@ParfaitG

# BUILD DATA FRAME Radius <- 1 Horizontal_Coordinates <- seq(-Radius, Radius, 0.01) Positive_Vertical_Coordinates <- sqrt((Radius ^ 2) - (Horizontal_Coordinates ^ 2)) Negative_Vertical_Coordinates <- -sqrt((Radius ^ 2) - (Horizontal_Coordinates ^ 2)) Circle_Coordinates <- data.frame( Horizontal_Coordinates = c( Horizontal_Coordinates, rev(Horizontal_Coordinates), Horizontal_Coordinates[1]

var_wide_df <- data.frame( Var1_E1_C1 = c(1, NA, NA, 1, 1), Var1_E1_C2 = c(NA, 3, 2, NA, NA), Var23_E2_C1 = c(NA,2 , NA, 1, 1), Var23_E2_C2 = c(3,NA , 1, NA, NA) ) var_long_df <- reshape( var_wide_df,

#Set a seed set.seed(2024) #Variable declaration------------- nConds <- 2 #Number of conditions stim <- c("R", "L") #Stimulus labels pi <- c(.75, .65) #Probability of step (+1) for random walk; 1-pi will be the probability of stepping -1 diff <- c("Easy", "Hard") #Difficulty label for the condition mean_a <- c(40, 40) #Mean upper bound for each condition

from pprint import pprint from xml.dom import minidom xml = '''\ <?xml version="1.0" encoding="UTF-8"?> <env:Envelope xmlns:env="http://schema.xmlsoap.org/soap/envelope/"> <env:Body> <wd:Get_Working_Response xmlns:wd="urn:com.workway/bsvc" wd:version="v40.1"> <wd:Request_Criteria>

df <- data.frame(x=c(1, 2, NA, NA)) df$foo1[!is.na(df$x)] <- 777 df[["foo2"]][!is.na(df$x)] <- 888 `<-`(df$foo3[!is.na(df$x)], 999) `[[`(df, "foo4")[!is.na(df$x)] <- 0