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Reading In, Reordering, Merging Data, Changing Shapes of Data Statistical Computing

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Reading in, Reordering, Merging Data, Changing shapes of data Statistical Computing Last week: Simulation • Running simulations is an integral part of being a statistician in the 21st century • R provides us with a utility functions for simulations from a wide variety of distributions • To make your simulation results reproducible, you must set the seed, using set.seed() • There is a natural connection between iteration, functions, and simulations • Saving and loading results can be done in two formats: rds and rdata formats Part I Reading in and reordering data Reading in data from the outside All along, we’ve already been reading in data from the outside, using: • readLines(): reading in lines of text from a file or webpage; returns vector of strings • read.table(): read in a data table from a file or webpage; returns data frame • read.csv(): like the above; returns data frame This week we’ll focus on read.table(), read.csv() and their counterparts write.table(), write.csv(), respectively Reading in data from a previous R session Reminder that we’ve seen two ways to read/write in data in specialized R formats: • readRDS(), saveRDS(): functions for reading/writing single R objects from/to a file • load(), save(): functions for reading/writing any number of R objects from/to a file Advantage: these can be a lot more memory efficient than what we’ll cover this week. Disadvantage: they’re limited in scope in the sense that they can only communicate with R read.table(), read.csv() Have a table full of data, just not in the R file format? Then read.table() is the function for you. It works as in: • read.table(file=file.name, sep=" "), to read data from a local file on your computer called file.name, assuming (say) space separated data • read.table(file=webpage.link, sep="\t"), to read data from a webpage up at webpage.link, assuming (say) tab separated data 1 The function read.csv() is just a shortcut for using read.table() with sep=",". Both read.csv() and read.table() can read in .csv file. (But note: these two actually differ on some of the default inputs!) Examples of reading in data # This data table is comma separated, so we can use read.csv() strike.df = read.csv("http://www.stat.cmu.edu/~ryantibs/statcomp/data/strikes.csv") head(strike.df) ## country year strike.volume unemployment inflation left.parliament ## 1 Australia 1951 296 1.3 19.8 43.0 ## 2 Australia 1952 397 2.2 17.2 43.0 ## 3 Australia 1953 360 2.5 4.3 43.0 ## 4 Australia 1954 3 1.7 0.7 47.0 ## 5 Australia 1955 326 1.4 2.0 38.5 ## 6 Australia 1956 352 1.8 6.3 38.5 ## centralization density ## 1 0.3748588 NA ## 2 0.3751829 NA ## 3 0.3745076 NA ## 4 0.3710170 NA ## 5 0.3752675 NA ## 6 0.3716072 NA sapply(strike.df, class) ## country year strike.volume unemployment ## "factor" "integer" "integer" "numeric" ## inflation left.parliament centralization density ## "numeric" "numeric" "numeric" "numeric" # This data table is tab separated, so let's specify sep="\t" anss.df = read.table( file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/anss.dat", sep="\t") head(anss.df) ## V1 V2 V3 V4 V5 V6 ## 1 Date Time Lat Lon Depth Mag ## 2 2002/01/01 10:39:06.82 -55.2140 -129.0000 10.00 6.00 ## 3 2002/01/01 11:29:22.73 6.3030 125.6500 138.10 6.30 ## 4 2002/01/02 14:50:33.49 -17.9830 178.7440 665.80 6.20 ## 5 2002/01/02 17:22:48.76 -17.6000 167.8560 21.00 7.20 ## 6 2002/01/03 07:05:27.67 36.0880 70.6870 129.30 6.20 sapply(anss.df, class) ## V1 V2 V3 V4 V5 V6 ## "factor" "factor" "factor" "factor" "factor" "factor" # Oops! It comes with column names, so let's set header=TRUE anss.df = read.table( 2 