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mightywell_mark1.Rmd
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---
title: "R Notebook"
output:
html_document:
theme: cerulean
---
This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code.
Try executing this chunk by clicking the *Run* button within the chunk or by placing your cursor inside it and pressing *Ctrl+Shift+Enter*.
Add a new chunk by clicking the *Insert Chunk* button on the toolbar or by pressing *Ctrl+Alt+I*.
When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the *Preview* button or press *Ctrl+Shift+K* to preview the HTML file).
The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike *Knit*, *Preview* does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.
```{r setup, include=FALSE, result = 'hide'}
library(dplyr)
library(plyr)
library(reticulate)
library(tidyverse)
#setwd('D:\\DIIG\\S20\\MW')
setwd('D:\\Batcave\\DIIG\\MightyWell')
use_python("C:\\Users\\Aneesh\\Anaconda3\\python.exe")
py_run_string("import os as os")
# py_run_string("os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = 'C:/Users/Aneesh/Anaconda3/Library/plugins/platforms'")
py_run_string("os.chdir('D:/Batcave/DIIG/MightyWell')")
product_reviews_final <- read.csv("product.csv", stringsAsFactors = FALSE)
product_reviews_final2 <- read.csv("product.csv", stringsAsFactors = FALSE)
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final$product_handle[grep("shirt", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("hat", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("sticker", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("line", product_reviews_final$product_handle)] <- "picc line cover"
product_reviews_final$product_handle[grep("medplanner", product_reviews_final$product_handle)] <- "medplanner"
product_reviews_final$product_handle[grep("up", product_reviews_final$product_handle)] <- "na"
product_reviews_final$product_handle[grep("perfect", product_reviews_final$product_handle)] <- "na"
product_reviews_final$product_handle[grep("2pack", product_reviews_final$product_handle)] <- "na"
product_reviews_final <- product_reviews_final[!(product_reviews_final$product_handle == "na"), ]
product_reviews_final <- product_reviews_final[!(product_reviews_final$product_handle == ""), ]
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
#old method
product_reviews_devices <- product_reviews_final[!(product_reviews_final$device == "na"), ]
product_reviews_products_devices_count <- count(product_reviews_devices, c("product_handle", "device"))
product_reviews_products_count <-count(product_reviews_devices, vars = "product_handle")
product_reviews_devices_count<- count(product_reviews_devices, vars = "device")
product_reviews_products_devices_count$device<-sub(", ", ",", product_reviews_products_devices_count$device)
product_reviews_products_devices_count$device<-sub(", ", ",", product_reviews_products_devices_count$device)
product_reviews_products_devices_count$device<-sub(", ", ",", product_reviews_products_devices_count$device)
product_reviews_devices_count$device<-sub(", ", ",", product_reviews_devices_count$device)
product_reviews_devices_count$device<-sub(", ", ",", product_reviews_devices_count$device)
product_reviews_devices_count$device<-sub(", ", ",", product_reviews_devices_count$device)
for (i in 1:nrow(product_reviews_products_devices_count)){
if (grepl(",", product_reviews_products_devices_count$device[i])){
z <- strsplit(product_reviews_products_devices_count$device[i], ",")
for (string in z){
for (q in string){
# print(q)
indexIWanttoadd <- which(product_reviews_products_devices_count$device == q & product_reviews_products_devices_count$product_handle == product_reviews_products_devices_count$product_handle[i])
product_reviews_products_devices_count$freq[indexIWanttoadd] <- product_reviews_products_devices_count$freq[i] + product_reviews_products_devices_count$freq[indexIWanttoadd]
}
}
}
}
product_reviews_devices_count_2 <- product_reviews_devices_count
for (i in 1:nrow(product_reviews_devices_count)){
if (grepl(",", product_reviews_devices_count$device[i])){
z <- strsplit(product_reviews_devices_count$device[i], ",")
for (string in z){
for (q in string){
# print(q)
indexIWanttoadd <- which(product_reviews_devices_count$device == q)
product_reviews_devices_count$freq[indexIWanttoadd] <- product_reviews_devices_count$freq[i] + product_reviews_devices_count$freq[indexIWanttoadd]
}
}
}
}
rows = nrow(product_reviews_devices)
product_reviews_products_count[,"probability"] <- NA
product_reviews_devices_count[,"probability"] <- NA
product_reviews_products_devices_count[,"probability"] <- NA
for (i in 1:nrow(product_reviews_products_devices_count)){
product_reviews_products_devices_count$probability[i] <- product_reviews_products_devices_count$freq[i] / rows
}
for (i in 1:nrow(product_reviews_products_count)){
product_reviews_products_count$probability[i] <- product_reviews_products_count$freq[i] / rows
