Commit e18f10db by Weigert, Andreas

### Update for T02

parent cd0b2ddf
 ... ... @@ -11,6 +11,8 @@ This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M) ```{r Exercise: Mathematical calculations} 2 + 3*5^2 2^3^5 1.4e-2 1.4*exp(-2) ... ...
 ... ... @@ -7,9 +7,11 @@ editor_options: This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M), Information Systems and Energy Efficient Systems, University of Bamberg. # Part Data types ```{r Exercise: Working with lists} # Execute the code chunks of Tutorial 1 first to have the variables text, u, x, A, etc. loaded into your environment. # Exercise 27 list_data <- list(text, u, x, A) ... ... @@ -59,15 +61,16 @@ students[3,2] students\$Age # Exercise 37 students[students\$Age < 30,"Name"] # colum name as identifier students[students\$Age < 30,"Name"] # column name as identifier students[students\$Age < 30,2] # column index as identifier students[students\$Age < 30,]\$Name # get a data.frame and then select the variable by \$ operator ``` # Your first project: The shower data set ```{r Load and inspect data} # Task 1 clone git repository # Task 1 clone / pull the git repository # Task 2 # Read data. Remember the relative path ... ... @@ -151,3 +154,18 @@ write.csv2(x = Shower[Shower\$Hh_ID != 8899,], file="../../output/cleaned_shower_ After cleaning data we have stored the data to the folder "output". # Cooldown exercise ```{r Cooldown exercise} Shower <- read.csv2("../../data/Shower_data.csv") summary(Shower) Shower\$group <- as.factor(Shower\$group) Shower_one_to_ten <- Shower[Shower\$Shower %in% 1:10, ] tapply(Shower_one_to_ten\$Volume, Shower_one_to_ten\$group, mean, na.rm=T) Shower_more_than_ten <- Shower[!Shower\$Shower %in% 1:10, ] tapply(Shower_more_than_ten\$Volume, Shower_more_than_ten\$group, mean, na.rm=T) ```
 ... ... @@ -9,6 +9,8 @@ This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M) ```{r Exercise: Working with lists} # Execute the code chunks of Tutorial 1 first to have the variables text, u, x, A, etc. loaded into your environment. # Exercise 27 ... ... @@ -114,3 +116,8 @@ Nationality <- as.factor(c("DE","US","DE","SE")) After cleaning data we have stored the data to the folder "output". ```{r Cooldown exercise} ```
 ... ... @@ -6,17 +6,6 @@ editor_options: --- This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M), Information Systems and Energy Efficient Systems, University of Bamberg. ```{r Solution for Cooldown exercise} Shower <- read.csv2("../../data/Shower_data.csv") summary(Shower) Shower\$group <- as.factor(Shower\$group) Shower_one_to_ten <- Shower[Shower\$Shower %in% 1:10, ] tapply(Shower_one_to_ten\$Volume, Shower_one_to_ten\$group, mean, na.rm=T) Shower_more_than_ten <- Shower[!Shower\$Shower %in% 1:10, ] tapply(Shower_more_than_ten\$Volume, Shower_more_than_ten\$group, mean, na.rm=T) ``` ```{r Functions} ... ...
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