MarketaP

import sys, os, glob, winsound
import arcpy
from arcpy.sa import *
from arcpy import env

arcpy.CheckOutExtension('spatial')
arcpy.env.overwriteOutput = True
## List of rasters to project/sample to that of raster list 2
dataPath1 = r"I:\Data\USDM\GRACE_Grid"
dataPath2 = r"I:\Data\NLDAS\Reclassify\Levels\ewp"

MarketaP

library(car)
library(MASS)
library(ggplot2)
library(viridisLite)

setwd("C:/Users/mpodebradska2/Desktop/School/Thesis/Indices_analysis/VegDRI")
VegDRI <- read.csv("VegDRI.csv", header = TRUE)
names(VegDRI) <- c( "2009", "2010", "2011", "2012", "2013","2014", "2015", "2016")
Productivity <- read.csv("prod_anomaly.csv", header = TRUE)
Productivity <- Productivity[-480,-c(1,2,3,4,5,6,7,8,9)]

MarketaP

library(car)
library(MASS)
library(ggplot2)
library(viridisLite)

setwd("/Users/marketa/Library/Mobile Documents/com~apple~CloudDocs/School/Thesis/SPI")
SPI6m <- read.csv("SPI6m.csv", header = TRUE)
names(SPI6m) <- c("2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013","2014", "2015", "2016")
Productivity <- read.csv("prod_anomaly.csv", header = TRUE)
names(Productivity) <- c("2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013","2014", "2015", "2016")

MarketaP

setwd("C:/Users/mpodebradska2/Desktop")
all_content <- readLines("data.csv")
skip_second <- all_content[-2]
my_data <- read.csv(textConnection(skip_second), header = TRUE, stringsAsFactors = FALSE)
my_data$TF <- my_data$X.1>=my_data$State..WWDT.

MarketaP

in_table = 'C:\Users\mpodebradska2\Documents\ArcGIS\Thesis_New\Table.dbf'
field_names = ['Plan_Name', 'Plan_Nam_1', 'Plan_Nam_2', 'Plan_Nam_3']
all_values = []

with arcpy.da.SearchCursor(in_table,field_names) as cursor:
  for row in cursor:
    all_values.extend(list(row))
    
unique_values = set(all_values)
print unique_values

MarketaP

install.packages("ncdf4")
install.packages("purrr")

library(ncdf4)
library(purrr)
setwd("/Users/marketa/Library/Mobile Documents/com~apple~CloudDocs/School/Thesis")

#reading the NetCDF file and getting specific variables
f <- nc_open("20180527_1441_historic_SPI_6_month.nc")
time <- ncdf4::ncvar_get(f, varid = "time")