diff --git a/DESCRIPTION b/DESCRIPTION
index c1f6aacd09f6520f362c455613f08334a51c24b8..906d77c3fac586ebe1f7c0e6175ce26f2c52dc92 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -63,6 +63,8 @@ Imports:
RCurl
Suggests:
xtable,
- EGRET
+ EGRET,
+ knitr
LazyLoad: yes
LazyData: yes
+VignetteBuilder: knitr
diff --git a/inst/doc/dataRetrieval.pdf b/inst/doc/dataRetrieval.pdf
index a318b868a025a593b301ed6a90543c0c360c97ac..207ffeebf0b083755d7cfc647cf009fd7349198f 100644
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diff --git a/vignettes/Rplots.pdf b/vignettes/Rplots.pdf
deleted file mode 100644
index 1ea11ca3db2dea66119dbe12b19dbb2b9040206d..0000000000000000000000000000000000000000
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diff --git a/vignettes/dataRetrieval-concordance.tex b/vignettes/dataRetrieval-concordance.tex
index 6666b7b667561fba80b016bbd472f5700fae6068..6531fec293bf5529c291ee7833f0ef8b878bf68a 100644
--- a/vignettes/dataRetrieval-concordance.tex
+++ b/vignettes/dataRetrieval-concordance.tex
@@ -1,16 +1,9 @@
\Sconcordance{concordance:dataRetrieval.tex:dataRetrieval.Rnw:%
-1 84 1 1 8 1 1 1 10 16 0 1 2 5 1 1 10 15 0 1 2 13 1 1 2 1 0 1 2 1 0 1 1 %
-3 0 1 2 2 1 1 2 7 0 1 2 7 1 1 3 2 0 1 1 12 0 1 2 5 1 1 4 3 0 1 3 1 0 1 %
-3 7 0 1 3 4 0 1 2 2 1 1 8 7 0 1 4 1 0 1 2 21 0 1 2 7 1 1 3 2 0 2 1 7 0 %
-1 2 1 1 1 2 7 0 1 2 9 1 1 4 2 0 2 1 1 2 3 0 1 2 4 1 1 3 1 0 3 1 1 3 5 0 %
-1 3 4 1 1 2 1 0 1 4 3 0 1 1 1 4 3 0 3 1 3 0 1 2 3 1 1 -5 1 9 14 1 1 3 1 %
-0 1 1 1 2 1 0 1 3 5 0 2 2 10 0 1 2 3 1 1 2 1 0 1 4 3 0 1 1 4 0 1 3 3 1 %
-1 -6 1 10 12 1 1 4 2 0 2 1 1 3 1 0 1 3 1 0 1 1 7 0 1 2 1 1 1 6 5 0 1 1 %
-3 0 1 2 2 1 1 -4 1 8 11 1 1 3 2 0 1 1 12 0 1 2 8 1 1 3 2 0 5 1 3 0 1 2 %
-13 1 1 2 1 0 1 1 3 0 1 2 8 1 1 2 1 0 2 1 1 3 5 0 1 2 2 1 1 11 18 0 1 2 %
-9 1 1 3 5 0 1 2 2 1 1 12 24 0 1 2 11 1 1 14 12 0 1 2 9 1 1 2 17 0 1 3 %
-28 1 1 2 1 0 2 1 3 0 1 2 16 1 1 2 1 0 2 1 3 0 1 2 7 1 1 2 1 0 3 1 1 2 2 %
-1 11 0 1 1 19 0 1 2 6 1 1 3 2 0 1 1 3 0 1 2 3 1 1 -5 1 9 21 1 1 2 4 0 1 %
-2 1 1 1 2 13 0 1 2 6 1 1 2 1 0 1 1 3 0 1 2 3 1 1 2 4 0 1 2 7 1 1 2 1 0 %
-1 1 3 0 1 2 1 1 1 2 4 0 1 2 10 1 1 5 47 0 1 2 9 1 1 6 45 0 1 2 2 1 1 6 %
-27 0 1 2 8 1 1 2 1 0 4 1 1 9 10 0 1 2 3 1 1 3 5 0 1 2 53 1}
+1 49 1 55 0 1 6 11 1 1 5 41 1 10 0 16 1 9 0 21 1 5 0 %
+6 1 8 0 14 1 14 0 24 1 11 0 17 1 20 0 15 1 10 0 5 1 8 %
+0 20 1 5 0 16 1 4 0 21 1 10 0 20 1 5 0 4 1 18 0 13 1 %
+9 0 26 1 9 0 10 1 10 0 14 1 21 0 19 1 5 0 19 1 5 0 17 %
+1 8 0 14 1 15 0 16 1 5 0 61 1 6 0 14 1 17 0 36 1 5 0 %
+24 1 5 0 20 1 38 0 13 1 10 0 22 1 5 0 5 1 14 0 10 1 5 %
+0 7 1 5 0 16 1 51 0 15 1 49 0 7 1 32 0 26 1 25 0 8 1 %
+5 0 56 1}
diff --git a/vignettes/dataRetrieval-fig1.pdf b/vignettes/dataRetrieval-fig1.pdf
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index dbfd9bda6bacf9c84842581d24aad56e85715d44..0000000000000000000000000000000000000000
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diff --git a/vignettes/dataRetrieval-fig2.pdf b/vignettes/dataRetrieval-fig2.pdf
deleted file mode 100644
index 01ce0beba2e98a3c5754144c36a445407def471c..0000000000000000000000000000000000000000
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diff --git a/vignettes/dataRetrieval-fig3.pdf b/vignettes/dataRetrieval-fig3.pdf
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index 099e61b857d9b23f054ac3ffdcaaefc505732802..0000000000000000000000000000000000000000
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diff --git a/vignettes/dataRetrieval-figegretEx.pdf b/vignettes/dataRetrieval-figegretEx.pdf
deleted file mode 100644
index a191efc14b2a5f7f6eab9c68304bf34433cc4a67..0000000000000000000000000000000000000000
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diff --git a/vignettes/dataRetrieval.Rnw b/vignettes/dataRetrieval.Rnw
index a92f5947bfd6a56788a3cc14de45b9d77645a18e..11455595d5c818ae8dc8aa61f0325214f677423a 100644
--- a/vignettes/dataRetrieval.Rnw
+++ b/vignettes/dataRetrieval.Rnw
@@ -1,8 +1,9 @@
%\VignetteIndexEntry{Introduction to the dataRetrieval package}
+%\VignetteEngine{knitr::knitr}
%\VignetteDepends{}
-%\VignetteSuggests{}
-%\VignetteImports{}
-%\VignettePackage{}
+%\VignetteSuggests{xtable,EGRET}
+%\VignetteImports{zoo, XML, RCurl}
+%\VignettePackage{dataRetrieval}
\documentclass[a4paper,11pt]{article}
@@ -12,10 +13,12 @@
\usepackage[numbers, round]{natbib}
\usepackage[american]{babel}
\usepackage{authblk}
-\usepackage{footnote}
+\usepackage{subfig}
\usepackage{placeins}
+\usepackage{footnote}
+\usepackage{tabularx}
\renewcommand\Affilfont{\itshape\small}
-\usepackage{Sweave}
+
\renewcommand{\topfraction}{0.85}
\renewcommand{\textfraction}{0.1}
\usepackage{graphicx}
@@ -42,7 +45,16 @@
\newcommand{\Rfunarg}[1]{{\texttt{#1}}}
\begin{document}
-\SweaveOpts{concordance=TRUE}
+
+
+<<openLibrary, echo=FALSE>>=
+library(xtable)
+options(continue=" ")
+options(width=60)
+library(knitr)
+
+@
+
%------------------------------------------------------------
\title{The dataRetrieval R package}
@@ -51,7 +63,14 @@
\author[1]{Robert Hirsch}
\affil[1]{United States Geological Survey}
-\SweaveOpts{highlight=TRUE, tidy=TRUE, keep.space=TRUE, keep.blank.space=FALSE, keep.comment=TRUE, keep.source=TRUE}
+
+<<include=TRUE ,echo=FALSE,eval=TRUE>>=
+opts_chunk$set(highlight=TRUE, tidy=TRUE, keep.space=TRUE, keep.blank.space=FALSE, keep.comment=TRUE, tidy=FALSE)
+knit_hooks$set(inline = function(x) {
+ if (is.numeric(x)) round(x, 3)})
+knit_hooks$set(crop = hook_pdfcrop)
+@
+
\maketitle
\tableofcontents
@@ -77,31 +96,20 @@ In this section, we will run through 5 examples, documenting how to get raw data
%------------------------------------------------------------
The United States Geological Survey organizes their hydrological data in standard structure. Streamgages are located throughout the United States, and each streamgage has a unique ID. Often (but not always), these ID's are 8 digits. The first step to finding data is discoving this 8-digit ID. One potential tool for discovering data is Environmental Data Discovery and Transformation (EnDDaT): \url{http://cida.usgs.gov/enddat/}. Follow the example on the EnDDaT web page to learn how to discover USGS stations and available data from any location in the United States.
-Once the site-ID is known, the next required input for USGS data retrievals is the 'parameter code'. This is a 5-digit code that specifies what measured paramater is being requested. A complete list of possible USGS parameter codes can be found at:
-
-\url{http://nwis.waterdata.usgs.gov/usa/nwis/pmcodes?radio_pm_search=param_group&pm_group=All+--+include+all+parameter+groups&pm_search=&casrn_search=&srsname_search=&format=html_table&show=parameter_group_nm&show=parameter_nm&show=casrn&show=srsname&show=parameter_units}
+Once the site-ID is known, the next required input for USGS data retrievals is the 'parameter code'. This is a 5-digit code that specifies what measured paramater is being requested. A complete list of possible USGS parameter codes can be found at \url{http://go.usa.gov/bVDz}.
Not every station will measure all parameters. A short list of commonly measured parameters is shown in Table \ref{tab:params}.
-<<openLibrary, echo=FALSE>>=
-library(xtable)
-options(continue=" ")
-# options(width=60)
-# options(SweaveHooks=list(fig=function()
-# par(mar=c(4.1,4.1,1.1,4.1),oma=c(0,0,0,0))))
-@
-
-<<label=tableParameterCodes, echo=FALSE,results=tex>>=
+<<tableParameterCodes, echo=FALSE,results='asis'>>=
pCode <- c('00060', '00065', '00010','00045','00400')
shortName <- c("Discharge [cfs]","Gage height [ft]","Temperature [C]", "Precipitation [in]", "pH")
data.df <- data.frame(pCode, shortName, stringsAsFactors=FALSE)
-data.table <- xtable(data.df,label="tab:params",
+xtable(data.df,label="tab:params",
caption="Common USGS Parameter Codes")
-print(data.table,
- caption.placement="top",include.rownames=FALSE, table.placement="!ht")
+
@
For real-time data, the parameter code and site ID will suffice. For most variables that are measured on a continuous basis, the USGS stores the historical data as daily values. These daily values may be in the form of statistics such as the daily mean values, but they can also include daily maximums, minimums or medians. These different statistics are specified by a 5-digit \texttt{"}stat code\texttt{"}. A complete list of stat codes can be found here:
@@ -109,19 +117,19 @@ For real-time data, the parameter code and site ID will suffice. For most varia
\url{http://nwis.waterdata.usgs.gov/nwis/help/?read_file=stat&format=table}
Some common stat codes are shown in Table \ref{tab:stat}.
-<<label=tableStatCodes, echo=FALSE,results=tex>>=
+<<tableStatCodes, echo=FALSE,results='asis'>>=
StatCode <- c('00001', '00002', '00003','00008')
shortName <- c("Maximum","Minimum","Mean", "Median")
data.df <- data.frame(StatCode, shortName, stringsAsFactors=FALSE)
-data.table <- xtable(data.df,label="tab:stat",
+xtable(data.df,label="tab:stat",
caption="Commonly found USGS Stat Codes")
-print(data.table,
- caption.placement="top",include.rownames=FALSE, table.placement="!ht")
+
@
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Site Information}
\label{sec:usgsSite}
@@ -134,7 +142,7 @@ print(data.table,
Use the getSiteFileData function to obtain all of the information available for a particular USGS site such as full station name, drainage area, latitude, and longitude:
-<<label=getSite, echo=TRUE>>=
+<<getSite, echo=TRUE>>=
library(dataRetrieval)
# Site ID for Choptank River near Greensboro, MD
siteNumber <- "01491000"
@@ -143,18 +151,19 @@ ChoptankInfo <- getSiteFileData(siteNumber)
A list of the available columns are found in Appendix \ref{sec:appendix2INFO}: INFO dataframe. Pulling out a specific example piece of information, in this case station name can be done as follows:
-<<siteNames, echo=TRUE>>=
+<<siteNames2, echo=TRUE>>=
ChoptankInfo$station.nm
@
Site information is obtained from \url{http://waterservices.usgs.gov/rest/Site-Test-Tool.html}
\FloatBarrier
+
%------------------------------------------------------------
\subsubsection{getDataAvailability}
\label{sec:usgsDataAvailability}
%------------------------------------------------------------
To find out the available data at a particular USGS site, including measured parameters, period of record, and number of samples (count), use the getDataAvailability function:
-<<label=getSiteAvailability, echo=TRUE>>=
+<<getSiteAvailability, echo=TRUE>>=
# Continuing from the previous example:
ChoptankAvailableData <- getDataAvailability(siteNumber)
head(ChoptankAvailableData)
@@ -165,24 +174,28 @@ There is an additional argument to the getDataAvailability called longNames, whi
It is also possible to only request parameter information for a subset of variables. In the following example, we retrieve just the daily mean parameter information from the Choptank data availability dataframe (excluding all unit value and water quality values). getMultipleParameterNames is the function that is embedded in the getDataAvailability, but here can be used as a standalone function.
-<<label=getSiteExtended, echo=TRUE>>=
+<<getSiteExtended, echo=TRUE>>=
# Continuing from the previous example:
# This pulls out just the daily data:
-ChoptankDailyData <- subset(ChoptankAvailableData,"dv" == service)
+ChoptankDailyData <- subset(ChoptankAvailableData,
+ "dv" == service)
# This pulls out the mean:
-ChoptankDailyData <- subset(ChoptankDailyData,"00003" == statCd)
+ChoptankDailyData <- subset(ChoptankDailyData,
+ "00003" == statCd)
#Now, make a call to get all of the parameter information:
-pCodeINFO <- getMultipleParameterNames(ChoptankDailyData$parameter_cd)
+pCodeINFO <- getMultipleParameterNames(
+ ChoptankDailyData$parameter_cd)
-#Merge the available dataframe with the parameter information dataframe:
-ChoptankDailyData <- merge(ChoptankDailyData,pCodeINFO,by="parameter_cd")
+#Merge the available dataframes:
+ChoptankDailyData <- merge(ChoptankDailyData,
+ pCodeINFO,by="parameter_cd")
@
The daily data at the Choptank River site can be displayed in a \LaTeX table using the xtable package. See Appendix \ref{app:createWordTable} for instructions on converting an R dataframe to a table in Microsoft Excel or Word.
