R Programming
R Programming - Conditions
- Comparison Operators
- equal (==)
- not equal (!=)
- greater or equal to (>=)
- lower or equal to (<=)
- Logical Operators
- the and operator (&)
- the or operator (|)
- the not operator (!)
- if (Stand-Alone) Statement
- else Statement
- ifelse Statement
TRUE & TRUE
TRUE & FALSE
TRUE | FALSE
!TRUE
2 == 3
5 < 6
c(1,4) >= 6
9 != 8
5 < 6 & 9 != 8score <- 80
exam_no <- 2
score >= 75 | exam_no == 1
score>=75 & score<90 | exam_no==1if (Stand-Alone) Statement
The if statement executes a chunk of code if and only if a defined condition is TRUE, which looks something like this:
if(TRUE) message("It was true!")## It was true!if(FALSE) message("It wasn't true!")a <- 3
num <- 4
if ( a <= num ) {
a <- a ^ 2
}
a## [1] 9if (Stand-Alone) Statement
num <- -1
if ( num < 0 ) {
print("num is negative.")
print("Don't worry, I'll fix it.")
num <- num * -1
print("Now num is positive.")
}## [1] "num is negative."
## [1] "Don't worry, I'll fix it."
## [1] "Now num is positive."num## [1] 1if (Stand-Alone) Statement
if (Stand-Alone) Statement
else - Statement
If you want something different to happen when the condition is FALSE, you can add an else declaration.
if(FALSE)
{
message("This won't execute...")
} else
{
message("but this will.")
}## but this will.a <- 3.5
dec <- 0.5
if (dec <= 0.5) {
adec <- dec + 1
} else {
adec <- dec
}
adec## [1] 1.5-else - and -else if- Statement
If your situation has more than two mutually exclusive cases, use else and if statements together.
a <- 1
b <- 1
if (a > b) {
print("A wins!")
} else if (a < b) {
print("B wins!")
} else {
print("Tie.")
}## [1] "Tie."Nesting and Stacking Statements
An if statement can be placed in another if statement. In the editor, modify the mynumber example once more as follows:
Nesting and Stacking Statements
Nesting and Stacking Statements
Nesting and Stacking Statements
Nesting and Stacking Statements
Practice - Conditions - TRUE and FALSE
- Print this if it is TRUE. “This message will print!”
if (...) {
print(...)
} - Go to sleep if it is TRUE, else wake up.
if (...) {
print("Go to sleep!")
} else {
print("Wake up!")
}- The variable message to “I execute this when true!” when the condition is TRUE.
if (...) {
message <- "..."
print(message)
} else {
message <- "I execute this when false!"
print(...)
}Practice - Conditions - Logical Op
Problem : You are a CAR, and you are going on the road, BUT ;
Car_Stop_Light <- 'orange'
Number_of_Pedestrians <- 2Remember rules
if (...) {
print(...);
} else {
print(...);
}Practice - Conditions - Logical Op
ANSWER : You are a CAR, and you are going on the road, BUT ;
Car_Stop_Light <- 'orange'
Number_of_Pedestrians <- 2Remember rules
if (Car_Stop_Light == 'green' & Number_of_Pedestrians ==0) {
print('Go!');
} else {
print('STOP');
}## [1] "STOP"Practice - Conditions - Logical Op
Problem : You want to enjoy, and let’s say the day is;
day <- "Saturday"It is okay, you can fun if it is weekend.
if (...) {
print('Enjoy the weekend!')
} else {
print('Do some work.')
}Practice - Conditions - Logical Op
ANSWER : You want to enjoy, and let’s say the day is;
day <- "Saturday"It is okay, you can fun if it is weekend.
if (day == 'Saturday' | day == 'Sunday') {
print('Enjoy the weekend!')
} else {
print('Do some work.')
}## [1] "Enjoy the weekend!"Practice - Conditions - Logical Op
Problem : You want to go out and your question is “Should I take an umbrella?”
