Create a masked frequency/contingency table

ivo_table_masked() lets you easily create pretty masked tables. If you want the table without masked values use ivo_table() instead.

Usage

ivo_table_masked(
  df,
  cell = 5,
  extra_header = TRUE,
  exclude_missing = FALSE,
  missing_string = "(Missing)",
  colsums = FALSE,
  rowsums = FALSE,
  sums_string = "Total",
  caption = NA,
  highlight_cols = NULL,
  highlight_rows = NULL,
  color = "darkgreen",
  font_name = "Arial",
  bold_cols = NULL,
  long_table = FALSE,
  remove_zero_rows = FALSE
)

Arguments

df: A data frame with 1-4 columns
cell: The largest value that will be masked. Defaults to 5, meaning that values between 1 and 5 are masked.
extra_header: Should the variable name be displayed? Defaults to TRUE.
exclude_missing: Whether to exclude missing values from the table. Defaults to FALSE.
missing_string: A string used to indicate missing values. Defaults to "(Missing)".
colsums: A logical indicating whether the sum of each column should be computed. Defaults to FALSE.
rowsums: A logical indicating whether the sum of each row should be computed. Defaults to FALSE.
sums_string: A string that is printed in the column/row where row/column sums are shown. Defaults to "Total".
caption: An optional string containing a table caption.
highlight_cols: A numeric vector containing the indices of the columns that should be highlighted.
highlight_rows: A numeric vector containing the indices of the rows that should be highlighted.
color: A named color or a color HEX code, used for the lines in the table. Defaults to "darkgreen".
font_name: The name of the font to be used in the table. Defaults to "Arial".
bold_cols: A numeric vector containing the indices of the columns that should use a bold font.
long_table: For one-way tables: FALSE (the default) means that the table will be wide and consist of a single row, TRUE means that the table will be long and consist of a single column.
remove_zero_rows: If set to TRUE, removes all rows that contain nothing but zeros. The default is FALSE.

Value

A stylized flextable.

Details

The functions ivo_table() and ivo_table_masked() takes a data.frame with 1-4 columns. The order of the columns in the data.frame will determine where they will be displayed in the table. The first column will always be displayed at the top of the table. If there are more than one column the following 2-4 columns will be displayed to the left in the order 2, 3, 4. To change how the columns are displayed in the table; change the place of the columns in the data.frame using dplyr::select().

Author

Måns Thulin and Kajsa Grind

Examples

# Generate example data
example_data <- data.frame(Year = sample(2020:2023, 50, replace = TRUE),
A = sample(c("Type 1", "Type 2"), 50, replace = TRUE),
B = sample(c("Apples", "Oranges", "Bananas"), 50, replace = TRUE),
C = sample(c("Swedish", "Norwegian", "Chilean"), 50, replace = TRUE))

### 1-way tables ###
data1 <- example_data |> dplyr::select(Year)
ivo_table_masked(data1) # No masking because all counts are >=5
Year
2020 2021 2022 2023
10 14 14 12
ivo_table_masked(data1, cell = 15) # Counts below <=15 are masked
Year
2020 2021 2022 2023
1-15 1-15 1-15 1-15

# With pipes
example_data |> dplyr::select(Year) |> ivo_table()
Year
2020 2021 2022 2023
10 14 14 12

### 2-way tables ###
data2 <- example_data |> dplyr::select(A, B)
ivo_table_masked(data2)
A
B Type 1 Type 2
Apples 9 1-5
Bananas 9 7
Oranges 9 11
ivo_table_masked(data2, cell = 7) # Counts <= 7 are masked
A
B Type 1 Type 2
Apples 9 1-7
Bananas 9 1-7
Oranges 9 11
# Row and column sums are also masked:
ivo_table_masked(
data2,
cell = 3,
colsums = TRUE,
rowsums = TRUE)
A 
B Type 1 Type 2 Total
Apples 9 5 14
Bananas 9 7 16
Oranges 9 11 20
Total 27 23 50

### 3-way tables ###
data3 <- example_data |> dplyr::select(C, B, Year)
ivo_table_masked(
data3,
cell = 3,
caption = "Values between 1 and 3 are masked."
)
Values between 1 and 3 are masked. C
B Year Chilean Norwegian Swedish
Apples 2020 1-3 1-3 0
2021 1-3 1-3 1-3
2022 1-3 4 0
2023 1-3 1-3 1-3
Bananas 2020 1-3 1-3 0
2021 1-3 1-3 1-3
2022 1-3 0 1-3
2023 1-3 1-3 1-3
Oranges 2020 1-3 1-3 1-3
2021 1-3 1-3 1-3
2022 1-3 4 0
2023 1-3 1-3 1-3

### 4-way tables ###
data4 <- example_data |> dplyr::select(Year, B, C, A)
ivo_table_masked(data4, colsums = TRUE, rowsums = TRUE)
Year 
B C A 2020 2021 2022 2023 Total
Apples Chilean Type 1 1-5 1-5 0 0 NA
Type 2 1-5 0 1-5 1-5 NA
Norwegian Type 1 1-5 1-5 1-5 1-5 NA
Type 2 0 0 1-5 0 NA
Swedish Type 1 0 1-5 0 1-5 NA
Type 2 0 0 0 0 0
Bananas Chilean Type 1 1-5 1-5 1-5 0 NA
Type 2 0 0 1-5 1-5 NA
Norwegian Type 1 1-5 1-5 0 1-5 NA
Type 2 1-5 0 0 0 NA
Swedish Type 1 0 0 1-5 1-5 NA
Type 2 0 1-5 1-5 1-5 NA
Oranges Chilean Type 1 1-5 0 1-5 1-5 NA
Type 2 0 1-5 0 1-5 NA
Norwegian Type 1 0 1-5 1-5 0 NA
Type 2 1-5 0 1-5 1-5 NA
Swedish Type 1 0 0 0 0 0
Type 2 1-5 1-5 0 1-5 NA
Total NA NA NA NA NA

	A
B	Type 1	Type 2	Total
Apples	9	5	14
Bananas	9	7	16
Oranges	9	11	20
Total	27	23	50