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library(ggplot2) | |
library(shiny) | |
library(gganimate) | |
library(XML) | |
library(lubridate) | |
library(tidyverse) | |
library(shinydashboard) | |
library(shinythemes) | |
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sub_4<- train %>% | |
filter(.,no_of_trainings==2) %>% | |
select(.,department,education,gender,is_promoted) | |
head(sub_4) |
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library(tidyverse) | |
sub_3 <- train %>% | |
select(.,department,education,gender,is_promoted,no_of_trainings) %>% | |
filter(.,no_of_trainings==2) | |
head(sub_3) |
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sub_2 <- train[which(train$no_of_trainings == 2),names(train) %in% | |
c("department","education","gender","is_promoted")] | |
head(sub_2) |
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train <- read.csv("~/Analytics Vidhya/HR analytics/train_LZdllcl.csv", header=T) | |
head(train) | |
#subset first few rows and columns | |
sub <- train[1:5000,1:6] | |
head(sub) |
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# assign column names | |
colnames(x) <- c("A", "B", "C") | |
x | |
#subset using the names | |
x[,c('A')] | |
#using the subset function | |
subset(x,select=c('A')) |
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x <- matrix(1:6,nrow=2,ncol=3) | |
x | |
#selecting an element | |
x[1,1] | |
#selecting just one row | |
x[2,] | |
# selecting one or more columns |
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x <-c(10,12,23,45,84,25,15,56,09) | |
#selecting one element | |
x[1] | |
#selecting multiple elements | |
x[c(3,9)] | |
#dropping certain elements | |
x[-c(1,2)] |
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data<- data.frame(variable1 = rep(LETTERS[1:3], each = 3), | |
variable2 = rep(paste0("factor", c(1, 2, 3)), 3), | |
num = 1:9) | |
head(data) | |
spread(data,variable2,num) | |
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x <- "AnaLytics VidHya 001" | |
str_to_lower(x) | |
str_to_upper(x) |
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