Advent of Code is back! Unwrap daily challenges to sharpen your Alteryx skills and earn badges along the way! Learn more now.

Alteryx Designer Desktop Discussions

Find answers, ask questions, and share expertise about Alteryx Designer Desktop and Intelligence Suite.

connect to tableau

chaitanyaiys
7 - Meteor

connect to tableau

10 REPLIES 10
chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("C:\\Users\\NATHDWAR\\Desktop\\1.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(start_word[i]) + 1, stop = nchar(data$C[start_pos]) - nchar(stop_word[i]) - 1)
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)

chaitanyaiys
7 - Meteor

# Load required libraries
library(readxl)
library(dplyr)

# Read data from Excel files
file1 <- read_excel("path_to_file1.xlsx")
file2 <- read_excel("path_to_file2.xlsx")

# Perform the join based on a common constraint
joined_data <- inner_join(file1, file2, by = "common_column_name")

# common_column_name should be replaced with the actual column name that is common between the two files

# View the joined data
print(joined_data)

chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(start_word[i]) + 1, stop = nchar(data$C[start_pos]) - nchar(stop_word[i]) - 2)
} else if (start_word[i] == "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[stop_pos], start = 1, stop = nchar(data$C[stop_pos]) - nchar(stop_word[i]) - 2)
} else if (stop_word[i] == "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(start_word[i]) + 1, stop = nchar(data$C[start_pos]))
}
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)

chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(start_word[i]) + 1, stop = nchar(data$C[start_pos]) - nchar(stop_word[i]) - 2)
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[stop_pos], start = 1, stop = nchar(data$C[stop_pos]) - nchar(stop_word[i]) - 2)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(start_word[i]) + 1, stop = nchar(data$C[start_pos]))
}
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)

chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(as.character(start_word[i])) + 1, stop = nchar(data$C[start_pos]) - nchar(as.character(stop_word[i])) - 2)
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[stop_pos], start = 1, stop = nchar(data$C[stop_pos]) - 1)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(as.character(start_word[i])) + 1, stop = nchar(data$C[start_pos]))
}
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)

chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(as.character(start_word[i])) + 1, stop = nchar(data$C[start_pos]) - nchar(as.character(stop_word[i])) - 2)
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(data$C[stop_pos], start = 1, stop = nchar(data$C[stop_pos]) - 1)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(data$C[start_pos], start = nchar(as.character(start_word[i])) + 1, stop = nchar(data$C[start_pos]))
}
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)

 

 

now1

chaitanyaiys
7 - Meteor

# Load required library
library(readxl)

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Function to extract values from column "C"
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(as.character(data$C[start_pos]), start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])) - nchar(as.character(stop_word[i])) - 2)
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(as.character(data$C[stop_pos]), start = 1, stop = nchar(as.character(data$C[stop_pos])) - 1)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(as.character(data$C[start_pos]), start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])))
}
}
return(result)
}

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)
print(values)
now 2

chaitanyaiys
7 - Meteor

# Load required libraries
library(readxl)
library(openxlsx)

# Function to extract values from column "C" and include all original columns
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(as.character(data$C[start_pos]), start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])) - nchar(as.character(stop_word[i])) - 2)
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(as.character(data$C[stop_pos]), start = 1, stop = nchar(as.character(data$C[stop_pos])) - 1)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(as.character(data$C[start_pos]), start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])))
}
}
# Create a data frame with all original columns and the extracted values
result_df <- cbind(data, Extracted_Values = result)
return(result_df)
}

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)

# Write data to a new Excel file
write.xlsx(values, "output_file.xlsx")

chaitanyaiys
7 - Meteor

# Load required libraries
library(readxl)
library(openxlsx)

# Function to extract values from column "C" and include all original columns
extract_values <- function(start_word, stop_word, data) {
result <- character(length(start_word))
for (i in seq_along(start_word)) {
if (!is.na(start_word[i]) & !is.na(stop_word[i]) & start_word[i] != "" & stop_word[i] != "") {
start_pos <- which(data$A == start_word[i])
stop_pos <- which(data$B == stop_word[i])
if (length(start_pos) > 0 & length(stop_pos) > 0 & stop_pos > start_pos) {
result[i] <- substr(data$C[start_pos], start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])) - nchar(as.character(stop_word[i])) - 2)
} else {
result[i] <- NA
}
} else if (is.na(start_word[i]) & !is.na(stop_word[i]) & stop_word[i] != "") {
# Get all words before stop word
stop_pos <- which(data$B == stop_word[i])
result[i] <- substr(as.character(data$C[stop_pos]), start = 1, stop = nchar(as.character(data$C[stop_pos])) - 1)
} else if (!is.na(start_word[i]) & is.na(stop_word[i]) & start_word[i] != "") {
# Get all words after start word
start_pos <- which(data$A == start_word[i])
result[i] <- substr(as.character(data$C[start_pos]), start = nchar(as.character(start_word[i])) + 1, stop = nchar(as.character(data$C[start_pos])))
}
}
# Create a data frame with all original columns and the extracted values
result_df <- cbind(data, Extracted_Values = result)
return(result_df)
}

# Read data from Excel file
data <- read_excel("path_to_your_excel_file.xlsx")

# Example usage
start_words <- data$A
stop_words <- data$B
values <- extract_values(start_words, stop_words, data)

# Write data to a new Excel file
write.xlsx(values, "output_file.xlsx")

now 3

Labels