}
for (i in 1:nrow(product_reviews_devices_count)){
product_reviews_devices_count$probability[i] <- product_reviews_devices_count$freq[i] / rows
}
product_reviews_products_devices_count <- product_reviews_products_devices_count[!(product_reviews_products_devices_count$device == ""), ]
product_reviews_products_count <- product_reviews_products_count[!(product_reviews_products_count$product_handle == ""), ]
product_reviews_devices_count <- product_reviews_devices_count[!(product_reviews_devices_count$device == ""), ]
row.names(product_reviews_products_devices_count) <- 1:nrow(product_reviews_products_devices_count)
row.names(product_reviews_products_count) <- 1:nrow(product_reviews_products_count)
row.names(product_reviews_devices_count) <- 1:nrow(product_reviews_devices_count)
product_reviews_products_devices_count_2 <- product_reviews_products_devices_count
x <- '';
product_reviews_products_devices_count[,"Baye's"] <- NA
for (i in 1:nrow(product_reviews_products_devices_count)){
s = product_reviews_products_devices_count$device[i]
y <- sapply(s,function(s) which(apply(product_reviews_devices_count==s,1,any))[1]);
product_reviews_products_devices_count$`Baye's`[i] <- product_reviews_products_devices_count$probability[i] / product_reviews_devices_count$probability[y]
}
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final[186,17] <- "looking good/feeling proud"
product_reviews_final[5,17] <- "air travel"
product_reviews_final[223,17] <- "tube feeding"
product_reviews_final[97,17] <- "IV bandage"
product_reviews_final[97,15] <- "sensitive skin"
product_reviews_final[7,17] <- "hold medical supplies"
product_reviews_final[233,17] <- "stay warm"
product_reviews_final[137,17] <- "hold PIIC line"
product_reviews_final[35,17] <- "hold medical supplies"
product_reviews_final[132,15] <- "chemotherapy"
product_reviews_final[83,15] <- "lyme disease"
product_reviews_final[258,17] <- "wheelchair"
product_reviews_final[241,15] <- "cancer"
product_reviews_final[153,15] <- "chemotherapy"
product_reviews_final[102,17] <- "tube feeding"
product_reviews_final[206,17] <- "hold PIIC line"
product_reviews_final[244,15] <- "blood tumor"
product_reviews_final[28,15] <- "lyme disease"
product_reviews_final[28,17] <- "hold medical supplies"
product_reviews_final[230,15] <- "lyme disease"
product_reviews_final[230,17] <- "looking good/feeling proud"
product_reviews_final[248,17] <- "looking good/feeling proud"
product_reviews_final[256,17] <- "looking good/feeling proud"
product_reviews_final[191,15] <- "sensitive skin"
product_reviews_final[53,15] <- "chemotherapy"
product_reviews_final[51,15] <- "cancer"
product_reviews_final[24,17] <- "hold medical supplies"
product_reviews_final[221,15] <- "lyme disease"
product_reviews_final[192,15] <- "lyme disease"
product_reviews_final[257,15] <- "fibromyalgia"
product_reviews_final= product_reviews_final[-c(56,264,265,266),]
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final$product_handle[grep("shirt", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("hat", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("sticker", product_reviews_final$product_handle)] <- "merch"
product_reviews_final$product_handle[grep("line", product_reviews_final$product_handle)] <- "picc line cover"
product_reviews_final$product_handle[grep("medplanner", product_reviews_final$product_handle)] <- "medplanner"
product_reviews_final$product_handle[grep("up", product_reviews_final$product_handle)] <- "na"
product_reviews_final$product_handle[grep("perfect", product_reviews_final$product_handle)] <- "na"
product_reviews_final$product_handle[grep("2pack", product_reviews_final$product_handle)] <- "na"
product_reviews_final <- product_reviews_final[!(product_reviews_final$product_handle == "na"), ]
product_reviews_final <- product_reviews_final[!(product_reviews_final$product_handle == ""), ]
product_reviews_final_deice <- as.data.frame(xtabs(~ device + product_handle, product_reviews_final))
product_reviews_final_deice <- product_reviews_final_deice[!(product_reviews_final_deice$device == "na"), ]
product_reviews_final_deice[,"probability"] <- 0
product_reviews_products_count_for_deice <-count(product_reviews_final, c("product_handle","device"))
product_reviews_products_count_for_deice <- product_reviews_products_count_for_deice[!(product_reviews_products_count_for_deice$device == "na"), ]
product_reviews_products_count_for_deice <-count(product_reviews_products_count_for_deice, vars = "product_handle")
for (i in 1: nrow(product_reviews_final_deice)){
s = product_reviews_final_deice$product_handle[i]
indexIWanttoadd <- which(product_reviews_products_count_for_deice$product_handle == s)
if (length(indexIWanttoadd) == 0){
next
}
if (product_reviews_products_count_for_deice$freq[indexIWanttoadd] == 0){
next
}
product_reviews_final_deice$probability[i] <- product_reviews_final_deice$Freq[i]/product_reviews_products_count_for_deice$freq[indexIWanttoadd]