-<<label=tablegda, echo=TRUE,results=tex>>=
+<<tablegda, echo=TRUE,results='asis'>>=
tableData <- with(ChoptankDailyData,
data.frame(shortName=srsname,
Start=as.character(startDate),
@@ -192,20 +205,20 @@ tableData <- with(ChoptankDailyData,
)
-data.table <- xtable(tableData,label="tab:gda",
+xtable(tableData,label="tab:gda",
caption="Daily mean data availabile at the Choptank River")
-print(data.table,
- caption.placement="top",include.rownames=FALSE)
+
@
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Parameter Information}
\label{sec:usgsParams}
%------------------------------------------------------------
To obtain all of the available information concerning a measured parameter, use the getParameterInfo function:
-<<label=getSite, echo=TRUE>>=
+<<label=getPCodeInfo, echo=TRUE>>=
# Using defaults:
parameterCd <- "00618"
parameterINFO <- getParameterInfo(parameterCd)
@@ -233,7 +246,8 @@ parameterCd <- "00060" # Discharge (cfs)
startDate <- "" # Will request earliest date
endDate <- "" # Will request latest date
-discharge <- retrieveNWISData(siteNumber, parameterCd, startDate, endDate)
+discharge <- retrieveNWISData(siteNumber,
+ parameterCd, startDate, endDate)
@
The variable datetime is automatically imported as a Date. Each requested parameter has a value and remark code column. The names of these columns depend on the requested parameter and stat code combinations. USGS remark codes are often \texttt{"}A\texttt{"} (approved for publication) or \texttt{"}P\texttt{"} (provisional data subject to revision). A more complete list of remark codes can be found here:
@@ -248,15 +262,16 @@ startDate <- "2012-01-01"
endDate <- "2012-06-30"
temperatureAndFlow <- retrieveNWISData(siteNumber, parameterCd,
- startDate, endDate, StatCd=statCd,interactive=FALSE)
+ startDate, endDate, StatCd=statCd)
@
Daily data is pulled from \url{http://waterservices.usgs.gov/rest/DV-Test-Tool.html}.
-An example of plotting the above data (Figure \ref{fig:TD}):
+An example of plotting the above data (Figure \ref{fig:getNWIStemperaturePlot}):
-<<label=getNWIStemperaturePlot, echo=TRUE>>=
+<<getNWIStemperaturePlot, echo=TRUE, fig.cap="Temperature and discharge plot of Choptank River in 2012.">>=
+par(mar=c(5,5,5,5))
colnames <- names(temperatureAndFlow)
with(temperatureAndFlow, plot(
get(colnames[3]), get(colnames[6]),
@@ -273,20 +288,10 @@ title(paste(ChoptankInfo$station.nm,"2012",sep=" "))
@
-\begin{figure}
-\begin{center}
-<<label=fig1, fig=TRUE,echo=FALSE,width=6,height=4>>=
-<<getNWIStemperaturePlot>>
-@
-\end{center}
-\caption{Temperature and discharge plot of Choptank River in 2012.}
-\label{fig:TD}
-\end{figure}
-
-
There are occasions where NWIS values are not reported as numbers, instead there might be text describing a certain event such as \texttt{"}Ice\texttt{"}. Any value that cannot be converted to a number will be reported as NA in this package.
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Unit Values}
\label{sec:usgsRT}
@@ -297,9 +302,7 @@ Any data that are collected at regular time intervals (such as 15-minute or hour
parameterCd <- "00060" # Discharge (cfs)
startDate <- "2012-05-12"
-# or use (yesterday): startDate <- as.character(Sys.Date()-1)
endDate <- "2012-05-13"
-# or use (today): endDate <- as.character(Sys.Date())
dischargeToday <- retrieveUnitNWISData(siteNumber, parameterCd,
startDate, endDate)
@
@@ -310,11 +313,11 @@ head(dischargeToday)
Note that time now becomes important, so the variable datetime is a POSIXct, and the time zone is included in a separate column. Data is pulled from \url{http://waterservices.usgs.gov/rest/IV-Test-Tool.html}. There are occasions where NWIS values are not reported as numbers, instead a common example is \texttt{"}Ice\texttt{"}. Any value that cannot be converted to a number will be reported as NA in this package.
-A simple plotting example is shown in Figure \ref{fig:RT}:
-<<label=getNWISUnit, echo=TRUE>>=
+A simple plotting example is shown in Figure \ref{fig:getNWISUnitPlot}:
+<<getNWISUnitPlot, echo=TRUE, fig.cap="Real-time discharge plot of Choptank River from May 12-13, 2012.">>=
colnames <- names(dischargeToday)
with(dischargeToday, plot(
- get(colnames[3]), get(colnames[4]),
+ dateTime, get(colnames[4]),
ylab="Discharge [cfs]",xlab=""
))
title(ChoptankInfo$station.nm)
@@ -322,17 +325,9 @@ title(ChoptankInfo$station.nm)
@
\newpage
-\begin{figure}
-\begin{center}
-<<label=fig2, fig=TRUE,echo=FALSE,width=6,height=4>>=
-<<getNWISUnit>>
-@
-\end{center}
-\caption{Real-time discharge plot of Choptank River from May 12-13, 2012.}
-\label{fig:RT}
-\end{figure}
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Water Quality Values}
\label{sec:usgsWQP}
@@ -354,9 +349,9 @@ dissolvedNitrateSimple <- getQWData(siteNumber, parameterCd,
startDate, endDate)
names(dissolvedNitrateSimple)
@
-Note that in this dataframe, datetime is imported as Dates (no times are included), and the qualifier is either blank or \texttt{"}\verb@<@\texttt{"} signifying a censored value. A plotting example is shown in Figure \ref{fig:nitrate}.
+Note that in this dataframe, datetime is imported as Dates (no times are included), and the qualifier is either blank or \texttt{"}\verb@<@\texttt{"} signifying a censored value. A plotting example is shown in Figure \ref{fig:getQWtemperaturePlot}.
-<<label=getQWtemperaturePlot, echo=TRUE>>=
+<<getQWtemperaturePlot, echo=TRUE, fig.cap="Nitrate plot of Choptank River.">>=
with(dissolvedNitrateSimple, plot(
dateTime, value.00618,
xlab="Date",ylab = paste(parameterINFO$srsname,
@@ -365,17 +360,8 @@ with(dissolvedNitrateSimple, plot(
title(ChoptankInfo$station.nm)
@
-\begin{figure}
-\begin{center}
-<<label=fig3, fig=TRUE,echo=FALSE,width=6,height=4>>=
-<<getQWtemperaturePlot>>
-@
-\end{center}
-\caption{Nitrate plot of Choptank River.}
-\label{fig:nitrate}
-\end{figure}
-
\FloatBarrier
+
%------------------------------------------------------------
\subsection{STORET Water Quality Retrievals}
\label{sec:usgsSTORET}
@@ -402,11 +388,13 @@ pCode <- c("00618","71851")
startDate <- "1964-06-11"
endDate <- "2012-12-18"
url_qw <- constructNWISURL(siteNumber,pCode,startDate,endDate,'qw')
-url_dv <- constructNWISURL(siteNumber,"00060",startDate,endDate,'dv',statCd="00003")
+url_dv <- constructNWISURL(siteNumber,"00060",startDate,endDate,
+ 'dv',statCd="00003")
url_uv <- constructNWISURL(siteNumber,"00060",startDate,endDate,'uv')
@
\FloatBarrier
+
%------------------------------------------------------------
\section{Data Retrievals Structured For Use In The EGRET Package}
%------------------------------------------------------------
@@ -427,6 +415,7 @@ INFO <-getMetaData(siteNumber,parameterCd, interactive=FALSE)
Column names in the INFO dataframe are listed in Appendix 2 (\ref{sec:appendix2INFO}).
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Daily Data}
%------------------------------------------------------------
@@ -436,58 +425,77 @@ The function to obtain the daily values (discharge in this case) is getDVData.
siteNumber <- "01491000"
startDate <- "2000-01-01"
endDate <- "2013-01-01"
-# This call will get NWIS data that is in cfs, and convert it
-# to cms since we didn't override the default in the convert argument:
-Daily <- getDVData(siteNumber, "00060", startDate, endDate,interactive=FALSE)
+# This call will get NWIS (cfs) data , and convert it to cms:
+Daily <- getDVData(siteNumber, "00060", startDate, endDate)
@
Details of the Daily dataframe are listed below:
-<<label=colNamesDaily, echo=FALSE,results=tex>>=
+<<colNamesDaily, echo=FALSE,results='asis'>>=
ColumnName <- c("Date", "Q", "Julian","Month","Day","DecYear","MonthSeq","Qualifier","i","LogQ","Q7","Q30")
Type <- c("Date", "number", "number","integer","integer","number","integer","string","integer","number","number","number")
-Description <- c("Date", "Discharge", "Number of days since January 1, 1850", "Month of the year [1-12]", "Day of the year [1-366]", "Decimal year", "Number of months since January 1, 1850", "Qualifing code", "Index of days from the start of the data frame", "Natural logarithm of Q", "7 day running average of Q", "30 running average of Q")
+Description <- c("Date", "Discharge in cms", "Number of days since January 1, 1850", "Month of the year [1-12]", "Day of the year [1-366]", "Decimal year", "Number of months since January 1, 1850", "Qualifing code", "Index of days, starting with 1", "Natural logarithm of Q", "7 day running average of Q", "30 running average of Q")
Units <- c("date", "cms","days", "months","days","years","months", "character","days","numeric","cms","cms")
DF <- data.frame(ColumnName,Type,Description,Units)
-data.table <- xtable(DF,
- caption="Daily dataframe")
-print(data.table, caption.placement="top",floating="FALSE",latex.environments=NULL,include.rownames=FALSE)
+xtable(DF, caption="Daily dataframe")
+
@
-\\*
+
If there are discharge values of zero, the code will add a small constant to all of the daily discharges. This constant is 0.001 times the mean discharge. The code will also report on the number of zero values and the size of the constant. EGRET should only be used if the number of zero values is a very small fraction of the total days in the record (say less than 0.1\% of the days). Columns Q7 and Q30 are the 7 and 30 day running averages for the 7 or 30 days ending on this specific date.
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Sample Data}
%------------------------------------------------------------
The function to obtain sample data from the water quality portal is getSampleData. The arguments for this function are also siteNumber, ParameterCd, StartDate, EndDate, interactive. These are the same inputs as getRawQWData or getQWData as described in the previous section.
<<secondExample>>=
+parameterCd <- "00618"
Sample <-getSampleData(siteNumber,parameterCd,
startDate, endDate,interactive=FALSE)
@
-Details of the Sample dataframe are listed below:
+\pagebreak
-<<label=colNamesQW, echo=FALSE,results=tex>>=
-ColumnName <- c("Date", "ConcLow", "ConcHigh", "Uncen", "ConcAve", "Julian","Month","Day","DecYear","MonthSeq","SinDY","CosDY","Q footnote","LogQ footnote")
-Type <- c("Date", "number","number","integer","number", "number","integer","integer","number","integer","number","number","number","number")
-Description <- c("Date", "Lower limit of concentration", "Upper limit of concentration", "Uncensored data (1=true, 0=false)", "Average of ConcLow and ConcHigh","Number of days since January 1, 1850", "Month of the year [1-12]", "Day of the year [1-366]", "Decimal year", "Number of months since January 1, 1850", "Sine of DecYear", "Cosine of DecYear", "Discharge", "Natural logarithm of flow")
-Units <- c("date","mg/L","mg/L","integer","mg/L","days","months","days","years","months","numeric","numeric","cms", "numeric")
+Details of the Sample dataframe are listed below:
-DF <- data.frame(ColumnName,Type,Description,Units)
+\begin{table}[!ht]
+\begin{minipage}{\linewidth}
+\begin{center}
+\caption{Sample dataframe}
+\begin{tabular}{llll}
+ \hline
+ColumnName & Type & Description & Units \\
+ \hline
+Date & Date & Date & date \\
+ ConcLow & number & Lower limit of concentration & mg/L \\
+ ConcHigh & number & Upper limit of concentration & mg/L \\
+ Uncen & integer & Uncensored data (1=true, 0=false) & integer \\
+ ConcAve & number & Average of ConcLow and ConcHigh & mg/L \\
+ Julian & number & Number of days since January 1, 1850 & days \\
+ Month & integer & Month of the year [1-12] & months \\
+ Day & integer & Day of the year [1-366] & days \\
+ DecYear & number & Decimal year & years \\
+ MonthSeq & integer & Number of months since January 1, 1850 & months \\
+ SinDY & number & Sine of DecYear & numeric \\
+ CosDY & number & Cosine of DecYear & numeric \\
+ Q \footnotemark[1] & number & Discharge & cms \\
+ LogQ \footnotemark[1] & number & Natural logarithm of flow & numeric \\
+ \hline
+\end{tabular}
+\end{center}
+\end{minipage}
+\end{table}
-data.table <- xtable(DF,
- caption="Sample dataframe")
-print(data.table, caption.placement="top",include.rownames=FALSE,table.placement="!ht",
- sanitize.text.function=function(str)gsub("footnote","\\footnotemark[1]",str,fixed=TRUE))
-@
\footnotetext[1]{Flow columns are populated from data in the Daily dataframe after calling the mergeReport function.}
\FloatBarrier
+
+
%------------------------------------------------------------
\subsection{Censored Values: Summation Explanation}
%------------------------------------------------------------
@@ -497,7 +505,7 @@ As an example to understand how the dataRetrieval package handles a more complex
\begin{center}
-<<label=exampleComplexQW, echo=FALSE,results=tex>>=
+<<label=exampleComplexQW, echo=FALSE, eval=TRUE,results='asis'>>=
cdate <- c("2003-02-15","2003-06-30","2004-09-15","2005-01-30","2005-05-30","2005-10-30")
rdp <- c("", "<","<","","","")
dp <- c(0.02,0.01,0.005,NA,NA,NA)
@@ -508,9 +516,8 @@ tp <- c(NA,NA,NA,0.43,0.05,0.02)
DF <- data.frame(cdate,rdp,dp,rpp,pp,rtp,tp)
-data.table <- xtable(DF,
- caption="Example data")
-print(data.table, caption.placement="top",floating="FALSE",latex.environments=NULL,include.rownames=FALSE)
+xtable(DF, caption="Example data")
+
@
\end{center}
@@ -518,9 +525,9 @@ print(data.table, caption.placement="top",floating="FALSE",latex.environments=NU
The dataRetrieval package will \texttt{"}add up\texttt{"} all the values in a given row to form the total for that sample. Thus, you only want to enter data that should be added together. For example, we might know the value for dp on 5/30/2005, but we don't want to put it in the table because under the rules of this data set, we are not suppose to add it in to the values in 2005.
-For every sample, the EGRET package requires a pair of numbers to define an interval in which the true value lies (ConcLow and ConcHigh). In a simple non-censored case (the reported value is above the detection limit), ConcLow equals ConcHigh and the interval collapses down to a single point.In a simple censored case, the value might be reported as <0.2, then ConcLow=NA and ConcHigh=0.2. We use NA instead of 0 as a way to elegantly handle future logarithm calculations.
+For every sample, the EGRET package requires a pair of numbers to define an interval in which the true value lies (ConcLow and ConcHigh). In a simple non-censored case (the reported value is above the detection limit), ConcLow equals ConcHigh and the interval collapses down to a single point.In a simple censored case, the value might be reported as \verb@<@0.2, then ConcLow=NA and ConcHigh=0.2. We use NA instead of 0 as a way to elegantly handle future logarithm calculations.
