draft of RDD analysis
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mjgaughan
parent
9bf6755f84
commit
c3106bd83c
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R/.Rhistory
536
R/.Rhistory
@ -1,271 +1,3 @@
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qqnorm(octo_data$issue_mmt)
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qqnorm(log(octo_data$issue_mmt))
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qqnorm(residuals(octo_data$issue_mmt))
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qqnorm(octo_data$issue_mmt)
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qqnorm(log(octo_data$issue_mmt))
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qqnorm(octo_data$issue_mmt)
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hist(log(octo_data$issue_mmt))
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hist(sqrt(octo_data$issue_mmt))
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#below are the models for the octo data, there should be analysis for each one
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octo_mmtmodel1 <- lm(underproduction_mean ~ mmt + new.age.factor, data=octo_data)
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summary(octo_mmtmodel1)
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#below are the models for the octo data, there should be analysis for each one
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octo_mmtmodel1 <- lm(underproduction_mean ~ mmt + new.age.factor, data=octo_data)
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summary(octo_mmtmodel1)
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# below this is the analysis for the octo data
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octo_data$new.age <- as.numeric(cut(octo_data$age_of_project/365, breaks=c(0,7.524197,10.323056,13.649367,17), labels=c(1,2,3,4)))
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table(octo_data$new.age)
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octo_data$new.age.factor <- as.factor(octo_data$new.age)
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hist(octo_data$new.age)
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#below are the models for the octo data, there should be analysis for each one
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octo_mmtmodel1 <- lm(underproduction_mean ~ mmt + new.age.factor, data=octo_data)
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summary(octo_mmtmodel1)
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hist(sqrt(octo_data$issue_mmt))
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hist(sqrt(octo_data$issue_mmt))
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hist(octo_data$issue_mmt)
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#right skewed data, need to transform
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library(rcompanion)
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install.packages(rcompanion)
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hist(sqrt(octo_data$issue_mmt))
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qqnorm(1/octo_data$issue_mmt)
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hist(1/octo_data$issue_mmt)
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hist(log(octo_data$issue_mmt))
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hist(sqrt(octo_data$issue_mmt))
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hist(log(octo_data$issue_mmt))
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octo_data$sqrt_issue_mmt <- sqrt(octo_data$issue_mmt)
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sqrt_issue_mmtmodel1 <- lm(underproduction_mean ~ sqrt_issue_mmt + new.age.factor, data=octo_data)
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summary(sqrt_issue_mmtmodel1)
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summary(issue_mmtmodel1)
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octo_data$wiki_mmt <- ((octo_data$wiki_contrib_count * 2) + (octo_data$total_contrib - octo_data$wiki_contrib_count)) / (octo_data$total_contrib)
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hist(octo_data$wiki_mmt)
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wiki_mmtmodel1 <- lm(underproduction_mean ~ wiki_mmt + new.age.factor, data=octo_data)
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summary(wiki_mmtmodel1)
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g3 <- ggplot(octo_data, aes(wiki_mmt)) + geom_histogram(binwidth = 5)
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g3
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g3 <- ggplot(octo_data, aes(wiki_mmt)) + geom_histogram(binwidth = 0.05)
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g3
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g3 <- ggplot(octo_data, aes(wiki_mmt)) + geom_histogram(binwidth = 0.05) + theme_bw()
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g3
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g3 <- ggplot(octo_data, aes(wiki_mmt)) + geom_histogram(binwidth = 0.01) + theme_bw()
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g3
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g2 <- ggplot(octo_data, aes(issue_mmt)) + geom_histogram(binwidth = 0.01) + theme_bw()
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g2
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g1 <- ggplot(octo_data, aes(sqrt_issue_mmt)) + geom_histogram(binwidth = 0.01) + theme_bw()
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g1
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g3 <- ggplot(octo_data, aes(wiki_mmt)) + geom_histogram(binwidth = 0.01) + theme_bw()
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g3
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g2 <- ggplot(octo_data, aes(issue_mmt)) + geom_histogram(binwidth = 0.01) + theme_bw()
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g2
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texreg(list(octo_mmtmodel1, issue_mmtmodel1, wiki_mmtmodel1), stars=NULL, digits=2,
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custom.model.names=c( 'M1: augm. formality','M2: MMT', 'M3: milestones' ),
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custom.coef.names=c('(Intercept)', 'Augmented formality', 'MMT', 'Age-2', 'Age-3', 'Age-4', 'Milestones'),
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use.packages=FALSE, table=FALSE, ci.force = TRUE)
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source('powerAnalysis.R') #my little "lib"
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texreg(list(octo_mmtmodel1, issue_mmtmodel1, wiki_mmtmodel1), stars=NULL, digits=2,
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custom.model.names=c( 'M1: augm. formality','M2: MMT', 'M3: milestones' ),
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custom.coef.names=c('(Intercept)', 'Augmented formality', 'MMT', 'Age-2', 'Age-3', 'Age-4', 'Milestones'),
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use.packages=FALSE, table=FALSE, ci.force = TRUE)
