Creation of a barchart object that can be inserted in a 'Microsoft' document.
Bar charts illustrate comparisons among individual items. In a bar chart, the categories are typically organized along the vertical axis, and the values along the horizontal axis.
Consider using a bar chart when:
The axis labels are long.
The values that are shown are durations.
Arguments
- data
a data.frame
- x
column name for x values.
- y
column name for y values.
- group
grouping column name used to split data into series. Optional.
- labels
column names of columns to be used as custom data labels displayed next to data points (not axis labels). Optional. If more than one name is provided, only the first one will be used as a label, but all labels (transposed if a group is used) will be available in the Excel file associated with the chart.
- asis
logical parameter defaulting to FALSE. When FALSE, the data is reshaped internally so that each series becomes a separate column. When TRUE, the data is used as-is and must already have one column for categories and one column per series, and
yaccepts a vector of series column names.asisdescribes the input shape read by the constructor. Not to be confused with thewrite_dataargument ofsheet_add_drawing.ms_chart(), which controls whethermschartwrites the chart's data into an Excel sheet at embed time. The two are independent.
See also
chart_settings(), chart_ax_x(), chart_ax_y(),
chart_data_labels(), chart_theme(), chart_labels()
Other 'Office' chart objects:
ms_areachart(),
ms_boxplotchart(),
ms_bubblechart(),
ms_chart_combine(),
ms_funnelchart(),
ms_histogramchart(),
ms_linechart(),
ms_paretochart(),
ms_piechart(),
ms_radarchart(),
ms_scatterchart(),
ms_stockchart(),
ms_sunburstchart(),
ms_treemapchart(),
ms_waterfallchart()
Examples
library(officer)
library(mschart)
library(officer)
# example chart 01 -------
chart_01 <- ms_barchart(
data = browser_data, x = "browser",
y = "value", group = "serie"
)
chart_01 <- chart_settings(
x = chart_01, dir = "vertical",
grouping = "clustered", gap_width = 50
)
chart_01 <- chart_ax_x(
x = chart_01, cross_between = "between",
major_tick_mark = "out"
)
chart_01 <- chart_ax_y(
x = chart_01, cross_between = "midCat",
major_tick_mark = "in"
)
# print(chart_01, preview = TRUE)
# example chart 02 -------
dat <- data.frame(
Species = factor(c("setosa", "versicolor", "virginica"),
levels = c("setosa", "versicolor", "virginica")
),
mean = c(5.006, 5.936, 6.588)
)
chart_02 <- ms_barchart(data = dat, x = "Species", y = "mean")
chart_02 <- chart_settings(x = chart_02, dir = "horizontal")
chart_02 <- chart_theme(x = chart_02, title_x_rot = 270, title_y_rot = 0)
# print(chart_02, preview = TRUE)
# example chart 03 -------
mytheme <- mschart_theme(
axis_title_x = fp_text(color = "gray", font.size = 20, bold = TRUE),
axis_title_y = fp_text(color = "gray", font.size = 20, italic = TRUE),
grid_major_line_y = fp_border(width = 1, color = "wheat"),
axis_ticks_y = fp_border(width = 1, color = "gray")
)
chart_03 <- ms_barchart(
data = browser_data, x = "browser",
y = "value", group = "serie"
)
chart_03 <- chart_settings(chart_03,
grouping = "stacked",
gap_width = 150, overlap = 100
)
chart_03 <- chart_ax_x(chart_03,
cross_between = "between",