-For the more complex example case, let us say dp is reported as <0.01 and pp is reported as 0.3. We know that the total must be at least 0.3 and could be as much as 0.31. Therefore, ConcLow=0.3 and ConcHigh=0.31. Another case would be if dp is reported as <0.005 and pp is reported <0.2. We know in this case that the true value could be as low as zero, but could be as high as 0.205. Therefore, in this case, ConcLow=NA and ConcHigh=0.205. The Sample dataframe for the example data is therefore:
+For the more complex example case, let us say dp is reported as \verb@<@0.01 and pp is reported as 0.3. We know that the total must be at least 0.3 and could be as much as 0.31. Therefore, ConcLow=0.3 and ConcHigh=0.31. Another case would be if dp is reported as \verb@<@0.005 and pp is reported \verb@<@0.2. We know in this case that the true value could be as low as zero, but could be as high as 0.205. Therefore, in this case, ConcLow=NA and ConcHigh=0.205. The Sample dataframe for the example data is therefore:
<<thirdExample,echo=FALSE>>=
getPreLoadedSampleData(DF)
@@ -528,6 +535,7 @@ getPreLoadedSampleData(DF)
@
\FloatBarrier
+
%------------------------------------------------------------
\subsection{User-Generated Data Files}
%------------------------------------------------------------
@@ -546,7 +554,7 @@ So, if you have a file called \texttt{"}ChoptankRiverFlow.txt\texttt{"} located
\begin{verbatim}
date Qdaily
10/1/1999 107
-10/2/1999 85
+10/2/1999 85
10/3/1999 76
10/4/1999 76
10/5/1999 113
@@ -558,10 +566,12 @@ The call to open this file, convert the flow to cubic meters per second, and pop
<<openDaily, eval = FALSE>>=
fileName <- "ChoptankRiverFlow.txt"
filePath <- "C:/RData/"
-Daily <- getDailyDataFromFile(filePath,fileName,separator="\t",interactive=FALSE)
+Daily <- getDailyDataFromFile(filePath,fileName,
+ separator="\t")
@
\FloatBarrier
+
%------------------------------------------------------------
\subsubsection{getSampleDataFromFile}
%------------------------------------------------------------
@@ -580,10 +590,12 @@ The call to open this file, and populate the Sample dataframe would be:
<<openSample, eval = FALSE>>=
fileName <- "ChoptankRiverNitrate.csv"
filePath <- "C:/RData/"
-Sample <- getSampleDataFromFile(filePath,fileName,separator=",",interactive=FALSE)
+Sample <- getSampleDataFromFile(filePath,fileName,
+ separator=",")
@
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Merge Report}
%------------------------------------------------------------
@@ -596,37 +608,28 @@ parameterCd <- "00631" # Nitrate
startDate <- "2000-01-01"
endDate <- "2013-01-01"
-Daily <- getDVData(siteNumber, "00060", startDate, endDate,interactive=FALSE)
-Sample <- getSampleData(siteNumber,parameterCd, startDate, endDate, interactive=FALSE)
+Daily <- getDVData(siteNumber, "00060", startDate, endDate)
+Sample <- getSampleData(siteNumber,parameterCd, startDate, endDate)
Sample <- mergeReport()
head(Sample)
@
\FloatBarrier
+
%------------------------------------------------------------
\subsection{EGRET Plots}
%------------------------------------------------------------
As has been mentioned, the data is specifically formatted to be used with the EGRET package. The EGRET package has powerful modeling capabilities using WRTDS, but also has a variety of graphing and tablular tools to explore the data without using the WRTDS algorithm. See the EGRET vignette, user guide, and/or wiki (\url{https://github.com/USGS-R/EGRET/wiki}) for detailed information. The following figure is an example of one of the plotting functions that can be used directly from the dataRetrieval dataframes.
-<<egretEx, echo=TRUE, eval=TRUE>>=
+<<egretEx, echo=TRUE, eval=TRUE, fig.cap="Default multiPlotDataOverview">>=
# Continuing Choptank example from the previous sections
library(EGRET)
multiPlotDataOverview()
@
-\begin{figure}[ht]
-\begin{center}
-
-<<label=figegretEx, fig=TRUE,echo=FALSE>>=
-<<egretEx>>
-@
-\end{center}
-\caption{Default multiPlotDataOverview}
-\label{fig:multiPlotDataOverview}
-\end{figure}
-
\clearpage
\appendix
+
%------------------------------------------------------------
\section{Getting Started in R}
\label{sec:appendix1}
@@ -651,7 +654,6 @@ To see the raw code for a particular code, type the name of the function:
removeDuplicates
@
-
%------------------------------------------------------------
\subsection{R User: Installing dataRetrieval}
%------------------------------------------------------------
@@ -662,29 +664,12 @@ install.packages("zoo")
install.packages("dataRetrieval", repos="http://usgs-r.github.com", type="source")
@
-It is a good idea to re-start the R enviornment after installing the package, especially if installing an updated version. Some users have found it necessary to delete the previous version's package folder before installing newer version of dataRetrieval. If you are experiencing issues after updating a package, trying deleting the package folder - the default location for Windows is something like this: C:/Users/userA/Documents/R/win-library/2.15/dataRetrieval, and the default for a Mac: /Users/userA/Library/R/2.15/library/dataRetrieval. Then, re-install the package using the directions above. Moving to CRAN should solve this problem.
+It is a good idea to re-start R after installing the package, especially if installing an updated version. Some users have found it necessary to delete the previous version's package folder before installing newer version of dataRetrieval. If you are experiencing issues after updating a package, trying deleting the package folder - the default location for Windows is something like this: C:/Users/userA/Documents/R/win-library/2.15/dataRetrieval, and the default for a Mac: /Users/userA/Library/R/2.15/library/dataRetrieval. Then, re-install the package using the directions above. Moving to CRAN should solve this problem.
After installing the package, you need to open the library each time you re-start R. This is done with the simple command:
<<openLibraryTest, eval=FALSE>>=
library(dataRetrieval)
@
-Using RStudio, you could alternatively click on the checkbox for dataRetrieval in the Packages window.
-
-%------------------------------------------------------------
-\subsection{R Developers: Installing dataRetrieval from gitHub}
-%------------------------------------------------------------
-Alternatively, R-developers can install the latest working version of dataRetrieval directly from gitHub using the devtools package (available on CRAN). Rtools (for Windows) and appropriate \LaTeX\ tools are required. Be aware that the version installed using this method isn't necessarily the same as the version in the stable release branch.
-
-
-<<gitInstal,eval = FALSE>>=
-library(devtools)
-install_github("dataRetrieval", "USGS-R")
-@
-To then open the library, simply type:
-
-<<openLibrary, eval=FALSE>>=
-library(dataRetrieval)
-@
%------------------------------------------------------------
\section{Columns Names}
@@ -696,11 +681,10 @@ library(dataRetrieval)
\label{sec:appendix2INFO}
%------------------------------------------------------------
-<<label=colNamesQW, echo=FALSE,results=tex>>=
+<<label=colNamesINFO, echo=FALSE,results='asis'>>=
infoDF <- data.frame(ColumnNames=names(INFO))
-data.table <- xtable(infoDF,
- caption="Column names in the INFO dataframe")
-print(data.table, caption.placement="top",floating="FALSE",latex.environments=NULL,include.rownames=FALSE,include.colnames=FALSE)
+xtable(infoDF, caption="Column names in the INFO dataframe")
+
@
\FloatBarrier
@@ -712,22 +696,17 @@ print(data.table, caption.placement="top",floating="FALSE",latex.environments=NU
There are 62 columns returned from the water quality portal.
-<<label=colNamesQW, echo=FALSE,results=tex>>=
+<<colNamesQW, echo=FALSE,results='asis'>>=
infoDF <- data.frame(ColumnNames=names(dissolvedNitrate[1:40]))
-data.table <- xtable(infoDF,
- caption="Column names in dissolvedNitrate")
-print(data.table, caption.placement="top",floating="FALSE",latex.environments=NULL,
- include.rownames=FALSE,include.colnames=FALSE)
+xtable(infoDF, caption="Column names in dissolvedNitrate")
+
@
\FloatBarrier
-<<label=colNamesQW2, echo=FALSE,results=tex>>=
+<<colNamesQW2, echo=FALSE,results='asis'>>=
infoDF <- data.frame(ColumnNames_Continued=names(dissolvedNitrate[41:62]))
-data.table <- xtable(infoDF,
- caption="Column names in dissolvedNitrate")
-print(data.table, caption.placement="top",floating="FALSE",latex.environments=NULL,
- include.rownames=FALSE,include.colnames=FALSE)
+xtable(infoDF, caption="Column names in dissolvedNitrate")
@
\clearpage
@@ -739,20 +718,21 @@ print(data.table, caption.placement="top",floating="FALSE",latex.environments=NU
There are a few steps that are required in order to create a table in a Microsoft product (Excel, Word, Powerpoint, etc.) from an R dataframe. There are certainly a variety of good methods, one of which is detailed here. The example we will step through here will be to create a table in Microsoft Word based on the dataframe tableData:
<<label=getSiteApp, echo=TRUE>>=
-ChoptankAvailableData <- getDataAvailability(siteNumber)
-ChoptankDailyData <- ChoptankAvailableData["dv" == ChoptankAvailableData$service,]
-ChoptankDailyData <- ChoptankDailyData["00003" == ChoptankDailyData$statCd,]
-pCodeINFO <- getMultipleParameterNames(ChoptankDailyData$parameter_cd, interactive=FALSE)
-ChoptankDailyData <- merge(ChoptankDailyData,pCodeINFO,by="parameter_cd")
+availableData <- getDataAvailability(siteNumber)
+dailyData <- availableData["dv" == availableData$service,]
+dailyData <- dailyData["00003" == dailyData$statCd,]
+pCodeINFO <- getMultipleParameterNames(dailyData$parameter_cd)
+dailyData <- merge(dailyData,pCodeINFO, by="parameter_cd")
-tableData <- with(ChoptankDailyData,
+tableData <- with(dailyData,
data.frame(
- shortName=srsname,
- Start=startDate,
- End=endDate,
- Count=count,
- Units=parameter_units)
+ shortName=srsname,
+ Start=startDate,
+ End=endDate,
+ Count=count,
+ Units=parameter_units)
)
+tableData
@
First, save the dataframe as a tab delimited file (you don't want to use comma delimited because there are commas in some of the data elements):
@@ -766,7 +746,7 @@ write.table(tableData, file="tableData.tsv",sep="\t",
This will save a file in your working directory called tableData.tsv. You can see your working directory by typing getwd() in the R console. Opening the file in a general-purpose text editor, you should see the following:
\begin{verbatim}
-shortName Start End Count Units
+shortName Start End Count Units
Temperature, water 2010-10-01 2012-06-24 575 deg C
Stream flow, mean. daily 1948-01-01 2013-03-13 23814 cfs
Specific conductance 2010-10-01 2012-06-24 551 uS/cm @25C
@@ -797,6 +777,7 @@ From Excel, it is simple to copy and paste the tables in other Microsoft product
\end{figure}
\clearpage
+
%------------------------------------------------------------
% BIBLIO
%------------------------------------------------------------
diff --git a/vignettes/dataRetrieval.log b/vignettes/dataRetrieval.log
index 910ea85734d4b4d6b7164c1816e2976ce2affc1a..44cb50cce9584a679e7239c09aa9183874a946f9 100644
--- a/vignettes/dataRetrieval.log
+++ b/vignettes/dataRetrieval.log
@@ -1,4 +1,4 @@
-This is pdfTeX, Version 3.1415926-2.3-1.40.12 (MiKTeX 2.9) (preloaded format=pdflatex 2012.1.6) 25 APR 2013 12:09
+This is pdfTeX, Version 3.1415926-2.3-1.40.12 (MiKTeX 2.9) (preloaded format=pdflatex 2012.1.6) 17 JUN 2013 15:35
entering extended mode
**dataRetrieval.tex
(D:\LADData\RCode\dataRetrieval\vignettes\dataRetrieval.tex
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+)
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+File: graphics.cfg 2007/01/18 v1.5 graphics configuration of teTeX/TeXLive
+)
+Package graphics Info: Driver file: pdftex.def on input line 91.
+
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+)
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+)
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Package: amsmath 2013/01/14 v2.14 AMS math features
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For additional information on amsmath, use the `?' option.
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Package: amsopn 1999/12/14 v2.01 operator names
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LaTeX Info: Redefining \[ on input line 2665.
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@@ -100,8 +151,8 @@ Package: hobsub-hyperref 2011/04/23 v1.4 Bundle oberdiek, subset hyperref (HO)
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@@ -135,24 +186,20 @@ Package: atbegshi 2011/01/30 v1.15 At begin shipout hook (HO)
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+ []
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+30 3651 mg/l[]
+ []
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+Weighted Re-gres-sions on
+ []
+
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diff --git a/vignettes/dataRetrieval.pdf b/vignettes/dataRetrieval.pdf
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diff --git a/vignettes/dataRetrieval.synctex.gz b/vignettes/dataRetrieval.synctex.gz
index 52ad2f678d3fda6fa8cf5b0a7f254641143af314..3f2d8cbc483300a977cc61b7bd6b9509cb34a01e 100644
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diff --git a/vignettes/dataRetrieval.tex b/vignettes/dataRetrieval.tex
index cb9accedf6a83ab368ec8057362768a1c7478ba5..4a885515a876d8e0a71f64c553a79b56f09dda70 100644
--- a/vignettes/dataRetrieval.tex
+++ b/vignettes/dataRetrieval.tex
@@ -1,10 +1,65 @@
%\VignetteIndexEntry{Introduction to the dataRetrieval package}
+%\VignetteEngine{knitr::knitr}
%\VignetteDepends{}
-%\VignetteSuggests{}
-%\VignetteImports{}
-%\VignettePackage{}
-
-\documentclass[a4paper,11pt]{article}
+%\VignetteSuggests{xtable,EGRET}
+%\VignetteImports{zoo, XML, RCurl}
+%\VignettePackage{dataRetrieval}
+
+\documentclass[a4paper,11pt]{article}\usepackage{graphicx, color}
+%% maxwidth is the original width if it is less than linewidth
+%% otherwise use linewidth (to make sure the graphics do not exceed the margin)
+\makeatletter
+\def\maxwidth{ %
+ \ifdim\Gin@nat@width>\linewidth
+ \linewidth
+ \else
+ \Gin@nat@width
+ \fi
+}
+\makeatother
+
+\definecolor{fgcolor}{rgb}{0.2, 0.2, 0.2}
+\newcommand{\hlnumber}[1]{\textcolor[rgb]{0,0,0}{#1}}%
+\newcommand{\hlfunctioncall}[1]{\textcolor[rgb]{0.501960784313725,0,0.329411764705882}{\textbf{#1}}}%
+\newcommand{\hlstring}[1]{\textcolor[rgb]{0.6,0.6,1}{#1}}%
+\newcommand{\hlkeyword}[1]{\textcolor[rgb]{0,0,0}{\textbf{#1}}}%
+\newcommand{\hlargument}[1]{\textcolor[rgb]{0.690196078431373,0.250980392156863,0.0196078431372549}{#1}}%
+\newcommand{\hlcomment}[1]{\textcolor[rgb]{0.180392156862745,0.6,0.341176470588235}{#1}}%
+\newcommand{\hlroxygencomment}[1]{\textcolor[rgb]{0.43921568627451,0.47843137254902,0.701960784313725}{#1}}%
+\newcommand{\hlformalargs}[1]{\textcolor[rgb]{0.690196078431373,0.250980392156863,0.0196078431372549}{#1}}%
+\newcommand{\hleqformalargs}[1]{\textcolor[rgb]{0.690196078431373,0.250980392156863,0.0196078431372549}{#1}}%
+\newcommand{\hlassignement}[1]{\textcolor[rgb]{0,0,0}{\textbf{#1}}}%
+\newcommand{\hlpackage}[1]{\textcolor[rgb]{0.588235294117647,0.709803921568627,0.145098039215686}{#1}}%
+\newcommand{\hlslot}[1]{\textit{#1}}%
+\newcommand{\hlsymbol}[1]{\textcolor[rgb]{0,0,0}{#1}}%
+\newcommand{\hlprompt}[1]{\textcolor[rgb]{0.2,0.2,0.2}{#1}}%
+
+\usepackage{framed}
+\makeatletter
+\newenvironment{kframe}{%
+ \def\at@end@of@kframe{}%
+ \ifinner\ifhmode%
+ \def\at@end@of@kframe{\end{minipage}}%
+ \begin{minipage}{\columnwidth}%
+ \fi\fi%
+ \def\FrameCommand##1{\hskip\@totalleftmargin \hskip-\fboxsep
+ \colorbox{shadecolor}{##1}\hskip-\fboxsep
+ % There is no \\@totalrightmargin, so:
+ \hskip-\linewidth \hskip-\@totalleftmargin \hskip\columnwidth}%
+ \MakeFramed {\advance\hsize-\width
+ \@totalleftmargin\z@ \linewidth\hsize
+ \@setminipage}}%
+ {\par\unskip\endMakeFramed%
+ \at@end@of@kframe}
+\makeatother
+
+\definecolor{shadecolor}{rgb}{.97, .97, .97}
+\definecolor{messagecolor}{rgb}{0, 0, 0}
+\definecolor{warningcolor}{rgb}{1, 0, 1}
+\definecolor{errorcolor}{rgb}{1, 0, 0}
+\newenvironment{knitrout}{}{} % an empty environment to be redefined in TeX
+
+\usepackage{alltt}
\usepackage{amsmath}
\usepackage{times}
@@ -12,10 +67,12 @@
\usepackage[numbers, round]{natbib}
\usepackage[american]{babel}
\usepackage{authblk}
-\usepackage{footnote}
+\usepackage{subfig}
\usepackage{placeins}
+\usepackage{footnote}
+\usepackage{tabularx}
\renewcommand\Affilfont{\itshape\small}
-\usepackage{Sweave}
+
\renewcommand{\topfraction}{0.85}
\renewcommand{\textfraction}{0.1}
\usepackage{graphicx}
@@ -40,9 +97,14 @@
\newcommand{\Rexpression}[1]{\texttt{#1}}
\newcommand{\Rmethod}[1]{{\texttt{#1}}}
\newcommand{\Rfunarg}[1]{{\texttt{#1}}}
+\IfFileExists{upquote.sty}{\usepackage{upquote}}{}
\begin{document}
-\input{dataRetrieval-concordance}
+
+
+
+
+
%------------------------------------------------------------
\title{The dataRetrieval R package}
@@ -53,6 +115,9 @@
+
+
+
\maketitle
\tableofcontents
@@ -77,55 +142,59 @@ In this section, we will run through 5 examples, documenting how to get raw data
%------------------------------------------------------------
The United States Geological Survey organizes their hydrological data in standard structure. Streamgages are located throughout the United States, and each streamgage has a unique ID. Often (but not always), these ID's are 8 digits. The first step to finding data is discoving this 8-digit ID. One potential tool for discovering data is Environmental Data Discovery and Transformation (EnDDaT): \url{http://cida.usgs.gov/enddat/}. Follow the example on the EnDDaT web page to learn how to discover USGS stations and available data from any location in the United States.