file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/anss.dat", sep="\t", header=TRUE) head(anss.df) ## Date Time Lat Lon Depth Mag ## 1 2002/01/01 10:39:06.82 -55.214 -129.000 10.0 6.0 ## 2 2002/01/01 11:29:22.73 6.303 125.650 138.1 6.3 ## 3 2002/01/02 14:50:33.49 -17.983 178.744 665.8 6.2 ## 4 2002/01/02 17:22:48.76 -17.600 167.856 21.0 7.2 ## 5 2002/01/03 07:05:27.67 36.088 70.687 129.3 6.2 ## 6 2002/01/03 10:17:36.30 -17.664 168.004 10.0 6.6 sapply(anss.df, class) ## Date Time Lat Lon Depth Mag ## "factor" "factor" "numeric" "numeric" "numeric" "numeric" Helpful input arguments The following inputs apply to either read.table() or read.csv() (though these two functions actually have different default inputs in general—e.g., header defaults to TRUE in read.table() but FALSE in read.csv()) • header: boolean, TRUE is the first line should be interpreted as column names • sep: string, specifies what separates the entries; empty string “” is interpreted to mean any white space • quote: string, specifies what set of characters signify the beginning and end of quotes; empty string “” disables quotes altogether Other helpful inputs: skip, row.names, col.names. You can read about them in the help file for read.table() Another example of reading in data # This data table is tab separated, and it comes with column names sprint.m.df = read.table( file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/sprint.m.dat", sep="\t", header=TRUE) ## Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 981 did not have 8 elements # Oops! It turns out it has some apostrophe marks in the City column, # so we have to set quote="" sprint.m.df = read.table( file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/sprint.m.dat", sep="\t", header=TRUE, quote="") head(sprint.m.df) ## Rank Time Wind Name Country Birthdate City Date ## 1 1 9.58 0.9 Usain Bolt JAM 21.08.86 Berlin 16.08.2009 ## 2 2 9.63 1.5 Usain Bolt JAM 21.08.86 London 05.08.2012 ## 3 3 9.69 0.0 Usain Bolt JAM 21.08.86 Beijing 16.08.2008 ## 4 3 9.69 2.0 Tyson Gay USA 09.08.82 Shanghai 20.09.2009 ## 5 3 9.69 -0.1 Yohan Blake JAM 26.12.89 Lausanne 23.08.2012 3 ## 6 6 9.71 0.9 Tyson Gay USA 09.08.82 Berlin 16.08.2009 unique(grep("'", sprint.m.df$City, value=TRUE)) # This is the troublemaker ## [1] "Villeneuve d'Ascq" write.table(), write.csv() To write a data frame (or matrix) to a text file, use write.table() or write.csv(). These are the counterparts to read.table() and read.csv(), and they work as in: • write.table(my.df, file="my.df.txt", sep=" ", quote=FALSE), to write my.dat to the text file “my.df.txt” (to be created in your working directory), with (say) space separation, and no quotes around the entries • write.csv(my.df, file="my.df.csv", quote=FALSE), to write my.dat to the text file “my.df.csv” (to be created in your working directory), with comma separation, and no quotes Note that quote=FALSE, signifying that no quotes should be put around the printed data entries, seems always preferable (default is quote=TRUE). Also, setting row.names=FALSE and col.names=FALSE will disable the printing of row and column names (defaults are row.names=TRUE and col.names=TRUE) read_excel • Use library(readxl) • data <-read_excel("filename.xlsx"); variables names are inputed as default. Reordering data Sometimes it’s convenient to reorder our data, say the rows of our data frame (or matrix). Recall: • The function order() takes in a vector, and returns the vector of indices that put this vector in increasing order • Set the input decreasing=TRUE in order() to get decreasing order • We can apply compute an appropriate vector of indices, and then use this on rows of our data frame to reorder all of the columns simultaneously Examples of reordering # The sprint data has its rows ordered by the fastest 100m