major_tick_mark = "out", minor_tick_mark = "none"
)
chart_03 <- chart_ax_y(chart_03,
num_fmt = "0.00",
minor_tick_mark = "none"
)
chart_03 <- set_theme(chart_03, mytheme)
chart_03 <- chart_labels(x = chart_03, title = "Things in percent")
chart_03 <- chart_data_labels(chart_03,
position = "ctr",
show_val = TRUE
)
chart_03 <- chart_labels_text(chart_03,
fp_text(color = "white", bold = TRUE, font.size = 9)
)
chart_03 <- chart_data_fill(chart_03,
values = c(
serie1 = "#4477AA",
serie2 = "#CC6677",
serie3 = "#DDCC77"
)
)
chart_03 <- chart_data_stroke(chart_03,
values = c(
serie1 = "#223B55",
serie2 = "#66333C",
serie3 = "#6F663C"
)
)
chart_03 <- chart_data_line_width(chart_03,
values = c(serie1 = 2, serie2 = 2, serie3 = 2)
)
# print(chart_03, preview = TRUE)
# example chart 04 -------
dat_groups <-
data.frame(
cut = c(
"Fair", "Fair", "Fair", "Fair", "Fair",
"Fair", "Fair", "Fair", "Good", "Good", "Good", "Good", "Good",
"Good", "Good", "Good", "Very Good", "Very Good", "Very Good",
"Very Good", "Very Good", "Very Good", "Very Good", "Very Good",
"Premium", "Premium", "Premium", "Premium", "Premium",
"Premium", "Premium", "Premium", "Ideal", "Ideal", "Ideal", "Ideal",
"Ideal", "Ideal", "Ideal", "Ideal"
),
clarity = c(
"I1", "SI2", "SI1", "VS2", "VS1", "VVS2",
"VVS1", "IF", "I1", "SI2", "SI1", "VS2", "VS1", "VVS2", "VVS1",
"IF", "I1", "SI2", "SI1", "VS2", "VS1", "VVS2", "VVS1", "IF",
"I1", "SI2", "SI1", "VS2", "VS1", "VVS2", "VVS1", "IF", "I1",
"SI2", "SI1", "VS2", "VS1", "VVS2", "VVS1", "IF"
),
carat = c(
1.065, 1.01, 0.98, 0.9, 0.77, 0.7, 0.7,
0.47, 1.07, 1, 0.79, 0.82, 0.7, 0.505, 0.4, 0.46, 1.145, 1.01,
0.77, 0.71, 0.7, 0.4, 0.36, 0.495, 1.11, 1.04, 0.9, 0.72, 0.7,
0.455, 0.4, 0.36, 1.13, 1, 0.71, 0.53, 0.53, 0.44, 0.4, 0.34
),
n = c(
210L, 466L, 408L, 261L, 170L, 69L, 17L, 9L,
96L, 1081L, 1560L, 978L, 648L, 286L, 186L, 71L, 84L, 2100L,
3240L, 2591L, 1775L, 1235L, 789L, 268L, 205L, 2949L, 3575L, 3357L,
1989L, 870L, 616L, 230L, 146L, 2598L, 4282L, 5071L, 3589L,
2606L, 2047L, 1212L
)
)
dat_groups$label <- sprintf(
"carat median is %.01f",
dat_groups$carat
)
dat_groups
#> cut clarity carat n label
#> 1 Fair I1 1.065 210 carat median is 1.1
#> 2 Fair SI2 1.010 466 carat median is 1.0
#> 3 Fair SI1 0.980 408 carat median is 1.0
#> 4 Fair VS2 0.900 261 carat median is 0.9
#> 5 Fair VS1 0.770 170 carat median is 0.8
#> 6 Fair VVS2 0.700 69 carat median is 0.7
#> 7 Fair VVS1 0.700 17 carat median is 0.7
#> 8 Fair IF 0.470 9 carat median is 0.5
#> 9 Good I1 1.070 96 carat median is 1.1
#> 10 Good SI2 1.000 1081 carat median is 1.0
#> 11 Good SI1 0.790 1560 carat median is 0.8
#> 12 Good VS2 0.820 978 carat median is 0.8
#> 13 Good VS1 0.700 648 carat median is 0.7
#> 14 Good VVS2 0.505 286 carat median is 0.5
#> 15 Good VVS1 0.400 186 carat median is 0.4
#> 16 Good IF 0.460 71 carat median is 0.5
#> 17 Very Good I1 1.145 84 carat median is 1.1
#> 18 Very Good SI2 1.010 2100 carat median is 1.0
#> 19 Very Good SI1 0.770 3240 carat median is 0.8
#> 20 Very Good VS2 0.710 2591 carat median is 0.7
#> 21 Very Good VS1 0.700 1775 carat median is 0.7
#> 22 Very Good VVS2 0.400 1235 carat median is 0.4
#> 23 Very Good VVS1 0.360 789 carat median is 0.4
#> 24 Very Good IF 0.495 268 carat median is 0.5
#> 25 Premium I1 1.110 205 carat median is 1.1
