search for: singlemealcode

...ta, MealsCombinations, c(MealA, MealB), remove=FALSE) SingleMealsCode <- SingleMealsCode[,-2] 2) I separated this dataframe into different dataframes based on "MealsCombination" column so R will recognize each meal combination separately : SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see a list of different databases, each of which represents a different Meal combinations which is great. No, I'm struggling with the last part, how can I run the maf code fo...

..., MealB), remove=FALSE) > SingleMealsCode <- SingleMealsCode[,-2] > > 2) I separated this dataframe into different dataframes based on "MealsCombination" > column so R will recognize each meal combination separately : > > SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) > > after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see > a list of different databases, each of which represents a different Meal combinations which is great. > > No, I'm struggling with the last part, how...

...lA, MealB), remove=FALSE) > SingleMealsCode <- SingleMealsCode[,-2] > > 2) I separated this dataframe into different dataframes based on "MealsCombination" > column so R will recognize each meal combination separately : > > SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) > > after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see > a list of different databases, each of which represents a different Meal combinations which is great. > > No, I'm struggling with the last part, how ca...

...) >> SingleMealsCode <- SingleMealsCode[,-2] >> >> 2) I separated this dataframe into different dataframes based on "MealsCombination" >> column so R will recognize each meal combination separately : >> >> SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) >> >> after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see >> a list of different databases, each of which represents a different Meal combinations which is great. >> >> No, I'm struggling with...

...SE) >> SingleMealsCode <- SingleMealsCode[,-2] >> >> 2) I separated this dataframe into different dataframes based on "MealsCombination" >> column so R will recognize each meal combination separately : >> >> SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) >> >> after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see >> a list of different databases, each of which represents a different Meal combinations which is great. >> >> No, I'm struggling with t...

Combine columns 1 and 2 into a column with a single ID like "33.55", "44.66" and use split() on these IDs to break up your dataset. Iterate over the list of data frames split() returns. B. > On Nov 17, 2017, at 12:59 PM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > Hi all .., > > > I have a large dataset of around 600,000 rows and 600

...lsCode <- SingleMealsCode[,-2] >>> >>> 2) I separated this dataframe into different dataframes based on "MealsCombination" >>> column so R will recognize each meal combination separately : >>> >>> SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) >>> >>> after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see >>> a list of different databases, each of which represents a different Meal combinations which is great. >>> >>> No, I'...

...lsCode <- SingleMealsCode[,-2] >>> >>> 2) I separated this dataframe into different dataframes based on "MealsCombination" >>> column so R will recognize each meal combination separately : >>> >>> SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) >>> >>> after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see >>> a list of different databases, each of which represents a different Meal combinations which is great. >>> >>> No, I'...

...e <- SingleMealsCode[,-2] > >> > >> 2) I separated this dataframe into different dataframes based on "MealsCombination" > >> column so R will recognize each meal combination separately : > >> > >> SeparatedGroupsofmealsCombs <- split(SingleMealCode,SingleMealCode$MealsCombinations) > >> > >> after investigating the structure of "SeparatedGroupsofmealsCombs" , I can see > >> a list of different databases, each of which represents a different Meal combinations which is great. > >> > >> No...

Hi all .., I have a large dataset of around 600,000 rows and 600 columns. The first col is codes for Meal A, the second columns is codes for Meal B. The third column is customers IDs where each customer had a combination of meals. Each column of the rest columns contains values 0,1,or 2. The dataset is organised in a way so that the first group of customers had similar meals combinations, this