- Check to see, if “weather” is “equal” to “cloudy” and, whether there is a “high_chance_of_rain”.
- If it is both, the code should assign the value of the variable message to be “Take umbrella!”
- Otherwise, the code should assign the value of the variable message to “No need for umbrella!”
- Print the message variable after the conditional statement.
- Based on the condition, what should its value be?
Note : There are two variables in your code, “weather” and “high_chance_of_rain”
Practice - Conditions - Logical Op
# you want to go out and your question is "Should I take an umbrella?"
message <- 'Should I take an umbrella?'
weather <- "cloudy"
high_chance_of_rain <- TRUEPractice - Conditions - Logical Op
# you want to go out and your question is "Should I take an umbrella?"
message <- 'Should I take an umbrella?'
weather <- "cloudy"
high_chance_of_rain <- TRUEif (...) {
message <- 'Take umbrella!'
print(message)
} else {
message <- 'No need for umbrella!'
print(message)
}Practice - Conditions - Logical Op
# you want to go out and your question is "Should I take an umbrella?"
message <- 'Should I take an umbrella?'
weather <- "cloudy"
high_chance_of_rain <- TRUE
if (weather == "cloudy" & high_chance_of_rain == TRUE) {
message <- 'Take umbrella!'
print(message)
} else {
message <- 'No need for umbrella!'
print(message)
}## [1] "Take umbrella!"Practice - R Language
Objectives
Manage Working Directory
Find the Data
Read Data with utils (R utility functions)
Practice - R Language
Manage Working Directory
- getwd() - get working directory
- list.files() # or dir()
getwd()## [1] "/Users/emirtoker/Desktop/Memurluk/Software_Tools_for_Earth_&_Environmental_Science/Software_Tools_R_Github"list.files()## [1] "_site.yml"
## [2] "about.Rmd"
## [3] "additional_course.Rmd"
## [4] "book.Rmd"
## [5] "code.Rmd"
## [6] "data_sources.Rmd"
## [7] "data_structure.Rmd"
## [8] "data.Rmd"
## [9] "datacamp.Rmd"
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## [11] "dc_logo2.png"
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## [15] "docs"
## [16] "index.Rmd"
## [17] "LICENSE"
## [18] "my_r_notebook.Rmd"
## [19] "ncl.Rmd"
## [20] "netcdf.Rmd"
## [21] "new_accounts.Rmd"
## [22] "new_data.csv"
## [23] "Presentation"
## [24] "python.Rmd"
## [25] "r_and_rstudio.Rmd"
## [26] "R_Home_Website"
## [27] "R_Interactive_Samples_with_Shiny_files"
## [28] "R_Interactive_Samples_with_Shiny.html"
## [29] "R_Interactive_Samples_with_Shiny.Rmd"
## [30] "R_Interactive_Training"
## [31] "r_language.Rmd"
## [32] "r_probability.Rmd"
## [33] "r_programming.Rmd"
## [34] "r_statistics.Rmd"
## [35] "README.html"
## [36] "README.md"
## [37] "rsconnect"
## [38] "Software_Tools_for_Earth_and_Environmental_Science_Syllabus_2020_21_Fall.png"
## [39] "Software_Tools_for_Earth_and_Environmental_Science_Syllabus.png"
## [40] "Software_Tools_R_Github.Rproj"
## [41] "syllabus.Rmd"
## [42] "unix_linux.Rmd"Practice - R Language
Manage Working Directory
- setwd() - set working directory
# 1
setwd("/Users/emirtoker/Downloads/")
