library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(dplyr)
library(readr)


##Read CSV, filter for FUEL 1 ONLY
read.csv("Case 3 and 4.csv")
##           X       NH3     CO2.Equi          CO      CH4      NO2       NOx
## 1 Fuel 1 C1 569309948 4.209020e+12 25145583260 77679539 24787354 163451219
## 2 Fuel 1 C2 564876943 4.158600e+12 25045065500 77108254 24681961 162727135
## 3 Fuel 2 C1    231225 4.281772e+09    65033792   208665   163748    868813
## 4 Fuel 2 C2    231225 4.281772e+09    65033792   208665   163748    868813
## 5 Fuel 5 C1    305806 2.141918e+09    14432938   107688    14897     97922
## 6 Fuel 5 C2    305806 2.141918e+09    14432938   107688    14897     97922
## 7 Fuel 9 C1         0 0.000000e+00           0        0        0         0
## 8 Fuel 9 C2         0 0.000000e+00           0        0        0         0
##   Total.PM10 Total.PM2.5 Brake.PM10 Tire.PM10 Brake.PM2.5 Tire.PM2.5      SO2
## 1   26436351    23386104  338501490 131513722    42312670   19726956 21267348
## 2   26276721    23244894  334268184 129868962    41783496   19480250 21012590
## 3      35390       32560     255749     99362       31972      14910    14310
## 4      35390       32560     255749     99362       31972      14910    14310
## 5      14990       13253     173203     67288       21650      10093    16492
## 6      14990       13253     173203     67288       21650      10093    16492
## 7          0           0  140953264  54762784    17619152    8214380        0
## 8          0           0  145186636  56407528    18148332    8461086        0
##   X.1       X.2 Total.Energy  Total.HC X.3       X.4    Distance
## 1  NA Fuel 1 C1  5.79170e+16 895665794  NA Fuel 1 C1 15417615884
## 2  NA Fuel 1 C2  5.72232e+16 892024074  NA Fuel 1 C2 15224795608
## 3  NA Fuel 2 C1  5.77525e+13    614553  NA Fuel 2 C1    11648541
## 4  NA Fuel 2 C2  5.77525e+13    614553  NA Fuel 2 C2    11648541
## 5  NA Fuel 5 C1  3.01113e+13    544127  NA Fuel 5 C1     7888795
## 6  NA Fuel 5 C2  3.01113e+13    544127  NA Fuel 5 C2     7888795
## 7  NA Fuel 9 C1  8.67326e+15         0  NA Fuel 9 C1  6419949052
## 8  NA Fuel 9 C2  8.91187e+15         0  NA Fuel 9 C2  6612763182
data <- read.csv("Case 3 FC2040.csv")
filtered_data <- data %>% filter(Fuel.Type == 1)

# Select columns from "NH3" to the end
nh3_col_index <- which(colnames(filtered_data) == "NH3")
selected_data <- filtered_data[, nh3_col_index:ncol(filtered_data)]

# Calculate the sum of each column
sums <- colSums(selected_data, na.rm = TRUE)

# Create a new row with the sums
new_row <- as.data.frame(t(sums))
colnames(new_row) <- colnames(selected_data)

# Add NA values for the columns before "NH3"
new_row1 <- cbind(data.frame(matrix(NA, nrow = 1, ncol = nh3_col_index - 1)), new_row)
colnames(new_row)[1:(nh3_col_index - 1)] <- colnames(data)[1:(nh3_col_index - 1)]

# Bind the new row to the original data
new_data <- bind_rows(data, new_row1)

view(new_row1)
#--------------
filtered_data <- data %>% filter(Fuel.Type == 2)

# Select columns from "NH3" to the end
nh3_col_index <- which(colnames(filtered_data) == "NH3")
selected_data <- filtered_data[, nh3_col_index:ncol(filtered_data)]

# Calculate the sum of each column
sums <- colSums(selected_data, na.rm = TRUE)

# Create a new row with the sums
new_row2 <- as.data.frame(t(sums))
colnames(new_row) <- colnames(selected_data)

# Add NA values for the columns before "NH3"
new_row1 <- cbind(data.frame(matrix(NA, nrow = 1, ncol = nh3_col_index - 1)), new_row)
colnames(new_row)[1:(nh3_col_index - 1)] <- colnames(data)[1:(nh3_col_index - 1)]

# Bind the new row to the original data
new_data <- bind_rows(data, new_row2)

view(new_row2)