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Argumentsheight either a vector or matrix of values describing the bars which make up the plot. If height is a vector, the plot consists of a sequence of rectangular bars with heights given by the values in the vector. If height is a matrix and beside is FALSE then each bar of the plot corresponds to a column of height, with the values in the column giving the heights of stacked sub-bars making up the bar. If height is a matrix and beside is TRUE, then the values in each column are juxtaposed rather than stacked.
width optional vector of bar widths. Re-cycled to length the number of bars drawn. Specifying a single value will have no visible effect unless xlim is specified.
space the amount of space (as a fraction of the average bar width) left before each bar. May be given as a single number or one number per bar. If height is a matrix and beside is TRUE, space may be specified by two numbers, where the first is the space between bars in the same group, and the second the space between the groups. If not given explicitly, it defaults to c(0,1) if height is a matrix and beside is TRUE, and to 0.2 otherwise.
names.arg a vector of names to be plotted below each bar or group of bars. If this argument is omitted, then the names are taken from the names attribute of height if this is a vector, or the column names if it is a matrix.
legend.text a vector of text used to construct a legend for the plot, or a logical indicating whether a legend should be included. This is only useful when height is a matrix. In that case given legend labels should correspond to the rows of height; if legend.text is true, the row names of height will be used as labels if they are non-null.
beside a logical value. If FALSE, the columns of height are portrayed as stacked bars, and if TRUE the columns are portrayed as juxtaposed bars.
horiz a logical value. If FALSE, the bars are drawn vertically with the first bar to the left. If TRUE, the bars are drawn horizontally with the first at the bottom.
density a vector giving the density of shading lines, in lines per inch, for the bars or bar components. The default value of NULL means that no shading lines are drawn. Non-positive values of density also inhibit the drawing of shading lines.
angle the slope of shading lines, given as an angle in degrees (counter-clockwise), for the bars or bar components.
col a vector of colors for the bars or bar components. By default, grey is used if height is a vector, and a gamma-corrected grey palette if height is a matrix.
border the color to be used for the border of the bars. Use border = NA to omit borders. If there are shading lines, border = TRUE means use the same colour for the border as for the shading lines.
main,sub overall and sub title for the plot.
xlab a label for the x axis.
ylab a label for the y axis.
xlim limits for the x axis.
ylim limits for the y axis.
xpd logical. Should bars be allowed to go outside region?
log string specifying if axis scales should be logarithmic; see plot.default.
axes logical. If TRUE, a vertical (or horizontal, if horiz is true) axis is drawn.
axisnames logical. If TRUE, and if there are names.arg (see above), the other axis is drawn (with lty = 0) and labeled.
cex.axis expansion factor for numeric axis labels.
cex.names expansion factor for axis names (bar labels).
inside logical. If TRUE, the lines which divide adjacent (non-stacked!) bars will be drawn. Only applies when space = 0 (which it partly is when beside = TRUE).
plot logical. If FALSE, nothing is plotted.
axis.lty the graphics parameter lty applied to the axis and tick marks of the categorical (default horizontal) axis. Note that by default the axis is suppressed.
offset a vector indicating how much the bars should be shifted relative to the x axis.
add logical specifying if bars should be added to an already existing plot; defaults to FALSE.
ann logical specifying if the default annotation (main, sub, xlab, ylab) should appear on the plot, see title.
args.legend list of additional arguments to pass to legend(); names of the list are used as argument names. Only used if legend.text is supplied.
formula a formula where the y variables are numeric data to plot against the categorical x variables. The formula can have one of three forms:
y ~ x y ~ x1 + x2 cbind(y1, y2) ~ x, see the examples.
data a data frame (or list) from which the variables in formula should be taken.
subset an optional vector specifying a subset of observations to be used.
na.action a function which indicates what should happen when the data contain NA values. The default is to ignore missing values in the given variables.
... arguments to be passed to/from other methods. For the default method these can include further arguments (such as axes, asp and main) and graphical parameters (see par) which are passed to plot.window(), title() and axis.
ValueA numeric vector (or matrix, when beside = TRUE), say mp, giving the coordinates of all the bar midpoints drawn, useful for adding to the graph.
If beside is true, use colMeans(mp) for the midpoints of each group of bars, see example.
Author(s)R Core, with a contribution by Arni Magnusson.
ReferencesBecker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Murrell, P. (2005) R Graphics. Chapman & Hall/CRC Press.
See Alsoplot(..., type = "h"), dotchart; hist for bars of a continuous variable. mosaicplot(), more sophisticated to visualize several categorical variables.