#> 26 Premium SI2 1.040 2949 carat median is 1.0
#> 27 Premium SI1 0.900 3575 carat median is 0.9
#> 28 Premium VS2 0.720 3357 carat median is 0.7
#> 29 Premium VS1 0.700 1989 carat median is 0.7
#> 30 Premium VVS2 0.455 870 carat median is 0.5
#> 31 Premium VVS1 0.400 616 carat median is 0.4
#> 32 Premium IF 0.360 230 carat median is 0.4
#> 33 Ideal I1 1.130 146 carat median is 1.1
#> 34 Ideal SI2 1.000 2598 carat median is 1.0
#> 35 Ideal SI1 0.710 4282 carat median is 0.7
#> 36 Ideal VS2 0.530 5071 carat median is 0.5
#> 37 Ideal VS1 0.530 3589 carat median is 0.5
#> 38 Ideal VVS2 0.440 2606 carat median is 0.4
#> 39 Ideal VVS1 0.400 2047 carat median is 0.4
#> 40 Ideal IF 0.340 1212 carat median is 0.3
text_prop <- fp_text(font.size = 11, color = "gray")
chart_04 <- ms_barchart(
data = dat_groups, x = "cut",
labels = "label", y = "n", group = "clarity"
)
chart_04 <- chart_settings(chart_04,
grouping = "clustered", dir = "horizontal",
gap_width = 0
)
chart_04 <- chart_data_labels(chart_04, position = "outEnd")
chart_04 <- chart_labels_text(chart_04, text_prop)
chart_04 <- chart_theme(chart_04, title_x_rot = 270, title_y_rot = 0)
# print(chart_04, preview = TRUE)
# example chart 05 -------
dat_no_group <- data.frame(
stringsAsFactors = FALSE,
cut = c("Fair", "Good", "Very Good", "Premium", "Ideal"),
carat = c(1, 0.82, 0.71, 0.86, 0.54),
n = c(1610L, 4906L, 12082L, 13791L, 21551L),
label = c(
"carat median is 1.0",
"carat median is 0.8", "carat median is 0.7",
"carat median is 0.9", "carat median is 0.5"
)
)
chart_05 <- ms_barchart(
data = dat_no_group,
x = "cut", labels = "label", y = "n"
)
chart_05 <- chart_settings(chart_05,
grouping = "clustered"
)
chart_05 <- chart_data_labels(chart_05, position = "outEnd")
chart_05 <- chart_labels_text(chart_05, text_prop)
# print(chart_05, preview = TRUE)
# example chart 06 -------
chart_06 <- ms_barchart(
data = dat_no_group,
x = "cut", labels = "label", y = "n"
)
chart_06 <- chart_settings(chart_06,
grouping = "clustered", table = TRUE
)
chart_06 <- chart_data_labels(chart_06, position = "outEnd")
chart_06 <- chart_labels_text(chart_06, text_prop)
# print(chart_06, preview = TRUE)
# example chart 07 -------
# Series order (and therefore legend order) follows the levels of
# the `group` factor. Convert the column to a factor with the desired
# level order before passing it to ms_barchart().
ordered_data <- browser_data
ordered_data$serie <- factor(ordered_data$serie,
levels = c("serie3", "serie1", "serie2")
)
chart_07 <- ms_barchart(
data = ordered_data, x = "browser",
y = "value", group = "serie"
)
chart_07 <- chart_labels(chart_07,
title = "Series and legend ordered via factor levels"
)
# print(chart_07, preview = TRUE)
# example chart 08 -------
# Wide-format input: each series is its own column. Pass the series
# column names as a vector in `y` and set `asis = TRUE`.
browser_wide <- data.frame(
browser = unique(browser_data$browser),
serie1 = browser_data$value[browser_data$serie == "serie1"],
serie2 = browser_data$value[browser_data$serie == "serie2"],
serie3 = browser_data$value[browser_data$serie == "serie3"]
)
chart_08 <- ms_barchart(
data = browser_wide,
x = "browser",
y = c("serie1", "serie2", "serie3"),
asis = TRUE
)
# print(chart_08, preview = TRUE)