-Once the site-ID is known, the next required input for USGS data retrievals is the 'parameter code'. This is a 5-digit code that specifies what measured paramater is being requested. A complete list of possible USGS parameter codes can be found at:
-
-\url{http://nwis.waterdata.usgs.gov/usa/nwis/pmcodes?radio_pm_search=param_group&pm_group=All+--+include+all+parameter+groups&pm_search=&casrn_search=&srsname_search=&format=html_table&show=parameter_group_nm&show=parameter_nm&show=casrn&show=srsname&show=parameter_units}
+Once the site-ID is known, the next required input for USGS data retrievals is the 'parameter code'. This is a 5-digit code that specifies what measured paramater is being requested. A complete list of possible USGS parameter codes can be found at \url{http://go.usa.gov/bVDz}.
Not every station will measure all parameters. A short list of commonly measured parameters is shown in Table \ref{tab:params}.
-
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:34 2013
-\begin{table}[!ht]
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:34:54 2013
+\begin{table}[ht]
\centering
-\caption{Common USGS Parameter Codes}
-\label{tab:params}
-\begin{tabular}{ll}
+\begin{tabular}{rll}
\hline
-pCode & shortName \\
+ & pCode & shortName \\
\hline
-00060 & Discharge [cfs] \\
- 00065 & Gage height [ft] \\
- 00010 & Temperature [C] \\
- 00045 & Precipitation [in] \\
- 00400 & pH \\
+1 & 00060 & Discharge [cfs] \\
+ 2 & 00065 & Gage height [ft] \\
+ 3 & 00010 & Temperature [C] \\
+ 4 & 00045 & Precipitation [in] \\
+ 5 & 00400 & pH \\
\hline
\end{tabular}
+\caption{Common USGS Parameter Codes}
+\label{tab:params}
\end{table}
+
+
+
For real-time data, the parameter code and site ID will suffice. For most variables that are measured on a continuous basis, the USGS stores the historical data as daily values. These daily values may be in the form of statistics such as the daily mean values, but they can also include daily maximums, minimums or medians. These different statistics are specified by a 5-digit \texttt{"}stat code\texttt{"}. A complete list of stat codes can be found here:
\url{http://nwis.waterdata.usgs.gov/nwis/help/?read_file=stat&format=table}
Some common stat codes are shown in Table \ref{tab:stat}.
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:34 2013
-\begin{table}[!ht]
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:34:54 2013
+\begin{table}[ht]
\centering
-\caption{Commonly found USGS Stat Codes}
-\label{tab:stat}
-\begin{tabular}{ll}
+\begin{tabular}{rll}
\hline
-StatCode & shortName \\
+ & StatCode & shortName \\
\hline
-00001 & Maximum \\
- 00002 & Minimum \\
- 00003 & Mean \\
- 00008 & Median \\
+1 & 00001 & Maximum \\
+ 2 & 00002 & Minimum \\
+ 3 & 00003 & Mean \\
+ 4 & 00008 & Median \\
\hline
\end{tabular}
+\caption{Commonly found USGS Stat Codes}
+\label{tab:stat}
\end{table}
+
+
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Site Information}
\label{sec:usgsSite}
@@ -138,139 +207,169 @@ StatCode & shortName \\
Use the getSiteFileData function to obtain all of the information available for a particular USGS site such as full station name, drainage area, latitude, and longitude:
-\begin{Schunk}
-\begin{Sinput}
-> library(dataRetrieval)
-> # Site ID for Choptank River near Greensboro, MD
-> siteNumber <- "01491000"
-> ChoptankInfo <- getSiteFileData(siteNumber)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{library}(dataRetrieval)
+\hlcomment{# Site ID for Choptank River near Greensboro, MD}
+siteNumber <- \hlstring{"01491000"}
+ChoptankInfo <- \hlfunctioncall{getSiteFileData}(siteNumber)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
A list of the available columns are found in Appendix \ref{sec:appendix2INFO}: INFO dataframe. Pulling out a specific example piece of information, in this case station name can be done as follows:
-\begin{Schunk}
-\begin{Sinput}
-> ChoptankInfo$station.nm
-\end{Sinput}
-\begin{Soutput}
-[1] "CHOPTANK RIVER NEAR GREENSBORO, MD"
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+ChoptankInfo$station.nm
+\end{alltt}
+\begin{verbatim}
+## [1] "CHOPTANK RIVER NEAR GREENSBORO, MD"
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
Site information is obtained from \url{http://waterservices.usgs.gov/rest/Site-Test-Tool.html}
\FloatBarrier
+
%------------------------------------------------------------
\subsubsection{getDataAvailability}
\label{sec:usgsDataAvailability}
%------------------------------------------------------------
To find out the available data at a particular USGS site, including measured parameters, period of record, and number of samples (count), use the getDataAvailability function:
-\begin{Schunk}
-\begin{Sinput}
-> # Continuing from the previous example:
-> ChoptankAvailableData <- getDataAvailability(siteNumber)
-> head(ChoptankAvailableData)
-\end{Sinput}
-\begin{Soutput}
- parameter_cd statCd startDate endDate count service
-2 00010 00001 1988-10-01 2012-05-09 894 dv
-3 00010 00002 2010-10-01 2012-05-09 529 dv
-4 00010 00003 2010-10-01 2012-05-09 529 dv
-5 00060 00003 1948-01-01 2013-04-24 23856 dv
-6 00095 00001 2010-10-01 2012-05-09 527 dv
-7 00095 00002 2010-10-01 2012-05-09 527 dv
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlcomment{# Continuing from the previous example:}
+ChoptankAvailableData <- \hlfunctioncall{getDataAvailability}(siteNumber)
+\hlfunctioncall{head}(ChoptankAvailableData)
+\end{alltt}
+\begin{verbatim}
+## parameter_cd statCd startDate endDate count service
+## 2 00010 00001 1988-10-01 2012-05-09 894 dv
+## 3 00010 00002 2010-10-01 2012-05-09 529 dv
+## 4 00010 00003 2010-10-01 2012-05-09 529 dv
+## 5 00060 00003 1948-01-01 2013-06-16 23908 dv
+## 6 00095 00001 2010-10-01 2012-05-09 527 dv
+## 7 00095 00002 2010-10-01 2012-05-09 527 dv
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
There is an additional argument to the getDataAvailability called longNames, which defaults to FALSE. Setting longNames to TRUE will cause the function to make a web service call for each parameter and return expanded information on that parameter. Currently, this is a very slow process because each parameter code makes a unique web service call. If the site does not have many measured parameters, setting longNames to TRUE is reasonable.
It is also possible to only request parameter information for a subset of variables. In the following example, we retrieve just the daily mean parameter information from the Choptank data availability dataframe (excluding all unit value and water quality values). getMultipleParameterNames is the function that is embedded in the getDataAvailability, but here can be used as a standalone function.
-\begin{Schunk}
-\begin{Sinput}
-> # Continuing from the previous example:
-> # This pulls out just the daily data:
-> ChoptankDailyData <- subset(ChoptankAvailableData,"dv" == service)
-> # This pulls out the mean:
-> ChoptankDailyData <- subset(ChoptankDailyData,"00003" == statCd)
-> #Now, make a call to get all of the parameter information:
-> pCodeINFO <- getMultipleParameterNames(ChoptankDailyData$parameter_cd)
-\end{Sinput}
-\begin{Soutput}
-Percent complete:
-20 40 60 80 100
-\end{Soutput}
-\begin{Sinput}
-> #Merge the available dataframe with the parameter information dataframe:
-> ChoptankDailyData <- merge(ChoptankDailyData,pCodeINFO,by="parameter_cd")
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlcomment{# Continuing from the previous example:}
+\hlcomment{# This pulls out just the daily data:}
+ChoptankDailyData <- \hlfunctioncall{subset}(ChoptankAvailableData,
+ \hlstring{"dv"} == service)
+
+\hlcomment{# This pulls out the mean:}
+ChoptankDailyData <- \hlfunctioncall{subset}(ChoptankDailyData,
+ \hlstring{"00003"} == statCd)
+
+\hlcomment{#Now, make a call to get all of the parameter information:}
+pCodeINFO <- \hlfunctioncall{getMultipleParameterNames}(
+ ChoptankDailyData$parameter_cd)
+\end{alltt}
+\begin{verbatim}
+## Percent complete:
+## 20 40 60 80 100
+\end{verbatim}
+\begin{alltt}
+
+\hlcomment{#Merge the available dataframes:}
+ChoptankDailyData <- \hlfunctioncall{merge}(ChoptankDailyData,
+ pCodeINFO,by=\hlstring{"parameter_cd"})
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
The daily data at the Choptank River site can be displayed in a \LaTeX table using the xtable package. See Appendix \ref{app:createWordTable} for instructions on converting an R dataframe to a table in Microsoft Excel or Word.
-\begin{Schunk}
-\begin{Sinput}
-> tableData <- with(ChoptankDailyData,
- data.frame(shortName=srsname,
- Start=as.character(startDate),
- End=as.character(endDate),
- Count=as.character(count),
- Units=parameter_units)
- )
-> data.table <- xtable(tableData,label="tab:gda",
- caption="Daily mean data availabile at the Choptank River")
-> print(data.table,
- caption.placement="top",include.rownames=FALSE)
-\end{Sinput}
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:39 2013
+\begin{kframe}
+\begin{alltt}
+tableData <- \hlfunctioncall{with}(ChoptankDailyData,
+ \hlfunctioncall{data.frame}(shortName=srsname,
+ Start=\hlfunctioncall{as.character}(startDate),
+ End=\hlfunctioncall{as.character}(endDate),
+ Count=\hlfunctioncall{as.character}(count),
+ Units=parameter_units)
+ )
+
+
+\hlfunctioncall{xtable}(tableData,label=\hlstring{"tab:gda"},
+ caption=\hlstring{"Daily mean data availabile at the Choptank River"})
+\end{alltt}
+\end{kframe}% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:00 2013
\begin{table}[ht]
\centering
-\caption{Daily mean data availabile at the Choptank River}
-\label{tab:gda}
-\begin{tabular}{lllll}
+\begin{tabular}{rlllll}
\hline
-shortName & Start & End & Count & Units \\
+ & shortName & Start & End & Count & Units \\
\hline
-Temperature, water & 2010-10-01 & 2012-05-09 & 529 & deg C \\
- Stream flow, mean. daily & 1948-01-01 & 2013-04-24 & 23856 & cfs \\
- Specific conductance & 2010-10-01 & 2012-05-09 & 527 & uS/cm @25C \\
- Suspended sediment concentration (SSC) & 1980-10-01 & 1991-09-30 & 3651 & mg/l \\
- Suspended sediment discharge & 1980-10-01 & 1991-09-30 & 3652 & tons/day \\
+1 & Temperature, water & 2010-10-01 & 2012-05-09 & 529 & deg C \\
+ 2 & Stream flow, mean. daily & 1948-01-01 & 2013-06-16 & 23908 & cfs \\
+ 3 & Specific conductance & 2010-10-01 & 2012-05-09 & 527 & uS/cm @25C \\
+ 4 & Suspended sediment concentration (SSC) & 1980-10-01 & 1991-09-30 & 3651 & mg/l \\
+ 5 & Suspended sediment discharge & 1980-10-01 & 1991-09-30 & 3652 & tons/day \\
\hline
\end{tabular}
-\end{table}\end{Schunk}
+\caption{Daily mean data availabile at the Choptank River}
+\label{tab:gda}
+\end{table}
+
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Parameter Information}
\label{sec:usgsParams}
%------------------------------------------------------------
To obtain all of the available information concerning a measured parameter, use the getParameterInfo function:
-\begin{Schunk}
-\begin{Sinput}
-> # Using defaults:
-> parameterCd <- "00618"
-> parameterINFO <- getParameterInfo(parameterCd)
-> colnames(parameterINFO)
-\end{Sinput}
-\begin{Soutput}
-[1] "parameter_cd" "parameter_group_nm" "parameter_nm"
-[4] "casrn" "srsname" "parameter_units"
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlcomment{# Using defaults:}
+parameterCd <- \hlstring{"00618"}
+parameterINFO <- \hlfunctioncall{getParameterInfo}(parameterCd)
+\hlfunctioncall{colnames}(parameterINFO)
+\end{alltt}
+\begin{verbatim}
+## [1] "parameter_cd" "parameter_group_nm"
+## [3] "parameter_nm" "casrn"
+## [5] "srsname" "parameter_units"
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
Pulling out a specific example piece of information, in this case parameter name can be done as follows:
-\begin{Schunk}
-\begin{Sinput}
-> parameterINFO$parameter_nm
-\end{Sinput}
-\begin{Soutput}
-[1] "Nitrate, water, filtered, milligrams per liter as nitrogen"
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+parameterINFO$parameter_nm
+\end{alltt}
+\begin{verbatim}
+## [1] "Nitrate, water, filtered, milligrams per liter as nitrogen"
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
Parameter information is obtained from \url{http://nwis.waterdata.usgs.gov/nwis/pmcodes/}
\FloatBarrier
%------------------------------------------------------------
@@ -281,122 +380,146 @@ To obtain historic daily records of USGS data, use the retrieveNWISData function
The dates (start and end) need to be in the format \texttt{"}YYYY-MM-DD\texttt{"} (note: the user does need to include the quotes). Setting the start date to \texttt{"}\texttt{"} will indicate to the program to ask for the earliest date, setting the end date to \texttt{"}\texttt{"} will ask for the latest available date.
