Visualise Access Transfo
Page 11 and 12: Understand Visualise Questions Tran
Page 13 and 14: Reproducibility http://www.flickr.c
Page 15 and 16: # Load data and create smaller subs
Page 17 and 18: Saturday, July 23, 2011 Learning cu
Page 19 and 20: SEXP applyClosure(SEXP call, SEXP o
Page 21 and 22: http://www.flickr.com/photos/meantu
Page 23 and 24: http://www.flickr.com/photos/wwwork
Page 25 and 26: http://www.flickr.com/photos/billy6
Page 27 and 28: Saturday, July 23, 2011 Domain spec
Page 29 and 30: Saturday, July 23, 2011 “If any n
Page 31: y ~ x y ~ x1 + x2 y ~ x1 * x2 y ~ x
Page 35 and 36: Saturday, July 23, 2011 Motivation
Page 37 and 38: disease Assault (homicide) by other
Page 39 and 40: library(ggplot2) library(plyr) load
Page 41 and 42: Saturday, July 23, 2011 Time of dea
Page 43 and 44: deaths$hod[deaths$hod == 99]
Page 45 and 46: # Compute deaths by hour by cause,
Page 47 and 48: Saturday, July 23, 2011 dist 0.005
Page 49 and 50: devi$resid
Page 51 and 52: Saturday, July 23, 2011 Challenge
Page 53 and 54: First need location: Saturday, July
Page 55 and 56: Only locations with >100 deaths Sat
Page 57 and 58: Saturday, July 23, 2011 Hours of pa
Page 61 and 62: 35 30 25 20 15 ● ● Saturday, Ju
Page 63 and 64: Saturday, July 23, 2011 ...
Page 65 and 66: temp_max freq 250 300 350 ● ●
Page 67 and 68: 0.008 0.006 0.004 0.008 0.006 0.004
Page 69 and 70: Saturday, July 23, 2011 Conclusions

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