# 2
getwd()## [1] "/Users/emirtoker/Downloads"list.files()## [1] "_grib2netcdf-webmars-public-svc-green-007-6fe5cac1a363ec1525f54343b6cc9fd8-8LiuI0.nc"
## [2] "-1396197156987262396..xls"
## [3] "-5211097752695221187..xls"
## [4] "-7376906819256400609..xls"
## [5] "-953619339638234986..xls"
## [6] "-969412494327541903..xls"
## [7] "(Cambridge Atmospheric and Space Science Series) Boris A. Kagan - Ocean Atmosphere Interaction and Climate Modeling-Cambridge University Press (2006).pdf"
## [8] "(International Geophysics 101) Benoit Cushman-Roisin and Jean-Marie Beckers (Eds.) - Introduction to Geophysical Fluid Dynamics_ Physical and Numerical Aspects-Academic Press (2011).pdf"
## [9] "(International Geophysics 103) Gerold Siedler, Stephen M. Griffies, John Gould and John A. Church (Eds.) - Ocean Circulation and Climate_ A 21 Century Perspective-Academic Press, Elsevier (2013).pdf"
## [10] "(Introduction to Geophysical 101) Benoit Cushman-Roisin, Jean-Marie Beckers - Introduction to Geophysical Fluid Dynamics_ Physical and Numerical Aspects-Academic Press (2011).pdf"
## [11] "1-s2.0-S0169809511000366-main.pdf"
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## [23] "1-s2.0-S0277379114000298-mmc1.kmz"
## [24] "10113034.pdf"
## [25] "14. Granulit, Eklojit.pptx"
## [26] "16638_F.pdf"
## [27] "19394386126_Akademisyen.pdf"
## [28] "19394386126_Ogrenci.pdf"
## [29] "1963_Book_SevereLocalStorms.pdf"
## [30] "2_AVICENA_-_Authors_statement_for_publication.doc"
## [31] "2015_OCEAN820_Final_engl.pdf"
## [32] "2018_Korotenko_peerj-5448.pdf"
## [33] "2019_eş-danışman-atama-dilekçesi.docx"
## [34] "2019JD031403.pdf"
## [35] "2020JournalImpactFactorandQuartile.pdf"
## [36] "3400534.acsm"
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## [44] "a3_hafta_cizelge_zoom_link_V2.xlsx - Sheet2.pdf"
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## [51] "a4_TURQUA_2020_Programı_V8.xlsx - Program .pdf"
## [52] "AGU2017_poster_XZ.pdf"
## [53] "Akarsu_Jeomorfolojisi_Lec6.pdf"
## [54] "Akiskanlar_Mekanigi_rev.pdf"
## [55] "angeo-21-21-2003.pdf"
## [56] "APR-D2000240-ResponsetoReviewers-Rev02.docx"
## [57] "Argor_oturumlar.pdf"
## [58] "atmosphere-09-00106.pdf"
## [59] "atmosphere-09-00378.pdf"
## [60] "ATMOSRES-D-20-00012 (1).pdf"
## [61] "ATMOSRES-D-20-00012_R1.pdf"
## [62] "ATMOSRES-D-20-00012_reviewer_comments.pdf"
## [63] "ATMOSRES-D-20-00012.pdf"
## [64] "AX88179_178A_Macintosh_Driver_Installer_v2.9.0_20171011.zip"
## [65] "AX88179_178A_macOS_10.15_above_Driver_Installer_v2.16.0 (1).zip"
## [66] "AX88179_178A_macOS_10.15_above_Driver_Installer_v2.16.0 2"
## [67] "AX88179_178A_macOS_10.15_above_Driver_Installer_v2.16.0.zip"
## [68] "aybe_seminerbilgiformu.docx"
## [69] "Bae2019_Article_DevelopmentOfASingle-MomentClo (1).pdf"
## [70] "Bae2019_Article_DevelopmentOfASingle-MomentClo.pdf"
## [71] "BAP_Uygulama_Esasları_Kılavuz_28_04_2020_v3 (1).pdf"
## [72] "BAP_Uygulama_Esasları_Kılavuz_28_04_2020_v3.pdf"
## [73] "Basvuru_Formu.doc"
## [74] "Besiktepe_1994_circulation_hydrography.pdf"