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library(texreg) #my little "lib"
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texreg(list(octo_mmtmodel1, issue_mmtmodel1, wiki_mmtmodel1), stars=NULL, digits=2,
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custom.model.names=c( 'M1: augm. formality','M2: MMT', 'M3: milestones' ),
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custom.coef.names=c('(Intercept)', 'Augmented formality', 'MMT', 'Age-2', 'Age-3', 'Age-4', 'Milestones'),
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use.packages=FALSE, table=FALSE, ci.force = TRUE)
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texreg(list(octo_mmtmodel1, issue_mmtmodel1, wiki_mmtmodel1), stars=NULL, digits=2,
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custom.model.names=c( 'M1: MMT','M2: issue contrib.', 'M3: wiki_contrib.' ),
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custom.coef.names=c('(Intercept)', 'MMT', 'Issues', 'Age-2', 'Age-3', 'Age-4', 'Wiki'),
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use.packages=FALSE, table=FALSE, ci.force = TRUE)
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glimpse(readme_df)
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library(tidyverse)
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
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glimpse(readme_df)
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head(readme_df)
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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glimpse(readme_df)
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "after_all_cnt", "before_mrg_cnt", "after_mrg_cnt", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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readme_df <- readme_df[,col_order]
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glimpse(readme_df)
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#TODO: turn character type into vector of numbers
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str_split(test, ", ")
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test <- "[0, 0, 0, 0]"
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#TODO: turn character type into vector of numbers
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str_split(test, ", ")
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#TODO: turn character type into vector of numbers
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str_split(gsub("[][]","", test), ", ")
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readme_df %>% add_column(cnt_before_all = str_split(gsub("[][]","", before_all_count), ", "))
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readme_df %>% mutate(cnt_before_all = str_split(gsub("[][]","", before_all_count), ", "))
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readme_df %>% mutate("cnt_before_all" = str_split(gsub("[][]","", "before_all_count"), ", "))
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head(readme_df$before_all_cnt)
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head(readme_df$cnt_before_all)
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readme_df %>% mutate(cnt_before_all = str_split(gsub("[][]","", "before_all_count"), ", "))
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head(readme_df$cnt_before_all)
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View(readme_df)
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View(readme_df)
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readme_df$cnt_before_all
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readme_df %>% mutate(cnt_before_all = str_split(gsub("[][]","", "before_all_count"), ", "))
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str_split(gsub("[][]","", readme_df$before_all_count), ", ")
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#str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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readme_df %>% mutate(cnt_before_all = str_split(gsub("[][]","", "before_all_cnt"), ", "))
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readme_df$cnt_before_all
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#str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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readme_df %>% mutate("cnt_before_all" = str_split(gsub("[][]","", "before_all_cnt"), ", "))
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readme_df$cnt_before_all
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str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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readme_df$cnt_before_all <- str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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readme_df$cnt_before_all
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readme_df$cnt_after_all <- str_split(gsub("[][]","", readme_df$after_all_cnt), ", ")
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readme_df$cnt_after_all
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readme_df$cnt_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_cnt), ", ")
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readme_df$cnt_before_mrg
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readme_df$cnt_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_cnt), ", ")
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readme_df$cnt_after_mrg
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#TODO: figure out if one needs to expand the data into a different dataframe, and if so how
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readme_df <- subset(readme_df, select = -c("before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt"))
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drop <- c("before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt")
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readme_df = readme_df[,!(names(readme_df) %in% drop)]
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View(readme_df)
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library(tidyverse)
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "after_all_cnt", "before_mrg_cnt", "after_mrg_cnt", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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readme_df <- readme_df[,col_order]
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glimpse(readme_df)
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readme_df$cnt_before_all <- str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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readme_df$cnt_before_all <- as.numeric(readme_df$cnt_before_all)
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View(readme_df)
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readme_df$cnt_before_all
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type(readme_df$cnt_before_all)
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typeof(readme_df$cnt_before_all)
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typeof(readme_df$cnt_before_all[0])
