In [1]:

    

setwd('/Users/erinlarson/Dropbox/Documents/GIT/DDESSS_Stream_Dream_Team')

data<-read.csv("WorkingDataSet.csv")

library("dplyr")


    

    




Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

In [2]:

    

t(data[1,])


    

    






1

	
X
1                   
	
ResultMeasure2
0                   
	
STRAHLER2
2.4                 
	
DrainageAreaMeasure_MeasureValue
195                 
	
HUCEightDigitCode
15060103            
	
date
2001-02-07T00:00:00Z
	
ResultSampleFractionText
Total               
	
PFOR2
73.918              
	
PWETL2
0.01                
	
PURB2
0.132               
	
PAGT2
0.076               
	
LatitudeMeasure
33.57311            
	
LongitudeMeasure
-110.9012           
	
MonitoringLocationIdentifier
USGS-09498400       

In [3]:

    

TotalP <-subset(data, ResultSampleFractionText=="Total")

group_by(TotalP, MonitoringLocationIdentifier) %>% 
    summarise(AvgTotal_P = mean(ResultMeasure2, na.rm = TRUE),
              SDTotal_P = sd(ResultMeasure2, na.rm = TRUE),
              PFOR2 = mean(PFOR2, na.rm=TRUE),
             Lat = mean(LatitudeMeasure, na.rm = TRUE),
              Long = mean(LongitudeMeasure, na.rm=TRUE)
             ) %>% write.csv("Avg_TotalP_LatLong.csv")


    

In [ ]:

    

TDP <-subset(data, ResultSampleFractionText=="Total")

group_by(TotalP, MonitoringLocationIdentifier) %>% 
    summarise(AvgTotal_P = mean(ResultMeasure2, na.rm = TRUE),
              SDTotal_P = sd(ResultMeasure2, na.rm = TRUE),
             Lat = mean(LatitudeMeasure, na.rm = TRUE),
              Long = mean(LongitudeMeasure, na.rm=TRUE)
             ) %>% write.csv("Avg_TotalP_LatLong.csv")