## [75] "C. Donald Ahrens, Robert Henson - Essentials of Meteorology_ An Invitation to the Atmosphere-Cengage Learning (2018).pdf"
## [76] "CBO9781107707405.011.pdf"
## [77] "check_input_data"
## [78] "Chevuturi-Dimri2015_Article_Inter-comparisonOfPhysicalProc.pdf"
## [79] "cintineo_mwr_jan2014.pdf"
## [80] "citation-318968783.ris"
## [81] "climate-05-00048-v2.pdf"
## [82] "Committee on the Earth system Context for Hominin Evolution, National Research Council - Understanding Climate's Influence on Human Evolution (2010).pdf"
## [83] "deniz-biyolojisi-6.pdf"
## [84] "deniz-planktonlari-ve-ekolojisi1.pdf"
## [85] "Density_colorbar_1000x500 (1).tif"
## [86] "Density_colorbar_1000x500.tif"
## [87] "Diffenbaugh-2020-The-covid--lockdowns-a-window-into-.pdf"
## [88] "dinamiknot1.doc"
## [89] "DiversityofbacteriaisolatedfromTurkishmarineareas.pdf"
## [90] "doğrudan-temin-onay-belgesi.xls"
## [91] "doktora-yeterlik-sınavı-başvuru-formu-g_1935ee314bceeb6433bf21ff0000f8c30df1333a4bceeb6433bf21ff0000f8c30d.doc"
## [92] "Dropbox"
## [93] "Dropbox.zip"
## [94] "DSM_DS1515+_25426.pat"
## [95] "efi_what_science_can_tell_us_1_2011_en.pdf"
## [96] "Emir_Comments_Response_V5_YE.docx"
## [97] "Emir_Paper_Revision_V1_YE.docx"
## [98] "Emir_Paper_Revision_V3_YE.docx"
## [99] "Evaluation_of_the_WRF_model_with_different_domain_.pdf"
## [100] "Evidence that the Great Pacifc Garbage Patch is rapidly accumulating plastic.pdf"
## [101] "Ezber-2015-Investigation-of-local-flow-feature (1).pdf"
## [102] "Ezber-2015-Investigation-of-local-flow-feature.pdf"
## [103] "FileZilla_3.49.1_macosx-x86.app.tar.bz2"
## [104] "FileZilla_3.50.0_macosx-x86.app.tar.bz2"
## [105] "Frederick K. Lutgens_ Edward J. Tarbuck - The atmosphere_ an introduction to meteorology (2016, Pearson) - libgen.lc.pdf"
## [106] "Frederick K. Lutgens_ Edward J. Tarbuck - The atmosphere_ an introduction to meteorology-Pearson (2016).pdf"
## [107] "Friedlingstein-2019-Global-carbon-budget-.pdf"
## [108] "Gao2011_Article_ATwo-momentBulkMicrophysicsCou.pdf"
## [109] "Gimeno-etal-2012-RevGeophys.pdf"
## [110] "gmd-2019-349 (1).bib"
## [111] "gmd-2019-349 (1).ris"
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## [114] "gmd-2019-349.bib"
## [115] "gmd-2019-349.ris"
## [116] "IJG_2013090916272381.pdf"
## [117] "ijgi-08-00204-v2.pdf"
## [118] "Impact_of_Highly_Reflective_Materials_on_Meteorolo.pdf"
## [119] "inputdata_checksum.dat"
## [120] "Install League of Legends euw.app"
## [121] "Install League of Legends euw.zip"
## [122] "Introductory Dynamical Oceanography by Stephen Pond and G L Pickard (Auth.) (z-lib.org).pdf"
## [123] "ipynb.ipynb"
## [124] "ITU_bap_yonerge_16_04_2019_v3 (1).pdf"
## [125] "ITU_bap_yonerge_16_04_2019_v3.pdf"
## [126] "IVD-Alindi-bU85GQ9XV8.pdf"
## [127] "Jane H. Hodgkinson, Frank D. Stacey - Practical Handbook of Earth Science-Taylor & Francis_CRC Press (2017).pdf"
## [128] "Jim Bell - The Earth Book_ From the Beginning to the End of Our Planet, 250 Milestones in the History of Earth Science-Sterling