time to the slowest. # Suppose we wanted to reorder, from slowest to fastest i.slow = order(sprint.m.df$Time, decreasing=TRUE) # By decreasing sprint time sprint.m.df.slow = sprint.m.df[i.slow,] # Reorder rows by decreasing sprint time head(sprint.m.df.slow) ## Rank Time Wind Name Country Birthdate City ## 2682 2691 10.09 1.8 Mel Lattany USA 10.08.59 Colorado Springs ## 2683 2691 10.09 -0.9 Mel Lattany USA 10.08.59 Z&uuml;rich ## 2684 2691 10.09 1.3 Carl Lewis USA 01.07.61 Walnut ## 2685 2691 10.09 0.6 Calvin Smith USA 08.01.61 Athens ## 2686 2691 10.09 -1.7 Carl Lewis USA 01.07.61 Indianapolis 4 ## 2687 2691 10.09 -0.9 Calvin Smith USA 08.01.61 Z&uuml;rich ## Date ## 2682 30.07.1978 ## 2683 19.08.1981 ## 2684 25.04.1982 ## 2685 14.05.1982 ## 2686 02.07.1982 ## 2687 18.08.1982 # Suppose we wanted to reorder the rows by sprinter name, alphabetically i.name = order(sprint.m.df$Name) # By sprinter name sprint.m.df.name = sprint.m.df[i.name,] # Reorder rows by name head(sprint.m.df.name) ## Rank Time Wind Name Country Birthdate City ## 1373 1281 10.03 0.5 Aaron Armstrong TTO 14.10.77 Port of Spain ## 1552 1456 10.04 1.0 Aaron Armstrong TTO 14.10.77 Port of Spain ## 2326 2145 10.07 1.0 Aaron Armstrong TTO 14.10.77 Port of Spain ## 568 491 9.96 2.0 Aaron Brown CAN 27.05.92 Montverde ## 1114 1011 10.01 1.8 Aaron Brown CAN 27.05.92 Montverde ## 1836 1683 10.05 1.9 Aaron Brown CAN 27.05.92 Eugene ## Date ## 1373 20.06.2009 ## 1552 25.06.2005 ## 2326 13.08.2011 ## 568 11.06.2016 ## 1114 11.06.2016 ## 1836 05.06.2013 Part II Merging data Merging data frames Suppose you have two data frames X, Y, and you want to combine them • Simplest case: the data frames have exactly the same number of rows, that the rows represent exactly the same units, and you want all columns from both; just use, data.frame(X,Y) • Next best case: you know that the two data frames have the same rows, but you only want certain columns from each; just use, e.g., data.frame(X$col1,X$col5,Y$col3) • Next best case: same number of rows but in different order; put one of them in same order as the other, with order().
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    High Commission of the Republic of Trinidad and Tobago B 3 / 26, Vasant Vihar New Delhi - 110057, India Tel No: +91 11 46007500 Fax No: +91 11 46007505 Website: www.hc4.net Email: [email protected] Printed by India Empire Publications: +91.9899117477 Design and Layout: H.E. Chandradath Singh Contents President’s message Prime Minister’s message Indian Prime Minister’s speech at CHOGM High Commissioner’s message Presenta3on of creden3als Prime Minister’s speech at PBD 2012 Photographic coverage of Prime Minister’s Visit Media coverage of PM’s Visit Indian Prime Minister’s visit to TnT Cricket reflec3ons by Ravi Chaturvedi Mission cricket and West Indies team in India Famous Trinidad and Tobago cricketers 50 years of Hindi movies The Olympic Dream Indian Arrival Day Emancipa3on Day Eco Tourism TRINIDAD AND TOBAGO : IDEALLY LOCATED Leading world exporter of menthol, ammonia and LNG... ...World’s best tourist destination 2012 4 TRINIDAD AND TOBAGO | 50 YEARS OF INDEPENDENCE PRESIDENT’S MESSAGE Message from the President of the Republic of Trinidad and Tobago His Excellency Professor George Maxwell Richards President t is with great pleasure that I bring greet - The strong bonds between us and the estab - ings on the occasion of the dual celebra - lishment of High Commissions in our respec - tion of the 50th anniversary of Trinidad tive countries have resulted in fruitful and Tobago’s Independence as well as fifty relationships which facilitate cooperation in en - years of diplomatic relations with the Republic ergy exploration, trade, technical training, aca - Iof India. demic pursuits and cultural exchanges, inter alia.