-\begin{Schunk}
-\begin{Sinput}
-> # Continuing with our Choptank River example
-> parameterCd <- "00060" # Discharge (cfs)
-> startDate <- "" # Will request earliest date
-> endDate <- "" # Will request latest date
-> discharge <- retrieveNWISData(siteNumber, parameterCd, startDate, endDate)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+
+\hlcomment{# Continuing with our Choptank River example}
+parameterCd <- \hlstring{"00060"} # \hlfunctioncall{Discharge} (cfs)
+startDate <- \hlstring{""} # Will request earliest date
+endDate <- \hlstring{""} # Will request latest date
+
+discharge <- \hlfunctioncall{retrieveNWISData}(siteNumber,
+ parameterCd, startDate, endDate)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
The variable datetime is automatically imported as a Date. Each requested parameter has a value and remark code column. The names of these columns depend on the requested parameter and stat code combinations. USGS remark codes are often \texttt{"}A\texttt{"} (approved for publication) or \texttt{"}P\texttt{"} (provisional data subject to revision). A more complete list of remark codes can be found here:
\url{http://waterdata.usgs.gov/usa/nwis/help?codes_help}
Another example that doesn't use the defaults would be a request for mean and maximum daily temperature and discharge in early 2012:
-\begin{Schunk}
-\begin{Sinput}
-> parameterCd <- c("00010","00060") # Temperature and discharge
-> statCd <- c("00001","00003") # Mean and maximum
-> startDate <- "2012-01-01"
-> endDate <- "2012-06-30"
-> temperatureAndFlow <- retrieveNWISData(siteNumber, parameterCd,
- startDate, endDate, StatCd=statCd,interactive=FALSE)
->
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+
+parameterCd <- \hlfunctioncall{c}(\hlstring{"00010"},\hlstring{"00060"}) # Temperature and discharge
+statCd <- \hlfunctioncall{c}(\hlstring{"00001"},\hlstring{"00003"}) # Mean and maximum
+startDate <- \hlstring{"2012-01-01"}
+endDate <- \hlstring{"2012-06-30"}
+
+temperatureAndFlow <- \hlfunctioncall{retrieveNWISData}(siteNumber, parameterCd,
+ startDate, endDate, StatCd=statCd)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
Daily data is pulled from \url{http://waterservices.usgs.gov/rest/DV-Test-Tool.html}.
-An example of plotting the above data (Figure \ref{fig:TD}):
-
-\begin{Schunk}
-\begin{Sinput}
-> colnames <- names(temperatureAndFlow)
-> with(temperatureAndFlow, plot(
- get(colnames[3]), get(colnames[6]),
- xlab="Date",ylab="Temperature [C]"
- ))
-> par(new=TRUE)
-> with(temperatureAndFlow, plot(
- get(colnames[3]), get(colnames[8]),
- col="red",type="l",xaxt="n",yaxt="n",xlab="",ylab="",axes=FALSE
- ))
-> axis(4,col="red",col.axis="red")
-> mtext("Discharge [cfs]",side=4,line=3,col="red")
-> title(paste(ChoptankInfo$station.nm,"2012",sep=" "))
-\end{Sinput}
-\end{Schunk}
-
-
-\begin{figure}
-\begin{center}
-\includegraphics{dataRetrieval-fig1}
-\end{center}
-\caption{Temperature and discharge plot of Choptank River in 2012.}
-\label{fig:TD}
+An example of plotting the above data (Figure \ref{fig:getNWIStemperaturePlot}):
+
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{par}(mar=\hlfunctioncall{c}(5,5,5,5))
+colnames <- \hlfunctioncall{names}(temperatureAndFlow)
+\hlfunctioncall{with}(temperatureAndFlow, \hlfunctioncall{plot}(
+ \hlfunctioncall{get}(colnames[3]), \hlfunctioncall{get}(colnames[6]),
+ xlab=\hlstring{"Date"},ylab=\hlstring{"Temperature [C]"}
+ ))
+\hlfunctioncall{par}(new=TRUE)
+\hlfunctioncall{with}(temperatureAndFlow, \hlfunctioncall{plot}(
+ \hlfunctioncall{get}(colnames[3]), \hlfunctioncall{get}(colnames[8]),
+ col=\hlstring{"red"},type=\hlstring{"l"},xaxt=\hlstring{"n"},yaxt=\hlstring{"n"},xlab=\hlstring{""},ylab=\hlstring{""},axes=FALSE
+ ))
+\hlfunctioncall{axis}(4,col=\hlstring{"red"},col.axis=\hlstring{"red"})
+\hlfunctioncall{mtext}(\hlstring{"Discharge [cfs]"},side=4,line=3,col=\hlstring{"red"})
+\hlfunctioncall{title}(\hlfunctioncall{paste}(ChoptankInfo$station.nm,\hlstring{"2012"},sep=\hlstring{" "}))
+\end{alltt}
+\end{kframe}\begin{figure}[]
+
+\includegraphics[width=\maxwidth]{figure/getNWIStemperaturePlot} \caption[Temperature and discharge plot of Choptank River in 2012]{Temperature and discharge plot of Choptank River in 2012.\label{fig:getNWIStemperaturePlot}}
\end{figure}
+\end{knitrout}
+
+
+
There are occasions where NWIS values are not reported as numbers, instead there might be text describing a certain event such as \texttt{"}Ice\texttt{"}. Any value that cannot be converted to a number will be reported as NA in this package.
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Unit Values}
\label{sec:usgsRT}
%------------------------------------------------------------
Any data that are collected at regular time intervals (such as 15-minute or hourly) are known as \texttt{"}Unit Values\texttt{"} - many of these are delivered on a real time basis and very recent data (even less than an hour old in many cases) are available through the function retrieveUnitNWISData. Some of these Unit Values are available for the past several years, and some are only available for a recent time period such as 120 days or a year. Here is an example of a retrieval of such data.
-\begin{Schunk}
-\begin{Sinput}
-> parameterCd <- "00060" # Discharge (cfs)
-> startDate <- "2012-05-12"
-> # or use (yesterday): startDate <- as.character(Sys.Date()-1)
-> endDate <- "2012-05-13"
-> # or use (today): endDate <- as.character(Sys.Date())
-> dischargeToday <- retrieveUnitNWISData(siteNumber, parameterCd,
- startDate, endDate)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+
+parameterCd <- \hlstring{"00060"} # \hlfunctioncall{Discharge} (cfs)
+startDate <- \hlstring{"2012-05-12"}
+endDate <- \hlstring{"2012-05-13"}
+dischargeToday <- \hlfunctioncall{retrieveUnitNWISData}(siteNumber, parameterCd,
+ startDate, endDate)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
Which produces the following dataframe:
-\begin{Schunk}
-\begin{Soutput}
- agency site dateTime X02_00060_00011 X02_00060_00011_cd
-1 USGS 01491000 2012-05-12 00:00:00 83 A
-2 USGS 01491000 2012-05-12 00:15:00 83 A
-3 USGS 01491000 2012-05-12 00:30:00 83 A
-4 USGS 01491000 2012-05-12 00:45:00 83 A
-5 USGS 01491000 2012-05-12 01:00:00 85 A
-6 USGS 01491000 2012-05-12 01:15:00 83 A
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{verbatim}
+## agency site dateTime X02_00060_00011
+## 1 USGS 01491000 2012-05-12 00:00:00 83
+## 2 USGS 01491000 2012-05-12 00:15:00 83
+## 3 USGS 01491000 2012-05-12 00:30:00 83
+## 4 USGS 01491000 2012-05-12 00:45:00 83
+## 5 USGS 01491000 2012-05-12 01:00:00 85
+## 6 USGS 01491000 2012-05-12 01:15:00 83
+## X02_00060_00011_cd
+## 1 A
+## 2 A
+## 3 A
+## 4 A
+## 5 A
+## 6 A
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
Note that time now becomes important, so the variable datetime is a POSIXct, and the time zone is included in a separate column. Data is pulled from \url{http://waterservices.usgs.gov/rest/IV-Test-Tool.html}. There are occasions where NWIS values are not reported as numbers, instead a common example is \texttt{"}Ice\texttt{"}. Any value that cannot be converted to a number will be reported as NA in this package.
-A simple plotting example is shown in Figure \ref{fig:RT}:
-\begin{Schunk}
-\begin{Sinput}
-> colnames <- names(dischargeToday)
-> with(dischargeToday, plot(
- get(colnames[3]), get(colnames[4]),
- ylab="Discharge [cfs]",xlab=""
- ))
-> title(ChoptankInfo$station.nm)
->
-\end{Sinput}
-\end{Schunk}
+A simple plotting example is shown in Figure \ref{fig:getNWISUnitPlot}:
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+colnames <- \hlfunctioncall{names}(dischargeToday)
+\hlfunctioncall{with}(dischargeToday, \hlfunctioncall{plot}(
+ dateTime, \hlfunctioncall{get}(colnames[4]),
+ ylab=\hlstring{"Discharge [cfs]"},xlab=\hlstring{""}
+ ))
+\hlfunctioncall{title}(ChoptankInfo$station.nm)
+\end{alltt}
+\end{kframe}\begin{figure}[]
+
+\includegraphics[width=\maxwidth]{figure/getNWISUnitPlot} \caption[Real-time discharge plot of Choptank River from May 12-13, 2012]{Real-time discharge plot of Choptank River from May 12-13, 2012.\label{fig:getNWISUnitPlot}}
+\end{figure}
+
+
+\end{knitrout}
+
\newpage
-\begin{figure}
-\begin{center}
-\includegraphics{dataRetrieval-fig2}
-\end{center}
-\caption{Real-time discharge plot of Choptank River from May 12-13, 2012.}
-\label{fig:RT}
-\end{figure}
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Water Quality Values}
\label{sec:usgsWQP}
@@ -404,67 +527,84 @@ A simple plotting example is shown in Figure \ref{fig:RT}:
To get USGS water quality data from water samples collected at the streamgage (as distinct from unit values collected through some type of automatic monitor) we can use the Water Quality Data Portal: \url{http://www.waterqualitydata.us/}. The raw data are obtained from the function getRawQWData, with the similar input arguments: siteNumber, parameterCd, startDate, endDate, and interactive. The difference is in parameterCd, in this function multiple parameters can be queried using a \texttt{"};\texttt{"} separator, and setting parameterCd to \texttt{"}\texttt{"} will return all of the measured observations. The raw data can be overwelming (see Appendix \ref{sec:appendix2WQP}), a simplified version of the data can be obtained using getQWData.There is a large amount of data returned for each observation.
-\begin{Schunk}
-\begin{Sinput}
-> # Dissolved Nitrate parameter codes:
-> parameterCd <- c("00618","71851")
-> startDate <- "1979-10-11"
-> endDate <- "2012-12-18"
-> dissolvedNitrate <- getRawQWData(siteNumber, parameterCd,
- startDate, endDate)
-> dissolvedNitrateSimple <- getQWData(siteNumber, parameterCd,
- startDate, endDate)
-> names(dissolvedNitrateSimple)
-\end{Sinput}
-\begin{Soutput}
-[1] "dateTime" "qualifier.71851" "value.71851" "qualifier.00618"
-[5] "value.00618"
-\end{Soutput}
-\end{Schunk}
-Note that in this dataframe, datetime is imported as Dates (no times are included), and the qualifier is either blank or \texttt{"}\verb@<@\texttt{"} signifying a censored value. A plotting example is shown in Figure \ref{fig:nitrate}.
-
-\begin{Schunk}
-\begin{Sinput}
-> with(dissolvedNitrateSimple, plot(
- dateTime, value.00618,
- xlab="Date",ylab = paste(parameterINFO$srsname,
- "[",parameterINFO$parameter_units,"]")
- ))
-> title(ChoptankInfo$station.nm)
-\end{Sinput}
-\end{Schunk}
-
-\begin{figure}
-\begin{center}
-\includegraphics{dataRetrieval-fig3}
-\end{center}
-\caption{Nitrate plot of Choptank River.}
-\label{fig:nitrate}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+
+\hlcomment{# Dissolved Nitrate parameter codes:}
+parameterCd <- \hlfunctioncall{c}(\hlstring{"00618"},\hlstring{"71851"})
+startDate <- \hlstring{"1979-10-11"}
+endDate <- \hlstring{"2012-12-18"}
+
+dissolvedNitrate <- \hlfunctioncall{getRawQWData}(siteNumber, parameterCd,
+ startDate, endDate)
+
+dissolvedNitrateSimple <- \hlfunctioncall{getQWData}(siteNumber, parameterCd,
+ startDate, endDate)
+\hlfunctioncall{names}(dissolvedNitrateSimple)
+\end{alltt}
+\begin{verbatim}
+## [1] "dateTime" "qualifier.00618" "value.00618"
+## [4] "qualifier.71851" "value.71851"
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
+Note that in this dataframe, datetime is imported as Dates (no times are included), and the qualifier is either blank or \texttt{"}\verb@<@\texttt{"} signifying a censored value. A plotting example is shown in Figure \ref{fig:getQWtemperaturePlot}.
+
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{with}(dissolvedNitrateSimple, \hlfunctioncall{plot}(
+ dateTime, value.00618,
+ xlab=\hlstring{"Date"},ylab = \hlfunctioncall{paste}(parameterINFO$srsname,
+ \hlstring{"["},parameterINFO$parameter_units,\hlstring{"]"})
+ ))
+\hlfunctioncall{title}(ChoptankInfo$station.nm)
+\end{alltt}
+\end{kframe}\begin{figure}[]
+
+\includegraphics[width=\maxwidth]{figure/getQWtemperaturePlot} \caption[Nitrate plot of Choptank River]{Nitrate plot of Choptank River.\label{fig:getQWtemperaturePlot}}
\end{figure}
+
+\end{knitrout}
+
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{STORET Water Quality Retrievals}
\label{sec:usgsSTORET}
%------------------------------------------------------------
There are additional data sets available on the Water Quality Data Portal (\url{http://www.waterqualitydata.us/}). These data sets can be housed in either the STORET (data from EPA) or NWIS database. Since STORET does not use USGS parameter codes, a \texttt{"}characteristic name\texttt{"} must be supplied. The following example retrieves specific conductance from a DNR site in Wisconsin.