Publishing Co. Inc. (2019).pdf"
## [129] "joc.4457.pdf"
## [130] "Kevin Hamilton (auth.), Kevin Hamilton, Wataru Ohfuchi (eds.) - High Resolution Numerical Modelling of the Atmosphere and Ocean-Springer-Verlag New York (2008) (1).pdf"
## [131] "KiraPfoch_2019_Poster_ESA_Louvain-la-Neuve.pdf"
## [132] "klt-trh-un-1.pdf"
## [133] "klt-trh-un-2.pdf"
## [134] "Launiainen_etal_2013Ambio.pdf"
## [135] "makale çalışma 180820.docx"
## [136] "manual.pdf"
## [137] "mdinhawaii.pdf"
## [138] "Midlatitude Synoptic Meteorology Dynamics, Analysis, and Forecasting by Gary Lackmann (z-lib.org).pdf"
## [139] "model_description_template_lpjg21.doc"
## [140] "Moya-Álvarez2019_Article_ResponseOfTheWRFModelToDiffere.pdf"
## [141] "Müh Jeo-3 Mineral ve kayaçlar.pdf"
## [142] "Murthy2018_Article_WRFSimulationOfASevereHailstor.pdf"
## [143] "MY1DMM_CHLORA-MYD28M.mov"
## [144] "MY1DMM_CHLORA.mov"
## [145] "Neil C. Wells - The Atmosphere and Ocean_ A Physical Introduction (Advancing Weather and Climate Science)-Wiley (2012).pdf"
## [146] "New Recording 6.m4a"
## [147] "noaa_7088_DS1.pdf"
## [148] "ornek.docx"
## [149] "ÖSYM Aday İşlemleri Sistemi - Sınav Başvuru Kayıt Bilgileri Elif Gözler.pdf"
## [150] "ÖSYM Aday İşlemleri Sistemi - Sınav Başvuru Kayıt Bilgileri.pdf"
## [151] "ÖSYM Sonuç Açıklama Sistemi (1).pdf"
## [152] "ÖSYM Sonuç Açıklama Sistemi.pdf"
## [153] "Ozgecmis_Formu.doc"
## [154] "PanoplyMacOS-4.11.4.dmg"
## [155] "Paper_forpreprintserver (1).pdf"
## [156] "Paper_forpreprintserver.pdf"
## [157] "PDF Datastream.pdf"
## [158] "PDF_TL_11_06_08_A.pdf"
## [159] "pericles_1944920858.enw"
## [160] "pericles_1944920858.txt"
## [161] "piyasa-fiyat-araştırma-tutanağı1b8bee4aceeb6433bf21ff0000f8c30d.xls"
## [162] "pngbarn (1).png"
## [163] "pngbarn.png"
## [164] "PngItem_201916.png"
## [165] "Potential_Temperature.pdf"
## [166] "pr_MNA-44_CNRM-CERFACS-CNRM-CM5_historicalandrcp85_r1i1p1_SMHI-RCA4_v1-bc-dbs-wfdei_day_19510101-21001231_2046_2046.nc"
## [167] "pr_MNA-44_CNRM-CERFACS-CNRM-CM5_historicalandrcp85_r1i1p1_SMHI-RCA4_v1-bc-dbs-wfdei_day_19510101-21001231_2046_2046.nc.aux.xml"
## [168] "pr_mna-44_cnrm-cerfacs-cnrm-cm5_historicalandrcp85_r1i1p1_smhi-rca4_v1-bc-dbs-wfdei_day_19510101-21001231_2046_2046.zip"
## [169] "qgis-macos-ltr.dmg"
## [170] "qj.49708737407.pdf"
## [171] "qj.49709942229.pdf"
## [172] "QNAPQfinderProMac-7.4.0.0731.dmg"
## [173] "R1T8MA.jpg"
## [174] "RD9700 Mac Driver"
## [175] "RD9700 Mac Driver 2"
## [176] "RD9700 Mac Driver 3"
## [177] "rd9700-mac-driver (1).zip"
## [178] "rd9700-mac-driver (2).zip"
## [179] "rd9700-mac-driver.zip"
## [180] "remotesensing-09-01143-v2.pdf"
## [181] "remotesensing-12-02253-v2.pdf"
## [182] "Review_AtmoRes-D-20-00012.pdf"
## [183] "roisinGFD2010.pdf"
## [184] "S0169809520300375.bib"
## [185] "S0169809520300375.ris"
## [186] "S0169809520300375.txt"
## [187] "Sarah Cornell_ I Colin Prentice_ Joanna House_ Catherine Downy - Understanding the earth system _ global change science for application-Cambridge University Press (2012).pdf"
