insertcols#

Purpose#

Inserts one or more new columns into a matrix or dataframe at a specified location.

Format#

X_expand = insertcols(X, idx, new_cols)#

Parameters:

X (Matrix or dataframe) – Data.
idx (Scalar, string or vector) – The index after which to insert the new columns. This may be an integer index or a string variable name.
new_cols (Scalar, string or vector) – The new columns to insert into X.

Returns:

X_expand (Matrix or dataframe) – Equal to input X with the new columns added after the position indicated by input idx.

Examples#

Example 1: Basic matrix usage#

X = { 1  2  3  4,
      5  6  7  8,
      9 10 11 12 };

new_cols = { 22 33,
             44 55,
             66 77 };

// Insert 'new_cols' ater column 2
X_expand = insertcols(X, 2, new_cols);

After the above code:

           1    2   22   33    3    4
X_expand = 5    6   44   55    7    8
           9   10   66   77   11   12

Example 2: Add a constant term to a matrix#

X = { 1  2  3  4,
      5  6  7  8,
      9 10 11 12 };

// Create vector for constant
const = ones(rows(X), 1);

// Insert after '0' column
idx = 0;

// Insert 'const' vector
X_expand = insertcols(X, idx, const);

After the above code:

           1    1    2    3    4
X_expand = 1    5    6    7    8
           1    9   10   11   12

insertcols() will expand a scalar to fill the new column, so the code below will also add a column of ones to the front of a matrix.

// Insert after '0' column
idx = 0;

// Specify scalar 1 to insert
const = 1;

// Expands scalar 'const'
// to match size of X and insert at
// beginning of matrix
X_expand = insertcols(X, idx, const);

Example 3: Add an indicator variable to a dataframe#

In this example we will create an indicator variable to show whether the original data in one of our columns contained a missing value or not. Then we will impute this value and insert the new column using a variable name as the index.

// Load 3 variables from the dataset
auto = loadd(getGAUSSHome("examples/auto2.dta"), "make + mpg + rep78");

print auto[1:7,.];

         make            mpg          rep78
  AMC Concord             22        Average
    AMC Pacer             17        Average
   AMC Spirit             22              .
Buick Century             20        Average
Buick Electra             15           Good
Buick LeSabre             18        Average
   Buick Opel             26              .

// Create an indicator variable to show whether
// 'rep78'  observations are missing
rep78_miss = auto[.,"rep78"] .== miss();

// Add a variable name to our indicator variable
rep78_miss = asdf(rep78_miss, "rep78_miss");

// Replace the missing values of 'rep78' with the mode
auto[.,"rep78"] = impute(auto[.,"rep78"], "mode");

// Add the indicator variable after 'mpg'
auto = insertcols(auto, "mpg", rep78_miss);

print auto[1:7,.];

         make            mpg     rep78_miss          rep78
  AMC Concord             22              0        Average
    AMC Pacer             17              0        Average
   AMC Spirit             22              1        Average
Buick Century             20              0        Average
Buick Electra             15              0           Good
Buick LeSabre             18              0        Average
   Buick Opel             26              1        Average