-\begin{Schunk}
-\begin{Sinput}
-> specificCond <- getWQPData('WIDNR_WQX-10032762',
- 'Specific conductance', '', '')
-> head(specificCond)
-\end{Sinput}
-\begin{Soutput}
- dateTime qualifier.Specific conductance value.Specific conductance
-1 2011-02-14 1360
-2 2011-02-17 1930
-3 2011-03-03 1240
-4 2011-03-10 1480
-5 2011-03-29 1130
-6 2011-04-07 1200
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+specificCond <- \hlfunctioncall{getWQPData}(\hlstring{'WIDNR_WQX-10032762'},
+ \hlstring{'Specific conductance'}, \hlstring{''}, \hlstring{''})
+\hlfunctioncall{head}(specificCond)
+\end{alltt}
+\begin{verbatim}
+## dateTime qualifier.Specific conductance
+## 1 2011-02-14
+## 2 2011-02-17
+## 3 2011-03-03
+## 4 2011-03-10
+## 5 2011-03-29
+## 6 2011-04-07
+## value.Specific conductance
+## 1 1360
+## 2 1930
+## 3 1240
+## 4 1480
+## 5 1130
+## 6 1200
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
%------------------------------------------------------------
@@ -474,19 +614,24 @@ There are additional data sets available on the Water Quality Data Portal (\url{
There may be times when you might be interested in seeing the URL (web address) that was used to obtain the raw data. The constructNWISURL function returns the URL. Aside from input variables that have already been described, there is a new argument \texttt{"}service\texttt{"}. The service argument can be \texttt{"}dv\texttt{"} (daily values), \texttt{"}uv\texttt{"} (unit values), \texttt{"}qw\texttt{"} (NWIS water quality values), or \texttt{"}wqp\texttt{"} (general Water Quality Portal values).
-\begin{Schunk}
-\begin{Sinput}
-> # Dissolved Nitrate parameter codes:
-> pCode <- c("00618","71851")
-> startDate <- "1964-06-11"
-> endDate <- "2012-12-18"
-> url_qw <- constructNWISURL(siteNumber,pCode,startDate,endDate,'qw')
-> url_dv <- constructNWISURL(siteNumber,"00060",startDate,endDate,'dv',statCd="00003")
-> url_uv <- constructNWISURL(siteNumber,"00060",startDate,endDate,'uv')
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlcomment{# Dissolved Nitrate parameter codes:}
+pCode <- \hlfunctioncall{c}(\hlstring{"00618"},\hlstring{"71851"})
+startDate <- \hlstring{"1964-06-11"}
+endDate <- \hlstring{"2012-12-18"}
+url_qw <- \hlfunctioncall{constructNWISURL}(siteNumber,pCode,startDate,endDate,\hlstring{'qw'})
+url_dv <- \hlfunctioncall{constructNWISURL}(siteNumber,\hlstring{"00060"},startDate,endDate,
+ \hlstring{'dv'},statCd=\hlstring{"00003"})
+url_uv <- \hlfunctioncall{constructNWISURL}(siteNumber,\hlstring{"00060"},startDate,endDate,\hlstring{'uv'})
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
+
%------------------------------------------------------------
\section{Data Retrievals Structured For Use In The EGRET Package}
%------------------------------------------------------------
@@ -499,76 +644,98 @@ In this section, we use 3 dataRetrieval functions to get sufficient data to perf
%------------------------------------------------------------
The function to obtain metadata, or data about the streamgage and measured parameters is getMetaData. This function combines getSiteFileData and getParameterInfo, producing one dataframe called INFO.
-\begin{Schunk}
-\begin{Sinput}
-> parameterCd <- "00618"
-> INFO <-getMetaData(siteNumber,parameterCd, interactive=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+parameterCd <- \hlstring{"00618"}
+INFO <-\hlfunctioncall{getMetaData}(siteNumber,parameterCd, interactive=FALSE)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
Column names in the INFO dataframe are listed in Appendix 2 (\ref{sec:appendix2INFO}).
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Daily Data}
%------------------------------------------------------------
The function to obtain the daily values (discharge in this case) is getDVData. It requires the inputs siteNumber, ParameterCd, StartDate, EndDate, interactive, and convert. Most of these arguments are described in the previous section, however \texttt{"}convert\texttt{"} is a new argument (defaults to TRUE), and it tells the program to convert the values from cubic feet per second (cfs) to cubic meters per second (cms). For EGRET applications with NWIS web retrieval, do not use this argument (the default is TRUE), EGRET assumes that discharge is always in cubic meters per second. If you don't want this conversion and are not using EGRET, set convert=FALSE in the function call.
-\begin{Schunk}
-\begin{Sinput}
-> siteNumber <- "01491000"
-> startDate <- "2000-01-01"
-> endDate <- "2013-01-01"
-> # This call will get NWIS data that is in cfs, and convert it
-> # to cms since we didn't override the default in the convert argument:
-> Daily <- getDVData(siteNumber, "00060", startDate, endDate,interactive=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+siteNumber <- \hlstring{"01491000"}
+startDate <- \hlstring{"2000-01-01"}
+endDate <- \hlstring{"2013-01-01"}
+\hlcomment{# This call will get NWIS (cfs) data , and convert it to cms:}
+Daily <- \hlfunctioncall{getDVData}(siteNumber, \hlstring{"00060"}, startDate, endDate)
+\end{alltt}
+\begin{verbatim}
+## There are 4750 data points, and 4750 days.
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
Details of the Daily dataframe are listed below:
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:53 2013
-\begin{tabular}{llll}
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:10 2013
+\begin{table}[ht]
+\centering
+\begin{tabular}{rllll}
\hline
-ColumnName & Type & Description & Units \\
+ & ColumnName & Type & Description & Units \\
\hline
-Date & Date & Date & date \\
- Q & number & Discharge & cms \\
- Julian & number & Number of days since January 1, 1850 & days \\
- Month & integer & Month of the year [1-12] & months \\
- Day & integer & Day of the year [1-366] & days \\
- DecYear & number & Decimal year & years \\
- MonthSeq & integer & Number of months since January 1, 1850 & months \\
- Qualifier & string & Qualifing code & character \\
- i & integer & Index of days from the start of the data frame & days \\
- LogQ & number & Natural logarithm of Q & numeric \\
- Q7 & number & 7 day running average of Q & cms \\
- Q30 & number & 30 running average of Q & cms \\
+1 & Date & Date & Date & date \\
+ 2 & Q & number & Discharge in cms & cms \\
+ 3 & Julian & number & Number of days since January 1, 1850 & days \\
+ 4 & Month & integer & Month of the year [1-12] & months \\
+ 5 & Day & integer & Day of the year [1-366] & days \\
+ 6 & DecYear & number & Decimal year & years \\
+ 7 & MonthSeq & integer & Number of months since January 1, 1850 & months \\
+ 8 & Qualifier & string & Qualifing code & character \\
+ 9 & i & integer & Index of days, starting with 1 & days \\
+ 10 & LogQ & number & Natural logarithm of Q & numeric \\
+ 11 & Q7 & number & 7 day running average of Q & cms \\
+ 12 & Q30 & number & 30 running average of Q & cms \\
\hline
-\end{tabular}\\*
+\end{tabular}
+\caption{Daily dataframe}
+\end{table}
+
+
+
If there are discharge values of zero, the code will add a small constant to all of the daily discharges. This constant is 0.001 times the mean discharge. The code will also report on the number of zero values and the size of the constant. EGRET should only be used if the number of zero values is a very small fraction of the total days in the record (say less than 0.1\% of the days). Columns Q7 and Q30 are the 7 and 30 day running averages for the 7 or 30 days ending on this specific date.
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Sample Data}
%------------------------------------------------------------
The function to obtain sample data from the water quality portal is getSampleData. The arguments for this function are also siteNumber, ParameterCd, StartDate, EndDate, interactive. These are the same inputs as getRawQWData or getQWData as described in the previous section.
-\begin{Schunk}
-\begin{Sinput}
-> Sample <-getSampleData(siteNumber,parameterCd,
- startDate, endDate,interactive=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+parameterCd <- \hlstring{"00618"}
+Sample <-\hlfunctioncall{getSampleData}(siteNumber,parameterCd,
+ startDate, endDate,interactive=FALSE)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
+
+\pagebreak
Details of the Sample dataframe are listed below:
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:55 2013
\begin{table}[!ht]
-\centering
+\begin{minipage}{\linewidth}
+\begin{center}
\caption{Sample dataframe}
\begin{tabular}{llll}
\hline
@@ -590,9 +757,15 @@ Date & Date & Date & date \\
LogQ \footnotemark[1] & number & Natural logarithm of flow & numeric \\
\hline
\end{tabular}
-\end{table}\footnotetext[1]{Flow columns are populated from data in the Daily dataframe after calling the mergeReport function.}
+\end{center}
+\end{minipage}
+\end{table}
+
+\footnotetext[1]{Flow columns are populated from data in the Daily dataframe after calling the mergeReport function.}
\FloatBarrier
+
+
%------------------------------------------------------------
\subsection{Censored Values: Summation Explanation}
%------------------------------------------------------------
@@ -602,49 +775,60 @@ As an example to understand how the dataRetrieval package handles a more complex
\begin{center}
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:55 2013
-\begin{tabular}{llrlrlr}
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:11 2013
+\begin{table}[ht]
+\centering
+\begin{tabular}{rllrlrlr}
\hline
-cdate & rdp & dp & rpp & pp & rtp & tp \\
+ & cdate & rdp & dp & rpp & pp & rtp & tp \\
\hline
-2003-02-15 & & 0.02 & & 0.50 & & \\
- 2003-06-30 & $<$ & 0.01 & & 0.30 & & \\
- 2004-09-15 & $<$ & 0.00 & $<$ & 0.20 & & \\
- 2005-01-30 & & & & & & 0.43 \\
- 2005-05-30 & & & & & $<$ & 0.05 \\
- 2005-10-30 & & & & & $<$ & 0.02 \\
+1 & 2003-02-15 & & 0.02 & & 0.50 & & \\
+ 2 & 2003-06-30 & $<$ & 0.01 & & 0.30 & & \\
+ 3 & 2004-09-15 & $<$ & 0.00 & $<$ & 0.20 & & \\
+ 4 & 2005-01-30 & & & & & & 0.43 \\
+ 5 & 2005-05-30 & & & & & $<$ & 0.05 \\
+ 6 & 2005-10-30 & & & & & $<$ & 0.02 \\
\hline
\end{tabular}
+\caption{Example data}
+\end{table}
+
+
+
\end{center}
The dataRetrieval package will \texttt{"}add up\texttt{"} all the values in a given row to form the total for that sample. Thus, you only want to enter data that should be added together. For example, we might know the value for dp on 5/30/2005, but we don't want to put it in the table because under the rules of this data set, we are not suppose to add it in to the values in 2005.
-For every sample, the EGRET package requires a pair of numbers to define an interval in which the true value lies (ConcLow and ConcHigh). In a simple non-censored case (the reported value is above the detection limit), ConcLow equals ConcHigh and the interval collapses down to a single point.In a simple censored case, the value might be reported as <0.2, then ConcLow=NA and ConcHigh=0.2. We use NA instead of 0 as a way to elegantly handle future logarithm calculations.
-
-For the more complex example case, let us say dp is reported as <0.01 and pp is reported as 0.3. We know that the total must be at least 0.3 and could be as much as 0.31. Therefore, ConcLow=0.3 and ConcHigh=0.31. Another case would be if dp is reported as <0.005 and pp is reported <0.2. We know in this case that the true value could be as low as zero, but could be as high as 0.205. Therefore, in this case, ConcLow=NA and ConcHigh=0.205. The Sample dataframe for the example data is therefore:
-
-\begin{Schunk}
-\begin{Soutput}
- Date ConcLow ConcHigh Uncen ConcAve Julian Month Day DecYear MonthSeq
-1 2003-02-15 0.520 0.520 1 0.520 55927 2 46 2003.124 1838
-2 2003-06-30 0.310 0.310 1 0.310 56062 6 181 2003.493 1842
-3 2004-09-15 0.205 0.205 1 0.205 56505 9 259 2004.706 1857
-4 2005-01-30 0.430 0.430 1 0.430 56642 1 30 2005.081 1861
-5 2005-05-30 0.050 0.050 1 0.050 56762 5 150 2005.408 1865
-6 2005-10-30 0.020 0.020 1 0.020 56915 10 303 2005.827 1870
- SinDY CosDY
-1 0.70406552 0.7101350
-2 0.04290476 -0.9990792
-3 -0.96251346 -0.2712339
-4 0.48505985 0.8744810
-5 0.54391895 -0.8391378
-6 -0.88668032 0.4623830
-\end{Soutput}
-\end{Schunk}
+For every sample, the EGRET package requires a pair of numbers to define an interval in which the true value lies (ConcLow and ConcHigh). In a simple non-censored case (the reported value is above the detection limit), ConcLow equals ConcHigh and the interval collapses down to a single point.In a simple censored case, the value might be reported as \verb@<@0.2, then ConcLow=NA and ConcHigh=0.2. We use NA instead of 0 as a way to elegantly handle future logarithm calculations.
+
+For the more complex example case, let us say dp is reported as \verb@<@0.01 and pp is reported as 0.3. We know that the total must be at least 0.3 and could be as much as 0.31. Therefore, ConcLow=0.3 and ConcHigh=0.31. Another case would be if dp is reported as \verb@<@0.005 and pp is reported \verb@<@0.2. We know in this case that the true value could be as low as zero, but could be as high as 0.205. Therefore, in this case, ConcLow=NA and ConcHigh=0.205. The Sample dataframe for the example data is therefore:
+
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{verbatim}
+## Date ConcLow ConcHigh Uncen ConcAve Julian Month
+## 1 2003-02-15 0.520 0.520 1 0.520 55927 2
+## 2 2003-06-30 0.310 0.310 1 0.310 56062 6
+## 3 2004-09-15 0.205 0.205 1 0.205 56505 9
+## 4 2005-01-30 0.430 0.430 1 0.430 56642 1
+## 5 2005-05-30 0.050 0.050 1 0.050 56762 5
+## 6 2005-10-30 0.020 0.020 1 0.020 56915 10
+## Day DecYear MonthSeq SinDY CosDY
+## 1 46 2003 1838 0.70407 0.7101
+## 2 182 2003 1842 0.02575 -0.9997
+## 3 259 2005 1857 -0.96251 -0.2712
+## 4 30 2005 1861 0.48506 0.8745
+## 5 151 2005 1865 0.52943 -0.8484
+## 6 304 2006 1870 -0.87861 0.4775
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{User-Generated Data Files}
%------------------------------------------------------------
@@ -663,7 +847,7 @@ So, if you have a file called \texttt{"}ChoptankRiverFlow.txt\texttt{"} located
\begin{verbatim}
date Qdaily
10/1/1999 107
-10/2/1999 85
+10/2/1999 85
10/3/1999 76
10/4/1999 76
10/5/1999 113
@@ -672,15 +856,20 @@ date Qdaily
\end{verbatim}
The call to open this file, convert the flow to cubic meters per second, and populate the Daily data frame would be:
-\begin{Schunk}
-\begin{Sinput}
-> fileName <- "ChoptankRiverFlow.txt"
-> filePath <- "C:/RData/"
-> Daily <- getDailyDataFromFile(filePath,fileName,separator="\t",interactive=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+fileName <- \hlstring{"ChoptankRiverFlow.txt"}
+filePath <- \hlstring{"C:/RData/"}
+Daily <- \hlfunctioncall{getDailyDataFromFile}(filePath,fileName,
+ separator=\hlstring{"\textbackslash{}t"})
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
+
%------------------------------------------------------------
\subsubsection{getSampleDataFromFile}
%------------------------------------------------------------
@@ -696,86 +885,102 @@ cdate;remarkCode;Nitrate
...