## [188] "sari2018.pdf"
## [189] "ScienceDirect_articles_22Jul2020_22-19-21.653"
## [190] "ScienceDirect_articles_22Jul2020_22-19-21.653.zip"
## [191] "Seasonally_asymmetric_transition_of_the_Asian_mons.pdf"
## [192] "singh2015.pdf"
## [193] "snw_cvr"
## [194] "snw_cvr.rar"
## [195] "Song-Sohn2018_Article_AnEvaluationOfWRFMicrophysicsS.pdf"
## [196] "SSRN-id3550308.pdf"
## [197] "SSS_colorbar_1000x500.tif"
## [198] "SST_colorbar_1000x500.tif"
## [199] "sst.wkmean.1981-1989.nc"
## [200] "sst.wkmean.1990-present.nc"
## [201] "Stephen Pond and G L Pickard (Auth.) - Introductory Dynamical Oceanography (1983) - libgen.lc.pdf"
## [202] "Supplementary_Toker_et_al_Revised.pptx"
## [203] "synology-assistant-6.2-24922.dmg"
## [204] "tez-projeleri-bursiyer-bilgi-formu.docx"
## [205] "The_Making_of_the_New_European_Wind_Atlas_Part_1_M.pdf"
## [206] "Thomas D. Potter, Bradley R. Colman - Handbook of Weather, Climate and Water_ Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements-Wiley-Interscience (2003).pdf"
## [207] "TM_NWS_ER_69.pdf"
## [208] "Toker-11.12.19.pdf"
## [209] "turqua20_kurs.csv"
## [210] "turqua20_kurs.csv.zip"
## [211] "turqua20_kuvaterner_atolye.csv"
## [212] "turqua20_kuvaterner_atolye.csv.zip"
## [213] "turqua20_Quaternary_workshop.csv"
## [214] "turqua20_Quaternary_workshop.csv.zip"
## [215] "turqua20_R_atolye.csv"
## [216] "Unite_4.pdf"
## [217] "Unite_9 (1).pdf"
## [218] "Unite_9.pdf"
## [219] "unluata_etal.pdf"
## [220] "video 2.MOV"
## [221] "video.MOV"
## [222] "Vorticity.PDF"
## [223] "Wang_etal_hess-2012 (1).pdf"
## [224] "Wang_etal_hess-2012.pdf"
## [225] "Water Exchange through Canal İstanbul and Bosphorus Strait.pdf"
## [226] "wct-4.5.1"
## [227] "wct-4.5.1.zip"
## [228] "WhatsApp Image 2020-07-14 at 00.31.59.jpeg"
## [229] "WINDS 850 - 4 SEASONS.docx"
## [230] "Zhang2018_Article_ApplyingTheWRFDouble-MomentSix.pdf"
## [231] "د. عزام أبو حبيب.pptx"file.path("~","Users","emirtoker","Downloads","-this_is_my_file.csv")## [1] "~/Users/emirtoker/Downloads/-this_is_my_file.csv"Practice - R Language
Find the Data
- file.path()
# Option 1
# setwd("/Users/emirtoker/Downloads/")
# read.csv("-this_is_my_file.csv")
# Option 2
path <- file.path("~","Users","emirtoker","Downloads","-this_is_my_file.csv")
path## [1] "~/Users/emirtoker/Downloads/-this_is_my_file.csv"# read.csv(path)Practice - R Language
Read Data
with utils (R utility functions)
- read.csv() - Comma Seperated Value
- read.delim() - Tab Delimited Data
- read.table() - Exocit file format
Practice - R Language
Read Data with utils (R utility functions)
read.csv() - Comma Seperated Value
Practice - R Language
Read Data with utils (R utility functions)
read.delim() - Tab Delimited Data
Practice - R Language
Read Data with utils (R utility functions)
read.table() - Exocit file format
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
17061_Sariyer_Sariyer_15dk<- read.csv( “~/Desktop/NCL_Script_ve_Gorsel/Makale/ time_series_makale/mgm_veri/17061_Sariyer_Sariyer_15dk.txt”, header=FALSE, sep=“;”)View(