}
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final_gender <- as.data.frame(xtabs(~ gender + product_handle, product_reviews_final))
product_reviews_final_gender <- product_reviews_final_gender[!(product_reviews_final_gender$gender == "anonymous"), ]
product_reviews_final_gender[,"probability"] <- 1
product_reviews_products_count_for_gender <-count(product_reviews_final, c("product_handle","gender"))
product_reviews_products_count_for_gender <- product_reviews_products_count_for_gender[!(product_reviews_products_count_for_gender$gender == "anonymous"), ]
product_reviews_products_count_for_gender <-count(product_reviews_products_count_for_gender, vars = "product_handle")
for (i in 1: nrow(product_reviews_final_gender)){
s = product_reviews_final_gender$product_handle[i]
indexIWanttoadd <- which(product_reviews_products_count_for_gender$product_handle == s)
if (length(indexIWanttoadd) == 0){
next
}
product_reviews_final_gender$probability[i] <- product_reviews_final_gender$Freq[i]/product_reviews_products_count_for_gender$freq[indexIWanttoadd]
}
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final_condition <- as.data.frame(xtabs(~ condition + product_handle, product_reviews_final))
product_reviews_final_condition <- product_reviews_final_condition[!(product_reviews_final_condition$condition == ""), ]
product_reviews_final_condition <- product_reviews_final_condition[!(product_reviews_final_condition$condition == "na"), ]
product_reviews_final_condition <- product_reviews_final_condition[!(product_reviews_final_condition$condition == "cancer"), ]
product_reviews_final_condition[,"probability"] <- NA
product_reviews_products_count_for_final_condition <-count(product_reviews_final, c("product_handle","condition"))
product_reviews_products_count_for_final_condition <- product_reviews_products_count_for_final_condition[!(product_reviews_products_count_for_final_condition$condition == ""), ]
product_reviews_products_count_for_final_condition <- product_reviews_products_count_for_final_condition[!(product_reviews_products_count_for_final_condition$condition == "na"), ]
product_reviews_products_count_for_final_condition <- product_reviews_products_count_for_final_condition[!(product_reviews_products_count_for_final_condition$condition == "cancer"), ]
product_reviews_products_count_for_final_condition <-count(product_reviews_products_count_for_final_condition, vars = "product_handle")
for (i in 1: nrow(product_reviews_final_condition)){
s = product_reviews_final_condition$product_handle[i]
indexIWanttoadd <- which(product_reviews_products_count_for_final_condition$product_handle == s)
if (length(indexIWanttoadd) == 0){
next
}
product_reviews_final_condition$probability[i] <- product_reviews_final_condition$Freq[i]/product_reviews_products_count_for_final_condition$freq[indexIWanttoadd]
}
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
product_reviews_final_case <- as.data.frame(xtabs(~ use.case + product_handle, product_reviews_final))
product_reviews_final_case <- product_reviews_final_case[!(product_reviews_final_case$use.case == ""), ]
product_reviews_final_case <- product_reviews_final_case[!(product_reviews_final_case$use.case == "na"), ]
product_reviews_final_case[,"probability"] <- NA
product_reviews_products_count_for_final_case <-count(product_reviews_final, c("product_handle","use.case"))
product_reviews_products_count_for_final_case <- product_reviews_products_count_for_final_case[!(product_reviews_products_count_for_final_case$use.case == ""), ]
product_reviews_products_count_for_final_case <- product_reviews_products_count_for_final_case[!(product_reviews_products_count_for_final_case$use.case == "na"), ]
product_reviews_products_count_for_final_case <-count(product_reviews_products_count_for_final_case, vars = "product_handle")
for (i in 1: nrow(product_reviews_final_case)){
s = product_reviews_final_case$product_handle[i]
indexIWanttoadd <- which(product_reviews_products_count_for_final_case$product_handle == s)
if (length(indexIWanttoadd) == 0){
next
}
product_reviews_final_case$probability[i] <- product_reviews_final_case$Freq[i]/product_reviews_products_count_for_final_case$freq[indexIWanttoadd]
}
product_reviews_final_case <- product_reviews_final_case[!is.na(product_reviews_final_case$probability), ]
```
```{r echo = FALSE, message=FALSE, result = 'hide'}
#write.csv(product_reviews_final_gender, "afinal_final_product_reviews_final_gender.csv")
#write.csv(product_reviews_final_condition, "afinal_final_product_reviews_final_condition.csv")
#write.csv(product_reviews_final_case, "afinal_final_product_reviews_final_case.csv")
#write.csv(product_reviews_final_deice, "final_final_product_reviews_products_devices_count.csv")
```
<!-- Useful documentation for R <-> Python variable exchange: -->
<!-- https://rstudio.github.io/reticulate/ -->
```{python message=FALSE, echo = FALSE}
print("Starting Python script...")