\end{verbatim}
The call to open this file, and populate the Sample dataframe would be:
-\begin{Schunk}
-\begin{Sinput}
-> fileName <- "ChoptankRiverNitrate.csv"
-> filePath <- "C:/RData/"
-> Sample <- getSampleDataFromFile(filePath,fileName,separator=",",interactive=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+fileName <- \hlstring{"ChoptankRiverNitrate.csv"}
+filePath <- \hlstring{"C:/RData/"}
+Sample <- \hlfunctioncall{getSampleDataFromFile}(filePath,fileName,
+ separator=\hlstring{","})
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{Merge Report}
%------------------------------------------------------------
Finally, there is a function called mergeReport that will look at both the Daily and Sample dataframe, and populate Q and LogQ columns into the Sample dataframe. The default arguments are Daily and Sample, however if you want to use other similarly structured dataframes, you can specify localDaily or localSample. Once mergeReport has been run, the Sample dataframe will be augumented with the daily discharges for all the days with samples. None of the water quality functions in EGRET will work without first having run the mergeReport function.
-\begin{Schunk}
-\begin{Sinput}
-> siteNumber <- "01491000"
-> parameterCd <- "00631" # Nitrate
-> startDate <- "2000-01-01"
-> endDate <- "2013-01-01"
-> Daily <- getDVData(siteNumber, "00060", startDate, endDate,interactive=FALSE)
-> Sample <- getSampleData(siteNumber,parameterCd, startDate, endDate, interactive=FALSE)
-> Sample <- mergeReport()
-\end{Sinput}
-\begin{Soutput}
- Discharge Record is 4750 days long, which is 13 years
- First day of the discharge record is 2000-01-01 and last day is 2013-01-01
- The water quality record has 220 samples
- The first sample is from 2000-01-04 and the last sample is from 2012-12-18
- Discharge: Minimum, mean and maximum 0.00991 4.55 246
- Concentration: Minimum, mean and maximum 0.2 1.3 2.4
- Percentage of the sample values that are censored is 0 %
-\end{Soutput}
-\begin{Sinput}
-> head(Sample)
-\end{Sinput}
-\begin{Soutput}
- Date ConcLow ConcHigh Uncen ConcAve Julian Month Day DecYear MonthSeq
-1 2000-01-04 1.59 1.59 1 1.59 54789 1 4 2000.010 1801
-2 2000-02-03 1.54 1.54 1 1.54 54819 2 34 2000.092 1802
-3 2000-02-15 1.37 1.37 1 1.37 54831 2 46 2000.124 1802
-4 2000-02-19 1.24 1.24 1 1.24 54835 2 50 2000.135 1802
-5 2000-03-23 0.52 0.52 1 0.52 54868 3 83 2000.225 1803
-6 2000-06-05 1.11 1.11 1 1.11 54942 6 157 2000.428 1806
- SinDY CosDY Q LogQ
-1 0.06004896 0.9981954 2.746734 1.0104126
-2 0.54391895 0.8391378 3.936042 1.3701756
-3 0.70406552 0.7101350 10.845352 2.3837366
-4 0.75113193 0.6601521 15.517632 2.7419769
-5 0.98808790 0.1538906 56.916861 4.0415916
-6 0.43939951 -0.8982918 1.812278 0.5945847
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+siteNumber <- \hlstring{"01491000"}
+parameterCd <- \hlstring{"00631"} # Nitrate
+startDate <- \hlstring{"2000-01-01"}
+endDate <- \hlstring{"2013-01-01"}
+
+Daily <- \hlfunctioncall{getDVData}(siteNumber, \hlstring{"00060"}, startDate, endDate)
+\end{alltt}
+\begin{verbatim}
+## There are 4750 data points, and 4750 days.
+\end{verbatim}
+\begin{alltt}
+Sample <- \hlfunctioncall{getSampleData}(siteNumber,parameterCd, startDate, endDate)
+Sample <- \hlfunctioncall{mergeReport}()
+\end{alltt}
+\begin{verbatim}
+##
+## Discharge Record is 4750 days long, which is 13 years
+## First day of the discharge record is 2000-01-01 and last day is 2013-01-01
+## The water quality record has 220 samples
+## The first sample is from 2000-01-04 and the last sample is from 2012-12-18
+## Discharge: Minimum, mean and maximum 0.00991 4.55 246
+## Concentration: Minimum, mean and maximum 0.2 1.3 2.4
+## Percentage of the sample values that are censored is 0 %
+\end{verbatim}
+\begin{alltt}
+\hlfunctioncall{head}(Sample)
+\end{alltt}
+\begin{verbatim}
+## Date ConcLow ConcHigh Uncen ConcAve Julian Month
+## 1 2000-01-04 1.59 1.59 1 1.59 54789 1
+## 2 2000-02-03 1.54 1.54 1 1.54 54819 2
+## 3 2000-02-15 1.37 1.37 1 1.37 54831 2
+## 4 2000-02-19 1.24 1.24 1 1.24 54835 2
+## 5 2000-03-23 0.52 0.52 1 0.52 54868 3
+## 6 2000-06-05 1.11 1.11 1 1.11 54942 6
+## Day DecYear MonthSeq SinDY CosDY Q LogQ
+## 1 4 2000 1801 0.06005 0.9982 2.747 1.0104
+## 2 34 2000 1802 0.54392 0.8391 3.936 1.3702
+## 3 46 2000 1802 0.70407 0.7101 10.845 2.3837
+## 4 50 2000 1802 0.75113 0.6602 15.518 2.7420
+## 5 83 2000 1803 0.98809 0.1539 56.917 4.0416
+## 6 157 2000 1806 0.43940 -0.8983 1.812 0.5946
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
\FloatBarrier
+
%------------------------------------------------------------
\subsection{EGRET Plots}
%------------------------------------------------------------
As has been mentioned, the data is specifically formatted to be used with the EGRET package. The EGRET package has powerful modeling capabilities using WRTDS, but also has a variety of graphing and tablular tools to explore the data without using the WRTDS algorithm. See the EGRET vignette, user guide, and/or wiki (\url{https://github.com/USGS-R/EGRET/wiki}) for detailed information. The following figure is an example of one of the plotting functions that can be used directly from the dataRetrieval dataframes.
-\begin{Schunk}
-\begin{Sinput}
-> # Continuing Choptank example from the previous sections
-> library(EGRET)
-> multiPlotDataOverview()
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlcomment{# Continuing Choptank example from the previous sections}
+\hlfunctioncall{library}(EGRET)
+\hlfunctioncall{multiPlotDataOverview}()
+\end{alltt}
+\end{kframe}\begin{figure}[]
-\begin{figure}[ht]
-\begin{center}
-
-\includegraphics{dataRetrieval-figegretEx}
-\end{center}
-\caption{Default multiPlotDataOverview}
-\label{fig:multiPlotDataOverview}
+\includegraphics[width=\maxwidth]{figure/egretEx} \caption[Default multiPlotDataOverview]{Default multiPlotDataOverview\label{fig:egretEx}}
\end{figure}
+
+\end{knitrout}
+
+
\clearpage
\appendix
+
%------------------------------------------------------------
\section{Getting Started in R}
\label{sec:appendix1}
@@ -791,27 +996,32 @@ There are many options for running and editing R code, one nice environment to l
At any time, you can get information about any function in R by typing a question mark before the functions name. This will open a file (in RStudio, in the Help window) that describes the function, the required arguments, and provides working examples.
-\begin{Schunk}
-\begin{Sinput}
-> ?removeDuplicates
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+?removeDuplicates
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
To see the raw code for a particular code, type the name of the function:
-\begin{Schunk}
-\begin{Sinput}
-> removeDuplicates
-\end{Sinput}
-\begin{Soutput}
-function (localSample = Sample)
-{
- Sample1 <- localSample[!duplicated(localSample[c("DecYear",
- "ConcHigh")]), ]
- return(Sample1)
-}
-<environment: namespace:dataRetrieval>
-\end{Soutput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+removeDuplicates
+\end{alltt}
+\begin{verbatim}
+## function (localSample = Sample)
+## {
+## Sample1 <- localSample[!duplicated(localSample[c("DecYear",
+## "ConcHigh")]), ]
+## return(Sample1)
+## }
+## <environment: namespace:dataRetrieval>
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
%------------------------------------------------------------
@@ -819,42 +1029,27 @@ function (localSample = Sample)
%------------------------------------------------------------
Before installing dataRetrieval, the zoo packages must be installed from CRAN:
-\begin{Schunk}
-\begin{Sinput}
-> install.packages("zoo")
-> install.packages("dataRetrieval", repos="http://usgs-r.github.com", type="source")
-\end{Sinput}
-\end{Schunk}
-
-It is a good idea to re-start the R enviornment after installing the package, especially if installing an updated version. Some users have found it necessary to delete the previous version's package folder before installing newer version of dataRetrieval. If you are experiencing issues after updating a package, trying deleting the package folder - the default location for Windows is something like this: C:/Users/userA/Documents/R/win-library/2.15/dataRetrieval, and the default for a Mac: /Users/userA/Library/R/2.15/library/dataRetrieval. Then, re-install the package using the directions above. Moving to CRAN should solve this problem.
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{install.packages}(\hlstring{"zoo"})
+\hlfunctioncall{install.packages}(\hlstring{"dataRetrieval"}, repos=\hlstring{"http://usgs-r.github.com"}, type=\hlstring{"source"})
+\end{alltt}
+\end{kframe}
+\end{knitrout}
-After installing the package, you need to open the library each time you re-start R. This is done with the simple command:
-\begin{Schunk}
-\begin{Sinput}
-> library(dataRetrieval)
-\end{Sinput}
-\end{Schunk}
-Using RStudio, you could alternatively click on the checkbox for dataRetrieval in the Packages window.
-
-%------------------------------------------------------------
-\subsection{R Developers: Installing dataRetrieval from gitHub}
-%------------------------------------------------------------
-Alternatively, R-developers can install the latest working version of dataRetrieval directly from gitHub using the devtools package (available on CRAN). Rtools (for Windows) and appropriate \LaTeX\ tools are required. Be aware that the version installed using this method isn't necessarily the same as the version in the stable release branch.
+It is a good idea to re-start R after installing the package, especially if installing an updated version. Some users have found it necessary to delete the previous version's package folder before installing newer version of dataRetrieval. If you are experiencing issues after updating a package, trying deleting the package folder - the default location for Windows is something like this: C:/Users/userA/Documents/R/win-library/2.15/dataRetrieval, and the default for a Mac: /Users/userA/Library/R/2.15/library/dataRetrieval. Then, re-install the package using the directions above. Moving to CRAN should solve this problem.
-\begin{Schunk}
-\begin{Sinput}
-> library(devtools)
-> install_github("dataRetrieval", "USGS-R")
-\end{Sinput}
-\end{Schunk}
-To then open the library, simply type:
+After installing the package, you need to open the library each time you re-start R. This is done with the simple command:
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{library}(dataRetrieval)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
-\begin{Schunk}
-\begin{Sinput}
-> library(dataRetrieval)
-\end{Sinput}
-\end{Schunk}
%------------------------------------------------------------
\section{Columns Names}
@@ -866,55 +1061,63 @@ To then open the library, simply type:
\label{sec:appendix2INFO}
%------------------------------------------------------------
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:57 2013
-\begin{tabular}{l}
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:14 2013
+\begin{table}[ht]
+\centering
+\begin{tabular}{rl}
\hline
+ & ColumnNames \\
\hline
-agency.cd \\
- site.no \\
- station.nm \\
- site.tp.cd \\
- lat.va \\
- long.va \\
- dec.lat.va \\
- dec.long.va \\
- coord.meth.cd \\
- coord.acy.cd \\
- coord.datum.cd \\
- dec.coord.datum.cd \\
- district.cd \\
- state.cd \\
- county.cd \\
- country.cd \\
- map.nm \\
- map.scale.fc \\
- alt.va \\
- alt.meth.cd \\
- alt.acy.va \\
- alt.datum.cd \\
- huc.cd \\
- basin.cd \\
- topo.cd \\
- construction.dt \\
- inventory.dt \\
- drain.area.va \\
- contrib.drain.area.va \\
- tz.cd \\
- local.time.fg \\
- reliability.cd \\
- project.no \\
- queryTime \\
- drainSqKm \\
- shortName \\
- staAbbrev \\
- param.nm \\
- param.units \\
- paramShortName \\
- paramNumber \\
- constitAbbrev \\
+1 & agency.cd \\
+ 2 & site.no \\
+ 3 & station.nm \\
+ 4 & site.tp.cd \\
+ 5 & lat.va \\
+ 6 & long.va \\
+ 7 & dec.lat.va \\
+ 8 & dec.long.va \\
+ 9 & coord.meth.cd \\
+ 10 & coord.acy.cd \\
+ 11 & coord.datum.cd \\
+ 12 & dec.coord.datum.cd \\
+ 13 & district.cd \\
+ 14 & state.cd \\
+ 15 & county.cd \\
+ 16 & country.cd \\
+ 17 & map.nm \\
+ 18 & map.scale.fc \\
+ 19 & alt.va \\
+ 20 & alt.meth.cd \\
+ 21 & alt.acy.va \\
+ 22 & alt.datum.cd \\
+ 23 & huc.cd \\
+ 24 & basin.cd \\
+ 25 & topo.cd \\
+ 26 & construction.dt \\
+ 27 & inventory.dt \\
+ 28 & drain.area.va \\
+ 29 & contrib.drain.area.va \\
+ 30 & tz.cd \\
+ 31 & local.time.fg \\
+ 32 & reliability.cd \\
+ 33 & project.no \\
+ 34 & queryTime \\
+ 35 & drainSqKm \\
+ 36 & shortName \\
+ 37 & staAbbrev \\
+ 38 & param.nm \\
+ 39 & param.units \\
+ 40 & paramShortName \\
+ 41 & paramNumber \\
+ 42 & constitAbbrev \\
\hline
\end{tabular}
+\caption{Column names in the INFO dataframe}
+\end{table}
+
+
+
\FloatBarrier
%------------------------------------------------------------
@@ -924,84 +1127,100 @@ agency.cd \\
There are 62 columns returned from the water quality portal.
