cleanUp: Cleans up hydrologic time series data

In waterData: Retrieval, Analysis, and Anomaly Calculation of Daily Hydrologic Time Series Data

Description

Function to identify and fix common problems with hydrologic data

Usage

cleanUp(dataset, task = "view", replace = 0.1)

Arguments

dataset	is a data frame in format of the data frame returned by importDVs.
task	is either "view" or "fix." View will return a list containing rows with negative values and rows with missing values. Fix will replace negative values with NA and replace zeroes with the value specified by the replace argument.
replace	is the value used to replace 0 values. The default is 0.1. For streamflow in small streams, one might want to use 0.01. For daily data other than streamflow, such as turbidity, users may not want to replace 0 values with a nonzero value. In those cases, replace can be set to 0.

Value

A list showing days with negative values and days with values of 0 when task is "view." When task is "fix" the fixed dataset is returned. When a negative value is replaced with NA, an "N" is added to the qualcode field to indicate that there had been a negative number. When a zero value is replaced, an "R" is added to the qualcode field to indicate that a zero value was replaced.

Note

If calculating anomalies (see compAnom), the user may need to replace isolated missing values with with a value; however, if there are larger periods with missing values, streamflow anomalies may not be an appropriate use of the data. The substitution of some missing data with values may be done using the function fillMiss that is part of this package. However, care needs to be taken when filling in missing data.

See Also

fillMiss

Examples

data(exampleWaterData)
head(badDataSet)
cleanUp(badDataSet, task="view")
q05054000Fix <- cleanUp(badDataSet, task="fix")
# replace 0s with NA, then one could use the fillMiss function
# to estimate values
q05054000Fix2 <- cleanUp(badDataSet, task="fix", replace=NA)
summary(badDataSet)
summary(q05054000Fix)
summary(q05054000Fix2)

Example output

     staid val      dates qualcode
1 05054000 470 2000-01-01      A e
2 05054000 470 2000-01-02      A e
3 05054000 470 2000-01-03      A e
4 05054000 460 2000-01-04      A e
5 05054000 460 2000-01-05      A e
6 05054000 460 2000-01-06      A e
[[1]]
        staid     val      dates qualcode
3979 05054000 -999999 2010-11-22  P Ice e

[[2]]
        staid val      dates qualcode
1365 05054000   0 2003-09-26        A
1366 05054000   0 2003-09-27        A
1367 05054000   0 2003-09-28        A

      staid           val              dates               qualcode   
 05054000:4018   Min.   :-999999   Min.   :2000-01-01   A      :2664  
                 1st Qu.:    523   1st Qu.:2002-10-01   A e    :1273  
                 Median :    923   Median :2005-07-01   P      :  41  
                 Mean   :   1548   Mean   :2005-07-01   P Ice e:   1  
                 3rd Qu.:   1900   3rd Qu.:2008-03-31   P e    :  39  
                 Max.   :  29100   Max.   :2010-12-31                 
      staid           val              dates                 qualcode   
 05054000:4018   Min.   :    0.1   Min.   :2000-01-01   A        :2661  
                 1st Qu.:  523.0   1st Qu.:2002-10-01   A R      :   3  
                 Median :  923.0   Median :2005-07-01   A e      :1273  
                 Mean   : 1797.0   Mean   :2005-07-01   P        :  41  
                 3rd Qu.: 1900.0   3rd Qu.:2008-03-31   P Ice e N:   1  
                 Max.   :29100.0   Max.   :2010-12-31   P e      :  39  
                 NA's   :1                                              
      staid           val              dates                 qualcode   
 05054000:4018   Min.   :   51.0   Min.   :2000-01-01   A        :2661  
                 1st Qu.:  524.0   1st Qu.:2002-10-01   A R      :   3  
                 Median :  924.5   Median :2005-07-01   A e      :1273  
                 Mean   : 1798.3   Mean   :2005-07-01   P        :  41  
                 3rd Qu.: 1900.0   3rd Qu.:2008-03-31   P Ice e N:   1  
                 Max.   :29100.0   Max.   :2010-12-31   P e      :  39  
                 NA's   :4                                              

waterData documentation built on May 2, 2019, 3:38 p.m.