17061_Sariyer_Sariyer_15dk)
~
Practice - R Language
Manage Directory, Find and Read Data
Instructions
- Go to main webpage of course
- Open Data “Istanbul_Goztepe_Precipitation_1846-2013_Monthly” (.dat) LINK
- Copy and Paste it in your “Downloads” directory in a text file
- Open your R Studio
We Have 4 Ways to Read
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 1 - GO TO FILE
- Check your Project Name and your Working directory
- Go to “Downloads” directory in R Studio
- List files and Read Data with three different read functions
- read.csv()
- read.delim()
- read.table()
- Choose the best
- Assign your data as “precip_1”
Caraful about header, seperater and missing data
look at the main web page for examples
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 2 - CALL THE FILE
- Go Back to your Working directory
- Define your file path with file.path()
- Assign the path a new variable as “path_my_file”
- Use your best read() function
- Read the file with “path_my_file”
- Assign your data as “precip_2”
path_my_file <- file.path("~","Downloads")
precip_2 <- read.table(path_my_file)Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 3 - IMPORT THE FILE
- Use “Import Datase”
- Assign your data as “precip_3”
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 4 - DOWNLOAD THE FILE
- Copy the LINK of data
- Use your best read() function
- Read the file with this function and LINK
- Assign your data as “precip_4”
precip_4 <- read.table("link")Practice - R Programming
Practice - R Programming
Objectives
Identify the Data
Indexing
Use Condition Statements
Plot
Practice - R Programming
Meet with the Data
- Look at structure
- Learn attributes and dimensions
- Rename attributes
? dimensions, variables and types ?
month.name
month.abb
attributes(precip_2)
attributes(precip_2)[1]
attributes(precip_2)[[1]]
attributes(precip_2)[[1]] <- c("Year",month.abb)
attr(precip_2,"names") <- c("Year",month.abb)
attr(precip_2,"row.names") <- 1846:2013
precip_2a <- precip_2[-1]
head(precip_2a)Practice - R Programming
Clear NA and Choose Colomn
- Print “precip_2a”
- Delete rows which include NA ( na.omit() )
- Assign it as “precip_2b”
- Select summer season
- Assign it as “precip_2b_summer”
precip_2b <- na.omit(precip_2a)
precip_2b_summer <- precip_2b[ ,6:8]Practice - R Programming
Use Condition Statements - if
- Compare June Mean Precipitation with July
- IF June mean precipitation is LOWER than July then print “June has low precipitation.”
mean_jun <- mean(precip_2b_summer$Jun)
mean_jul <- mean(precip_2b_summer$Jul)
if (mean_jun > mean_jul) {
print("June has low precipitation.")
}
colMeans(precip_2b_summer)
Practice - R Programming
Use Condition Statements - else
- IF June mean precipitation is LOWER than July then print “June has low precipitation.”
- ELSE print “June has high precipitation.”
- Calculate mean of each month ( colMeans() )
mean_jun <- mean(precip_2b_summer$Jun)
mean_jul <- mean(precip_2b_summer$Jul)
if (mean_jun < mean_jul) {
print("June has low precipitation.")