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:57 2013
-\begin{tabular}{l}
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:14 2013
+\begin{table}[ht]
+\centering
+\begin{tabular}{rl}
\hline
+ & ColumnNames \\
\hline
-OrganizationIdentifier \\
- OrganizationFormalName \\
- ActivityIdentifier \\
- ActivityTypeCode \\
- ActivityMediaName \\
- ActivityMediaSubdivisionName \\
- ActivityStartDate \\
- ActivityStartTime.Time \\
- ActivityStartTime.TimeZoneCode \\
- ActivityEndDate \\
- ActivityEndTime.Time \\
- ActivityEndTime.TimeZoneCode \\
- ActivityDepthHeightMeasure.MeasureValue \\
- ActivityDepthHeightMeasure.MeasureUnitCode \\
- ActivityDepthAltitudeReferencePointText \\
- ActivityTopDepthHeightMeasure.MeasureValue \\
- ActivityTopDepthHeightMeasure.MeasureUnitCode \\
- ActivityBottomDepthHeightMeasure.MeasureValue \\
- ActivityBottomDepthHeightMeasure.MeasureUnitCode \\
- ProjectIdentifier \\
- ActivityConductingOrganizationText \\
- MonitoringLocationIdentifier \\
- ActivityCommentText \\
- SampleAquifer \\
- HydrologicCondition \\
- HydrologicEvent \\
- SampleCollectionMethod.MethodIdentifier \\
- SampleCollectionMethod.MethodIdentifierContext \\
- SampleCollectionMethod.MethodName \\
- SampleCollectionEquipmentName \\
- ResultDetectionConditionText \\
- CharacteristicName \\
- ResultSampleFractionText \\
- ResultMeasureValue \\
- ResultMeasure.MeasureUnitCode \\
- MeasureQualifierCode \\
- ResultStatusIdentifier \\
- StatisticalBaseCode \\
- ResultValueTypeName \\
- ResultWeightBasisText \\
+1 & OrganizationIdentifier \\
+ 2 & OrganizationFormalName \\
+ 3 & ActivityIdentifier \\
+ 4 & ActivityTypeCode \\
+ 5 & ActivityMediaName \\
+ 6 & ActivityMediaSubdivisionName \\
+ 7 & ActivityStartDate \\
+ 8 & ActivityStartTime.Time \\
+ 9 & ActivityStartTime.TimeZoneCode \\
+ 10 & ActivityEndDate \\
+ 11 & ActivityEndTime.Time \\
+ 12 & ActivityEndTime.TimeZoneCode \\
+ 13 & ActivityDepthHeightMeasure.MeasureValue \\
+ 14 & ActivityDepthHeightMeasure.MeasureUnitCode \\
+ 15 & ActivityDepthAltitudeReferencePointText \\
+ 16 & ActivityTopDepthHeightMeasure.MeasureValue \\
+ 17 & ActivityTopDepthHeightMeasure.MeasureUnitCode \\
+ 18 & ActivityBottomDepthHeightMeasure.MeasureValue \\
+ 19 & ActivityBottomDepthHeightMeasure.MeasureUnitCode \\
+ 20 & ProjectIdentifier \\
+ 21 & ActivityConductingOrganizationText \\
+ 22 & MonitoringLocationIdentifier \\
+ 23 & ActivityCommentText \\
+ 24 & SampleAquifer \\
+ 25 & HydrologicCondition \\
+ 26 & HydrologicEvent \\
+ 27 & SampleCollectionMethod.MethodIdentifier \\
+ 28 & SampleCollectionMethod.MethodIdentifierContext \\
+ 29 & SampleCollectionMethod.MethodName \\
+ 30 & SampleCollectionEquipmentName \\
+ 31 & ResultDetectionConditionText \\
+ 32 & CharacteristicName \\
+ 33 & ResultSampleFractionText \\
+ 34 & ResultMeasureValue \\
+ 35 & ResultMeasure.MeasureUnitCode \\
+ 36 & MeasureQualifierCode \\
+ 37 & ResultStatusIdentifier \\
+ 38 & StatisticalBaseCode \\
+ 39 & ResultValueTypeName \\
+ 40 & ResultWeightBasisText \\
\hline
\end{tabular}
+\caption{Column names in dissolvedNitrate}
+\end{table}
+
+
+
\FloatBarrier
-% latex table generated in R 3.0.0 by xtable 1.7-1 package
-% Thu Apr 25 12:08:58 2013
-\begin{tabular}{l}
+% latex table generated in R 3.0.1 by xtable 1.7-1 package
+% Mon Jun 17 15:35:14 2013
+\begin{table}[ht]
+\centering
+\begin{tabular}{rl}
\hline
+ & ColumnNames\_Continued \\
\hline
-ResultTimeBasisText \\
- ResultTemperatureBasisText \\
- ResultParticleSizeBasisText \\
- PrecisionValue \\
- ResultCommentText \\
- USGSPCode \\
- ResultDepthHeightMeasure.MeasureValue \\
- ResultDepthHeightMeasure.MeasureUnitCode \\
- ResultDepthAltitudeReferencePointText \\
- SubjectTaxonomicName \\
- SampleTissueAnatomyName \\
- ResultAnalyticalMethod.MethodIdentifier \\
- ResultAnalyticalMethod.MethodIdentifierContext \\
- ResultAnalyticalMethod.MethodName \\
- MethodDescriptionText \\
- LaboratoryName \\
- AnalysisStartDate \\
- ResultLaboratoryCommentText \\
- DetectionQuantitationLimitTypeName \\
- DetectionQuantitationLimitMeasure.MeasureValue \\
- DetectionQuantitationLimitMeasure.MeasureUnitCode \\
- PreparationStartDate \\
+1 & ResultTimeBasisText \\
+ 2 & ResultTemperatureBasisText \\
+ 3 & ResultParticleSizeBasisText \\
+ 4 & PrecisionValue \\
+ 5 & ResultCommentText \\
+ 6 & USGSPCode \\
+ 7 & ResultDepthHeightMeasure.MeasureValue \\
+ 8 & ResultDepthHeightMeasure.MeasureUnitCode \\
+ 9 & ResultDepthAltitudeReferencePointText \\
+ 10 & SubjectTaxonomicName \\
+ 11 & SampleTissueAnatomyName \\
+ 12 & ResultAnalyticalMethod.MethodIdentifier \\
+ 13 & ResultAnalyticalMethod.MethodIdentifierContext \\
+ 14 & ResultAnalyticalMethod.MethodName \\
+ 15 & MethodDescriptionText \\
+ 16 & LaboratoryName \\
+ 17 & AnalysisStartDate \\
+ 18 & ResultLaboratoryCommentText \\
+ 19 & DetectionQuantitationLimitTypeName \\
+ 20 & DetectionQuantitationLimitMeasure.MeasureValue \\
+ 21 & DetectionQuantitationLimitMeasure.MeasureUnitCode \\
+ 22 & PreparationStartDate \\
\hline
\end{tabular}
+\caption{Column names in dissolvedNitrate}
+\end{table}
+
+
+
\clearpage
%------------------------------------------------------------
@@ -1010,38 +1229,66 @@ ResultTimeBasisText \\
%------------------------------------------------------------
There are a few steps that are required in order to create a table in a Microsoft product (Excel, Word, Powerpoint, etc.) from an R dataframe. There are certainly a variety of good methods, one of which is detailed here. The example we will step through here will be to create a table in Microsoft Word based on the dataframe tableData:
-\begin{Schunk}
-\begin{Sinput}
-> ChoptankAvailableData <- getDataAvailability(siteNumber)
-> ChoptankDailyData <- ChoptankAvailableData["dv" == ChoptankAvailableData$service,]
-> ChoptankDailyData <- ChoptankDailyData["00003" == ChoptankDailyData$statCd,]
-> pCodeINFO <- getMultipleParameterNames(ChoptankDailyData$parameter_cd, interactive=FALSE)
-> ChoptankDailyData <- merge(ChoptankDailyData,pCodeINFO,by="parameter_cd")
-> tableData <- with(ChoptankDailyData,
- data.frame(
- shortName=srsname,
- Start=startDate,
- End=endDate,
- Count=count,
- Units=parameter_units)
- )
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+availableData <- \hlfunctioncall{getDataAvailability}(siteNumber)
+dailyData <- availableData[\hlstring{"dv"} == availableData$service,]
+dailyData <- dailyData[\hlstring{"00003"} == dailyData$statCd,]
+pCodeINFO <- \hlfunctioncall{getMultipleParameterNames}(dailyData$parameter_cd)
+\end{alltt}
+\begin{verbatim}
+## Percent complete:
+## 20 40 60 80 100
+\end{verbatim}
+\begin{alltt}
+dailyData <- \hlfunctioncall{merge}(dailyData,pCodeINFO, by=\hlstring{"parameter_cd"})
+
+tableData <- \hlfunctioncall{with}(dailyData,
+ \hlfunctioncall{data.frame}(
+ shortName=srsname,
+ Start=startDate,
+ End=endDate,
+ Count=count,
+ Units=parameter_units)
+ )
+tableData
+\end{alltt}
+\begin{verbatim}
+## shortName Start
+## 1 Temperature, water 2010-10-01
+## 2 Stream flow, mean. daily 1948-01-01
+## 3 Specific conductance 2010-10-01
+## 4 Suspended sediment concentration (SSC) 1980-10-01
+## 5 Suspended sediment discharge 1980-10-01
+## End Count Units
+## 1 2012-05-09 529 deg C
+## 2 2013-06-16 23908 cfs
+## 3 2012-05-09 527 uS/cm @25C
+## 4 1991-09-30 3651 mg/l
+## 5 1991-09-30 3652 tons/day
+\end{verbatim}
+\end{kframe}
+\end{knitrout}
+
First, save the dataframe as a tab delimited file (you don't want to use comma delimited because there are commas in some of the data elements):
-\begin{Schunk}
-\begin{Sinput}
-> write.table(tableData, file="tableData.tsv",sep="\t",
- row.names = FALSE,quote=FALSE)
-\end{Sinput}
-\end{Schunk}
+\begin{knitrout}
+\definecolor{shadecolor}{rgb}{0.969, 0.969, 0.969}\color{fgcolor}\begin{kframe}
+\begin{alltt}
+\hlfunctioncall{write.table}(tableData, file=\hlstring{"tableData.tsv"},sep=\hlstring{"\textbackslash{}t"},
+ row.names = FALSE,quote=FALSE)
+\end{alltt}
+\end{kframe}
+\end{knitrout}
+
This will save a file in your working directory called tableData.tsv. You can see your working directory by typing getwd() in the R console. Opening the file in a general-purpose text editor, you should see the following:
\begin{verbatim}
-shortName Start End Count Units
+shortName Start End Count Units
Temperature, water 2010-10-01 2012-06-24 575 deg C
Stream flow, mean. daily 1948-01-01 2013-03-13 23814 cfs
Specific conductance 2010-10-01 2012-06-24 551 uS/cm @25C
@@ -1072,6 +1319,7 @@ From Excel, it is simple to copy and paste the tables in other Microsoft product
\end{figure}
\clearpage
+
%------------------------------------------------------------
% BIBLIO
%------------------------------------------------------------
diff --git a/vignettes/dataRetrieval.toc b/vignettes/dataRetrieval.toc
index f05553d7aa44793f0a9945381c7f4fe909a895f7..a6398165a491095179565b0083edcdf602e67b5e 100644
--- a/vignettes/dataRetrieval.toc
+++ b/vignettes/dataRetrieval.toc
@@ -4,28 +4,27 @@
\contentsline {subsection}{\numberline {2.1}Introduction}{3}{subsection.2.1}
\contentsline {subsection}{\numberline {2.2}Site Information}{4}{subsection.2.2}
\contentsline {subsubsection}{\numberline {2.2.1}getSiteFileData}{4}{subsubsection.2.2.1}
-\contentsline {subsubsection}{\numberline {2.2.2}getDataAvailability}{5}{subsubsection.2.2.2}
+\contentsline {subsubsection}{\numberline {2.2.2}getDataAvailability}{4}{subsubsection.2.2.2}
\contentsline {subsection}{\numberline {2.3}Parameter Information}{6}{subsection.2.3}
\contentsline {subsection}{\numberline {2.4}Daily Values}{7}{subsection.2.4}
-\contentsline {subsection}{\numberline {2.5}Unit Values}{8}{subsection.2.5}
-\contentsline {subsection}{\numberline {2.6}Water Quality Values}{10}{subsection.2.6}
-\contentsline {subsection}{\numberline {2.7}STORET Water Quality Retrievals}{11}{subsection.2.7}
-\contentsline {subsection}{\numberline {2.8}URL Construction}{12}{subsection.2.8}
-\contentsline {section}{\numberline {3}Data Retrievals Structured For Use In The EGRET Package}{12}{section.3}
-\contentsline {subsection}{\numberline {3.1}INFO Data}{13}{subsection.3.1}
-\contentsline {subsection}{\numberline {3.2}Daily Data}{13}{subsection.3.2}
-\contentsline {subsection}{\numberline {3.3}Sample Data}{14}{subsection.3.3}
-\contentsline {subsection}{\numberline {3.4}Censored Values: Summation Explanation}{15}{subsection.3.4}
-\contentsline {subsection}{\numberline {3.5}User-Generated Data Files}{16}{subsection.3.5}
-\contentsline {subsubsection}{\numberline {3.5.1}getDailyDataFromFile}{16}{subsubsection.3.5.1}
-\contentsline {subsubsection}{\numberline {3.5.2}getSampleDataFromFile}{17}{subsubsection.3.5.2}
-\contentsline {subsection}{\numberline {3.6}Merge Report}{18}{subsection.3.6}
-\contentsline {subsection}{\numberline {3.7}EGRET Plots}{19}{subsection.3.7}
-\contentsline {section}{\numberline {A}Getting Started in R}{21}{appendix.A}
-\contentsline {subsection}{\numberline {A.1}New to R?}{21}{subsection.A.1}
-\contentsline {subsection}{\numberline {A.2}R User: Installing dataRetrieval}{21}{subsection.A.2}
-\contentsline {subsection}{\numberline {A.3}R Developers: Installing dataRetrieval from gitHub}{22}{subsection.A.3}
+\contentsline {subsection}{\numberline {2.5}Unit Values}{10}{subsection.2.5}
+\contentsline {subsection}{\numberline {2.6}Water Quality Values}{12}{subsection.2.6}
+\contentsline {subsection}{\numberline {2.7}STORET Water Quality Retrievals}{14}{subsection.2.7}
+\contentsline {subsection}{\numberline {2.8}URL Construction}{14}{subsection.2.8}
+\contentsline {section}{\numberline {3}Data Retrievals Structured For Use In The EGRET Package}{15}{section.3}
+\contentsline {subsection}{\numberline {3.1}INFO Data}{15}{subsection.3.1}
+\contentsline {subsection}{\numberline {3.2}Daily Data}{15}{subsection.3.2}
+\contentsline {subsection}{\numberline {3.3}Sample Data}{16}{subsection.3.3}
+\contentsline {subsection}{\numberline {3.4}Censored Values: Summation Explanation}{17}{subsection.3.4}
+\contentsline {subsection}{\numberline {3.5}User-Generated Data Files}{18}{subsection.3.5}
+\contentsline {subsubsection}{\numberline {3.5.1}getDailyDataFromFile}{18}{subsubsection.3.5.1}
+\contentsline {subsubsection}{\numberline {3.5.2}getSampleDataFromFile}{19}{subsubsection.3.5.2}
+\contentsline {subsection}{\numberline {3.6}Merge Report}{20}{subsection.3.6}
+\contentsline {subsection}{\numberline {3.7}EGRET Plots}{21}{subsection.3.7}
+\contentsline {section}{\numberline {A}Getting Started in R}{23}{appendix.A}
+\contentsline {subsection}{\numberline {A.1}New to R?}{23}{subsection.A.1}
+\contentsline {subsection}{\numberline {A.2}R User: Installing dataRetrieval}{23}{subsection.A.2}
\contentsline {section}{\numberline {B}Columns Names}{24}{appendix.B}
\contentsline {subsection}{\numberline {B.1}INFO dataframe}{24}{subsection.B.1}
-\contentsline {subsection}{\numberline {B.2}Water Quality Portal}{25}{subsection.B.2}
-\contentsline {section}{\numberline {C}Creating tables in Microsoft from R}{27}{appendix.C}
+\contentsline {subsection}{\numberline {B.2}Water Quality Portal}{26}{subsection.B.2}
+\contentsline {section}{\numberline {C}Creating tables in Microsoft from R}{29}{appendix.C}
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