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Articles by Nizamuddin Siddiqui
Page 125 of 196
Convert list with varying number of elements into a data frame.
To convert list with varying number of elements into a data frame in R, we can use stri_list2matrix function of stringi package along with as.data.frame function.For Example, if we have a list called LIST that contains varying number of elements then we can convert it into a data frame by using the below mentioned command −as.data.frame(t(stri_list2matrix(LIST)))Example 1Following snippet creates a sample list −List1
Read MoreHow to multiply vector values in sequence with matrix columns in R?
To multiply vector values in sequence with matrix columns in R, we can follow the below steps −First of all, create a matrix.Then, create a vector.After that, use t function for transpose and multiplication sign * to multiply vector values in sequence with matrix columns.ExampleCreate the data frameLet’s create a data frame as shown below −M
Read MoreHow to find the frequency of each value in an R data frame?
To find the frequency of each value in an R data frame, we can use table function along with unlist function.For Example, if we have a data frame called df and we want to find the frequency of each value in df then we can use the below command −table(unlist(df))Example 1Following snippet creates a sample data frame −x1
Read MoreHow to convert alphabets to numbers in data.table object in R?
To convert alphabets to numbers in data.table object in R, we can follow the below steps −First of all, create a data.table object.Then, use mutate_each function of dplyr package along with chartr function to convert alphabets to numbers.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) v1
Read MoreHow to find the percentage of values that lie within a range in R data frame column?
To find the percentage of values that lie within a range in R data frame column, we can follow the below steps −First of all, create a data frame.Then, use sum function along with extreme values for range and length function to find the percentage of values that lie within that range.ExampleCreate the data frameLet’s create a data frame as shown below −Var
Read MoreHow to find the total by year column in an R data frame?
To find the total by year column in an R data frame, we can use aggregate function with sum function.For Example, if we have a data frame called df that contains a year colmn say Year and a numerical column say Demand then we can find the total Demand by Year with the help of command given below −aggregate(df["Demand"],by=df["Year"],sum)Example 1Following snippet creates a sample data frame −Year
Read MoreHow to standardize selected columns in data.table object in R?
To standardize selected columns in data.table object in R, we can follow the below steps −First of all, create a data.table object.Then, use scale function and cbind function with subsetting to standardize selected columns.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) var1
Read MoreHow to save a matrix as CSV file using R?
To save a matrix as CSV file using R, we can use write.matrix function of MASS package. For Example, if we have a matrix called M and we want to save it as CSV file then we can use the below mentioned command −write.matrix(M,file="Mat.csv")ExampleFollowing snippet creates a sample matrix −M
Read MoreHow to subset an R data frame by specifying columns that contains NA?
To subset an R data frame by specifying columns that contains NA, we can follow the below steps −First of all, create a data frame with some columns containing NAs.Then, use is.na along with subset function to subset the data frame by specifying columns that contains NA.ExampleCreate the data frameLet’s create a data frame as shown below −x
Read MoreFind the common elements between two columns of an R dataframe.
To find the common elements between two columns of an R data frame, we can use intersect function.For Example, if we have a data frame called df that contains two columns say X and Y then we can find the common elements between X and Y by using the below command −intersect(df$X,df$Y)Example 1Following snippet creates a sample data frame −x1
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