} else {
print("June has high precipitation.")
}
colMeans(precip_2b_summer)Practice - R Programming
Plot
Problem : Extremes and Outliers
- Plot precipitation for June
- Add title and unit
plot(precip_2b_summer$Jun,
xlab = "Years",
ylab = "Precipitation [mm/month]",
main = "Istanbul Monthly Precipitation - June",
type = "l",
col="blue")Practice - R Programming
Plot
Problem : Extremes and Outliers
- Edit x-axis, which years are they ?
- What about August ?
attr(precip_2b_summer,"row.names")
x_years <- attr(precip_2b_summer,"row.names")
plot(x_years,
precip_2b_summer$Jun,
xlab = "Years",
ylab = "Precipitation [mm/month]",
main = "Istanbul Monthly Precipitation - June",
type = "l",
col="blue")
plot(precip_2b_summer$Aug)Practice - R Programming
Plot
Problem : Extremes and Outliers
Homework-2
R Programming - Loops
Loops are R’s method for repeating a task, which makes them a useful tool for programming simulations.
R Programming - repeat Loops
repeat
{
message("Happy Groundhog Day!")
break
}R Programming - repeat Loops
coins <- 3
game <- 0
repeat
{
game <- game + 1
coins <- coins -1
print(game)
print("nice try, play again")
if (coins==0) {
break
}
}## [1] 1
## [1] "nice try, play again"
## [1] 2
## [1] "nice try, play again"
## [1] 3
## [1] "nice try, play again"[1] 1
[1] "nice try, play again"
[1] 2
[1] "nice try, play again"
[1] 3
[1] "nice try, play again"R Programming - while Loops
While loops are like backward repeat loops.
while(condition) {
conditional statement
}R Programming - while Loops
coins <- 3
game <- 0
while(coins >= 0)
{
coins <- coins -1
game <- game + 1
print(game)
print("nice try, play again")
}## [1] 1
## [1] "nice try, play again"
## [1] 2
## [1] "nice try, play again"
## [1] 3
## [1] "nice try, play again"
## [1] 4
## [1] "nice try, play again"R Programming - for Loops
The third type of loop is to be used when you know exactly how many times you want the code to repeat.
R Programming - for Loops
for(i in 1:2) {
message("just say it ", i, " times")
}## just say it 1 times## just say it 2 timesR Programming - for Loops
for(i in c(1,2) ) {
message("just say it ", i, " times")
}## just say it 1 times## just say it 2 timesfor(i in c("apple","banana") ) {
message("just say it ", i, " times")
}## just say it apple times## just say it banana timesit is related with length of vector
R Programming - for Loops
month.name## [1] "January" "February" "March" "April" "May"
## [6] "June" "July" "August" "September" "October"
## [11] "November" "December"for(month in month.name) {
message("The month of ", month)
}## The month of January## The month of February## The month of March## The month of April## The month of May## The month of June## The month of July## The month of August## The month of September## The month of October## The month of November## The month of DecemberR Programming - apply Loops
- The apply() functions form the basis of more complex combinations and helps to perform operations with very few lines of code.
- More specifically, the family is made up of the apply(), lapply() , sapply(), vapply(), mapply(), rapply(), and tapply() functions.
apply(X, MARGIN, FUN, ...)
# X is an array or a matrix, dim(X) must have a positive length
# MARGIN=1, it applies over rows, whereas with
# MARGIN=2, it works over columns. Note that when you use the construct
# MARGIN=c(1,2), it applies to both rows and columns
# FUN, which is the function that you want to apply to the data. apply(precip_2b_summer, MARGIN=1, mean)
apply(precip_2b_summer, MARGIN=2, mean)
apply(precip_2b_summer, MARGIN=c(1,2), mean)
apply(precip_2b_summer, MARGIN=c(2,1), mean)R Programming - apply Loops
R Programming - lapply Loops
lapply(precip_2b_summer,"[",1)
sapply(precip_2b_summer,"[",1)