```
```{python message=FALSE}
import pandas as pd
# This code can be hidden as well, like previous code blocks
gender = pd.read_csv('D:/Batcave/DIIG/MightyWell/final_final_product_reviews_final_gender.csv')
#getting information on gender analysis
condition = pd.read_csv("D:/Batcave/DIIG/MightyWell/final_final_product_reviews_final_condition.csv")
#getting information on medical condition analysis
case = pd.read_csv("D:/Batcave/DIIG/MightyWell/final_final_product_reviews_final_case.csv")
#getting information on case use analysis
device = pd.read_csv("D:/Batcave/DIIG/MightyWell/final_final_product_reviews_products_devices_count.csv")
# input() doesn't work in RMarkdown. So I added specific strings for now.
# gender_input = input("Please either either male or female: ") #stores gender
gender_input = "male"
# condition_input = input("Please input what condition you have: ") #stores medical condition
condition_input = "lyme disease"
# case_input = input("Please input what function you desire from the device: ") #stores user need
case_input = "holding picc line"
# device_input = input("Please input what device you want to replace: ") #stores user previous device
device_input = "med planner"
score_medplanner = 0
score_mighty_pages = 0
score_merch = 0
score_picc_line_cover = 0
score_the_mighty_wrap = 0
score_medical_iv_fusion_backpack = 0
condition['probability'] = condition['probability'] * 0.4
case['probability'] = case['probability'] * 0.3
device['probability'] = device['probability'] * 0.2
gender['probability'] = gender['probability'] * 0.1
def summing(stringinput, scoreinput, ):
global score_medplanner, score_mighty_pages, score_merch, score_picc_line_cover, score_the_mighty_wrap, score_medical_iv_fusion_backpack
if (stringinput == "medical-iv-infusion-backpack-for-patients"):
score_medical_iv_fusion_backpack += scoreinput
if (stringinput == "medplanner"):
score_medplanner += scoreinput
if (stringinput == "merch"):
score_merch += scoreinput
if (stringinput == "mighty-pages"):
score_mighty_pages += scoreinput
if (stringinput == "picc line cover"):
score_picc_line_cover += scoreinput
if (stringinput == "the-mighty-wrap"):
score_the_mighty_wrap += scoreinput
def max_score():
global score_medplanner, score_mighty_pages, score_merch, score_picc_line_cover, score_the_mighty_wrap, score_medical_iv_fusion_backpack
max_val = max(score_medplanner, score_mighty_pages, score_merch, score_picc_line_cover, score_the_mighty_wrap, score_medical_iv_fusion_backpack)
if (max_val == score_medplanner):
print ("The best device to use is the medplanner")
if (max_val == score_mighty_pages):
print ("The best device to use is the mighty pages")
if (max_val == score_merch):
print ("The best device to use is the merch")
if (max_val == score_picc_line_cover):
print ("The best device to use is the picc line cover")
if (max_val == score_the_mighty_wrap):
print ("The best device to use is the mighty wrap")
if (max_val == score_medical_iv_fusion_backpack):
print ("The best device to use is the medical iv infusion backpack")
product_devices = ["medical-iv-infusion-backpack-for-patients", "medplanner", "merch", "mighty-pages", "picc line cover", "the-mighty-wrap"]
score = 0.0 #temp value that changes
for string in product_devices:
if condition_input in condition['condition'].unique() : #first checking if user input is in the database for condition
index_of_condition = condition.index[(condition['condition'] == condition_input) & (condition['product_handle'] == string)].tolist()[0] #getting the index of the condiiton and device to find its probability
score = condition['probability'][index_of_condition] #getting probability of the two conditions above
summing(string, score) #adding the probability above to the scores of each device
else:
score = 0.0
if case_input in case['use.case'].unique(): #repeating above for use case
index_of_condition = case.index[(case['use.case'] == case_input) & (case['product_handle'] == string)].tolist()[0]
score = case['probability'][index_of_condition]
summing(string, score)
else:
score = 0.0
if gender_input in gender['gender'].unique(): #repeating above for gender
index_of_condition = gender.index[(gender['gender'] == gender_input) & (gender['product_handle'] == string)].tolist()[0]
score = gender['probability'][index_of_condition]
summing(string, score)
else:
score = 0.0
if device_input in device['device'].unique(): #repeating above for previous device
index_of_condition = device.index[(device['device'] == device_input) & (device['product_handle'] == string)].tolist()[0]
score = device['probability'][index_of_condition]
summing(string, score)
else:
score = 0.0
max_score()
```