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readme_df$cnt_before_all <- unlist(str_split(gsub("[][]","", readme_df$before_all_cnt), ", "))
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readme_df$cnt_before_all <- str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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typeof(readme_df$cnt_before_all)
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typeof(readme_df$cnt_before_all[[0]])
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typeof(readme_df$cnt_before_all[0])
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sapply(readme_df, class)
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readme_df[,lapply(readme_df, unlist)]
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readme_df[,lapply(readme_df$cnt, unlist)]
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readme_df[,lapply(readme_df$cnt_before_all, unlist)]
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typeof(readme_df$cnt_before_all[0])
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View(readme_df)
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View(readme_df)
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readme_df$cnt_before_all <- as.numeric(str_split(gsub("[][]","", readme_df$before_all_cnt), ", "))
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readme_df$cnt_before_all <- as.numeric(str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")[[1]])
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readme_df$cnt_before_all <- str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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typeof(readme_df$cnt_before_all[0])
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typeof(readme_df$cnt_before_all[0][0])
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readme_df$cnt_before_all[0]
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unlist(readme_df$cnt_before_all[0])
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readme_df$cnt_before_all[0]
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readme_df$cnt_before_all
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test <- readme_df$cnt_before_all
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test
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as.numeric(test)
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test[0]
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test[1]
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as.numeric(test[1])
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unlist(test[1])
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as.numeric(unlist(test[1]))
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test2 <- as.numeric(unlist(test))
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test2
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print(entry)
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for (entry in test) {
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print(entry)
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}
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print(as.numeric(unlist(entry)))
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for (entry in test) {
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print(as.numeric(unlist(entry)))
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}
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test_two <- append(test_two, as.numeric(unlist(entry)))
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print(as.numeric(unlist(entry)))
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for (entry in test) {
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test_two <- append(test_two, as.numeric(unlist(entry)))
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print(as.numeric(unlist(entry)))
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}
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test_two <- c()
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for (entry in test) {
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test_two <- append(test_two, as.numeric(unlist(entry)))
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print(as.numeric(unlist(entry)))
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}
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readme_df$cnt_before_all <- as.numeric(readme_df$cnt_before_all)
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test_two
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readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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iterator <- 0
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for (entry in test) {
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readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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print(as.numeric(unlist(entry)))
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iterator <- iterator + 1
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}
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View(readme_df)
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library(tidyverse)
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_cnt", "after_all_cnt", "before_mrg_cnt", "after_mrg_cnt", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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readme_df <- readme_df[,col_order]
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glimpse(readme_df)
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head(readme_df)
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#this has to happen on the analysis side of things for a given row, it cannot happen on the storage side
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#this is a conversation of whether or not the data should be saved in terms of
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readme_df$cnt_before_all <- str_split(gsub("[][]","", readme_df$before_all_cnt), ", ")
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# test <- readme_df$cnt_before_all
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# as.numeric(unlist(test[1]))
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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readme_df$cnt_after_all <- str_split(gsub("[][]","", readme_df$after_all_cnt), ", ")
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readme_df$cnt_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_cnt), ", ")
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readme_df$cnt_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_cnt), ", ")
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drop <- c("before_all_cnt", "before_mrg_cnt", "after_all_cnt", "after_mrg_cnt")
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readme_df = readme_df[,!(names(readme_df) %in% drop)]
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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new_test <- head(readme_df, 1)
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View(new_test)
