```
# NOT RUN {
set.seed(101)
### Single data frame
X = matrix(rnorm(20), 10, 2)
X3 = sample(letters[1:3], 10, replace = TRUE)
X4 = sample(LETTERS[1:3], 10, replace = TRUE)
df = data.frame(X, X3, X4)
makeX(df)
makeX(df, sparse = TRUE)
### Single data freame with missing values
Xn = X
Xn[3, 1] = NA
Xn[5, 2] = NA
X3n = X3
X3n[6] = NA
X4n = X4
X4n[9] = NA
dfn = data.frame(Xn, X3n, X4n)
makeX(dfn)
makeX(dfn, sparse = TRUE)
makeX(dfn, na.impute = TRUE)
makeX(dfn, na.impute = TRUE, sparse = TRUE)
### Test data as well
X = matrix(rnorm(10), 5, 2)
X3 = sample(letters[1:3], 5, replace = TRUE)
X4 = sample(LETTERS[1:3], 5, replace = TRUE)
dft = data.frame(X, X3, X4)
makeX(df, dft)
makeX(df, dft, sparse = TRUE)
### Missing data in test as well
Xn = X
Xn[3, 1] = NA
Xn[5, 2] = NA
X3n = X3
X3n[1] = NA
X4n = X4
X4n[2] = NA
dftn = data.frame(Xn, X3n, X4n)
makeX(dfn, dftn)
makeX(dfn, dftn, sparse = TRUE)
makeX(dfn, dftn, na.impute = TRUE)
makeX(dfn, dftn, sparse = TRUE, na.impute = TRUE)
# }
```

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