  • 2014 Commonwealth Games Statistics – Men's 100M (100Y

    2014 Commonwealth Games Statistics – Men's 100M (100Y

    2014 Commonwealth Games Statistics – Men’s 100m (100y before 1970) by K Ken Nakamura All time performance list at the Commonwealth Games Performance Performer Time Wind Name Nat Pos Venue Year 1 1 9.88 -0.1 Ato Boldon TRI 1 Kuala Lumpur 1998 2 2 9.91 1.9 Linford Christie ENG 1 Victoria 1994 3 9.96 0.0 Ato Boldon 1sf1 Kuala Lumpur 1998 3 3 9.96 -0.1 Frankie Fredericks NAM 2 Kuala Lumpur 1998 5 9.98 1.8 Linford Christie 1sf1 Victoria 1994 5 9.98 0.0 Frankie Fredericks 2sf1 Kuala Lumpur 1998 6 4 9.98 0.2 Kim Collins SKN 1 Manchester 2002 8 5 10.00 -0.1 Obadele Thompson BAR 3 Kuala Lumpur 1998 9 10.02 1.3 Linford Christie 1sf2 Auckland 1990 9 10.02 0.2 Linford Christie 1qf1 Victoria 1994 11 6 10.03 -0.1 Matt Shirvington AUS 4 Kuala Lumpur 1998 11 6 10.03 0.2 Asafa Powell JAM 1sf2 Melbourne 2006 11 10.03 0.9 Asafa Powell 1 Melbourne 2006 14 10.04 1.8 Frankie Fredericks 1qf3 Victoria 1994 15 8 10.05 1.8 Olapade Adenikin NGR 2sf1 Victoria 1994 15 8 10.05 1.9 Michael Green JAM 2 Victoria 1994 15 10.05 -0.5 Ato Boldon 1qf4 Kuala Lumpur 1998 18 10.06 1.9 Frankie Fredericks 3 Victoria 1994 18 10 10.06 0.8 Dwain Chambers ENG 1sf2 Manchester 2002 20 11 10.07 1.6 Ben Johnson CAN 1 Edinburgh 1986 20 10.07 1.9 Ato Boldon 4 Victoria 1994 22 10.08 -0.5 Obadele Thompson 1sf2 Kuala Lumpur 1998 22 12 10.08 -0.1 Darren Campbell ENG 5 Kuala Lumpur 1998 22 10.08 0.2 Kim Collins 1sf1 Manchester 2002 25 10.09 0.2 Obadele Thompson 1qf3 Kuala Lumpur 1998 26 13 10.10 1.5 Glenroy Gilbert CAN 1h8 Victoria 1994 26 13 10.10 1.8 Horace Dove-Edwin NZL 3sf1 Vitoria 1994
  • Master Schedule.Xlsx

    Master Schedule.Xlsx

    Date Baton Rouge Berlin Morning Time Time Sex Event Round Saturday 8/15 3:05 AM 10:05 M Shot PutQualification Saturday 8/15 3:10 AM 10:10 W 100 Metres Hurdles Heptathlon Saturday 8/15 3:50 AM 10:50 W 3000 Metres Steeplechase Heats Saturday 8/15 4:00 AM 11:00 W Triple Jump Qualification Saturday 8/15 4:20 AM 11:20 W High Jump Heptathlon Saturday 8/15 4:40 AM 11:40 M 100 Metres Heats SaturdaSaturdayy 88/15/15 55:00:00 AM 12:00M Hammer Throw QQualificationualification Saturday 8/15 5:50 AM 12:50 W 400 Metres Heats Saturday 8/15 6:00 AM 13:00 M 20 Kilometres Race Walk Final Saturday 8/15 6:20 AM 13:20 M Hammer ThrowQualification Afternoon session Saturday 8/15 11:15 AM 18:15 M 1500 Metres Heats Saturday 8/15 11:20 AM 18:20 W Shot Put Heptathlon Saturday 8/15 11:50 AM 18:50 M 100 Metres Quarter-Final Saturday 8/15 12:00 PM 19:00 W Pole Vault Qualification Saturday 8/15 12:25 PM 19:25 W 10,000 Metres Final Saturday 8/15 1:15 PM 20:15 M Shot Put Final Saturday 8/15 1:20 PM 20:20 M 400 Metres Hurdles Heats Saturday 8/15 2:10 PM 21:10 W 200 Metres Heptathlon Date Baton Rouge Berlin Date Time Time Morning session Sex Event Round Sunday 8/16 3:05 AM 10:05 W Shot PutQualification Sunday 8/16 3:10 AM 10:10 W 800 Metres Heats Sunday 8/16 3:45 AM 10:45 W Javelin Throw Qualification Sunday 8/16 4:00 AM 11:00 M 3000 Metres Steeplechase Heats Sunday 8/16 4:35 AM 11:35 W Long Jump Heptathlon SundaSundayy 88/16/16 44:55:55 AM 11:11:5555 W 100 Metres Heats Sunday 8/16 5:00 AM 12:00 W 20 Kilometres Race Walk Final Sunday 8/16 5:15 AM 12:15 W Javelin Throw