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write.csv(readme_df, "r_readme_did.csv", row.names=FALSE)
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# as.numeric(unlist(test[1]))
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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new_test <- head(readme_df, 1)
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View(new_test)
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longer <- new_test |>
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pivot_longer(cols = starts_with("cnt"),
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names_to = "window",
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values_to = "count"))
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longer <- new_test |>
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pivot_longer(cols = starts_with("cnt"),
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names_to = "window",
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values_to = "count")
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longer
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View(longer)
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longer |> unnest(count)
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new_longer <- longer |> unnest(count)
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View(new_longer)
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longer
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View(new_longer)
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longer <- new_test |>
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pivot_longer(cols = starts_with("cnt"),
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names_to = "window",
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values_to = "count") |>
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unnest(as.numeric(unlist(count)))
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longer
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longer <- new_test |>
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pivot_longer(cols = starts_with("cnt"),
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names_to = "window",
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values_to = "count") |>
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@ -510,3 +242,271 @@ longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, le
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View(longer)
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head(longer)
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sapply(longer, class)
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library(plyr)
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library(tidyverse)
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
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#preprocessing for readme_df
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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readme_df <- readme_df[,col_order]
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readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ")
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readme_df$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
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readme_df$ct_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_ct), ", ")
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readme_df$ct_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_ct), ", ")
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drop <- c("before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct")
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readme_df = readme_df[,!(names(readme_df) %in% drop)]
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# as.numeric(unlist(test[1]))
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- head(readme_df, 1)
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
View(longer)
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == all)] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all")] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
View(readme_df)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[5,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
View(readme_df)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[76,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[77,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[143,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[185,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
# as.numeric(unlist(test[1]))
|
||||
# test_two <- c()
|
||||
# iterator <- 0
|
||||
# for (entry in test) {
|
||||
# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
|
||||
# print(as.numeric(unlist(entry)))
|
||||
# iterator <- iterator + 1
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- readme_df[231,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
lm(count ~ D + I(week - 26)) |>
|
||||
summary()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
lm(count ~ D * I(week - 26)) |>
|
||||
summary()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
lm(formula = count ~ D * I(week - 26)) |>
|
||||
summary()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(method = "lm")
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(method = "lm")
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(aes(x = week, y = count, color = D))
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth()
|
||||
sapply(longer, class)
|
||||
longer$count <- as.numeric(longer$count)
|
||||
sapply(longer, class)
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
lm(formula = count ~ D * I(week - 26)) |>
|
||||
summary()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth()
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(se = False)
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(se = FALSE)
|
||||
|
||||
0
R/didAnalysis.R
Normal file
0
R/didAnalysis.R
Normal file
@ -32,7 +32,7 @@ readme_df = readme_df[,!(names(readme_df) %in% drop)]
|
||||
# }
|
||||
# test_two
|
||||
#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
|
||||
new_test <- head(readme_df, 1)
|
||||
new_test <- readme_df[231,]
|
||||
longer <- new_test |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
@ -40,3 +40,24 @@ longer <- new_test |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
|
||||
#sapply(longer, class)
|
||||
|
||||
#testing out analysis below
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
ggplot(aes(x = week, y = count)) +
|
||||
geom_point() +
|
||||
geom_vline(xintercept = 26)
|
||||
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0)) |>
|
||||
lm(formula = count ~ D * I(week - 26)) |>
|
||||
summary()
|
||||
|
||||
longer[which(longer$observation_type == "all"),] |>
|
||||
select(count, week) |>
|
||||
mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
|
||||
ggplot(aes(x = week, y = count, color = D)) +
|
||||
geom_point() +
|
||||
geom_smooth(se = FALSE)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user