search for: mealb

Thanks Boris , this was very helpful but I'm struggling with the last part. 1) I combined the first 2 columns :- library(tidyr) SingleMealsCode <-unite(MyData, 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$MealsCo...

...Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > Thanks Boris , this was very helpful but I'm struggling with the last part. > > 1) I combined the first 2 columns :- > > > library(tidyr) > SingleMealsCode <-unite(MyData, 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(SingleM...

...15 PM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > Thanks Boris , this was very helpful but I'm struggling with the last part. > > 1) I combined the first 2 columns :- > > > library(tidyr) > SingleMealsCode <-unite(MyData, 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(SingleMea...

...ail.com> wrote: >> >> >> Thanks Boris , this was very helpful but I'm struggling with the last part. >> >> 1) I combined the first 2 columns :- >> >> >> library(tidyr) >> SingleMealsCode <-unite(MyData, 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 : >> >> SeparatedGroupsofmealsCom...

...hotmail.com> wrote: >> >> >> Thanks Boris , this was very helpful but I'm struggling with the last part. >> >> 1) I combined the first 2 columns :- >> >> >> library(tidyr) >> SingleMealsCode <-unite(MyData, 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...

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

...>>> >>> Thanks Boris , this was very helpful but I'm struggling with the last part. >>> >>> 1) I combined the first 2 columns :- >>> >>> >>> library(tidyr) >>> SingleMealsCode <-unite(MyData, 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 : >>> >>> S...

...>>> >>> Thanks Boris , this was very helpful but I'm struggling with the last part. >>> >>> 1) I combined the first 2 columns :- >>> >>> >>> library(tidyr) >>> SingleMealsCode <-unite(MyData, 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 : >>> >>> S...

...t; > >> Thanks Boris , this was very helpful but I'm struggling with the last part. > >> > >> 1) I combined the first 2 columns :- > >> > >> > >> library(tidyr) > >> SingleMealsCode <-unite(MyData, 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 : > >> > >...

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