Examples# Formula methodbarplot(GNP ~ Year, data = longley)barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
## 3rd form of formula - 2 categories :op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))summary(d.Titanic <- as.data.frame(Titanic))barplot(Freq ~ Class + Survived, data = d.Titanic, subset = Age == "Adult" & Sex == "Male", main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend = TRUE)# Corresponding table :(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))# Alternatively, a mosaic plot :mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)par(op)
# Default methodrequire(grDevices) # for colourstN <- table(Ni <- stats::rpois(100, lambda = 5))r <- barplot(tN, col = rainbow(20))#- type = "h" plotting *is* 'bar'plotlines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE, sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)barplot(VADeaths, plot = FALSE, beside = TRUE)
mp <- barplot(VADeaths) # defaulttot <- colMeans(VADeaths)text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")barplot(VADeaths, beside = TRUE, col = c("lightblue", "mistyrose", "lightcyan", "lavender", "cornsilk"), legend = rownames(VADeaths), ylim = c(0, 100))title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]mybarcol <- "gray20"mp <- barplot(hh, beside = TRUE, col = c("lightblue", "mistyrose", "lightcyan", "lavender"), legend = colnames(VADeaths), ylim = c(0,100), main = "Death Rates in Virginia", font.main = 4, sub = "Faked upper 2*sigma error bars", col.sub = mybarcol, cex.names = 1.5)segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)stopifnot(dim(mp) == dim(hh)) # corresponding matricesmtext(side = 1, at = colMeans(mp), line = -2, text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading examplebarplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black", legend = rownames(VADeaths))title(main = list("Death Rates in Virginia", font = 4))
# Border colorbarplot(VADeaths, border = "dark blue")
# Log scales (not much sense here)barplot(tN, col = heat.colors(12), log = "y")barplot(tN, col = gray.colors(20), log = "xy")
# Legend locationbarplot(height = cbind(x = c(465, 91) / 465 * 100, y = c(840, 200) / 840 * 100, z = c(37, 17) / 37 * 100), beside = FALSE, width = c(465, 840, 37), col = c(1, 2), legend.text = c("A", "B"), args.legend = list(x = "topleft"))構造數據：
# 構造數據x <- c(100, 130, 169, 220, 286, 372, 484, 629, 818, 1063, 1382, 1797)y <- c("1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月", "12月")01 開始繪製柱形圖
1. barplot() ： 繪製一個最簡單的柱形圖：
# 1. barplot() ： 繪製一個最簡單的柱形圖barplot(x)運行結果：
2. names.arg = "" ：給每根柱子添加類別名稱：
# 2. names.arg = "" ：給每根柱子添加類別名稱barplot(x,names.arg = y)運行結果：
3. col = "" ： 把柱形圖統一改成藍色
# 3. col = "" ： 把柱形圖統一改成藍色barplot(x,names.arg = y,col = "blue")運行結果：
4. col = rainbow(數量) ： 把柱形圖改成彩虹色(注意數組下標越界)：
# 4. col = rainbow(數量) ： 把柱形圖改成彩虹色(注意數組下標越界)barplot(x,names.arg = y,col = rainbow(12))運行結果：
5. colors <- c(顏色序列）： 自定義每根柱子的顏色：
# 5. colors <- c(顏色序列） ： 自定義每根柱子的顏色colors <- c("#4E79A7", "#A0CBE8", "#F28E2B", "#FFBE7D", "#59A14F", "#8CD17D", "#B6992D", "#F1CE63", "#499894", "#86BCB6", "#E15759", "#E19D9A")barplot(x,names.arg = y,col = colors)運行結果：
6. border = "blue" ： 把邊框線顏色調為藍色
# 6. border = "blue" ： 把邊框線顏色調為藍色barplot(x,names.arg = y,col = colors,border = "blue")運行結果：
7. border = "NA" ： 為了顯得更美觀，把柱形圖的邊框線消掉
# 7. border = "NA" ： 為了顯得更美觀，把柱形圖的邊框線消掉barplot(x,names.arg = y,col = colors,border = "NA")運行結果：
8. main = "主標題名稱" ： 添加主標題
# 8. main = "主標題名稱" ： 添加主標題barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)")運行結果：
9. sub = "副標題名稱" ： 添加副標題
# 9. sub = "副標題名稱" ： 添加副標題barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢")運行結果：
10. ylab = "Y軸標籤信息" ： 給y軸加標籤
# 10. ylab = "Y軸標籤信息" ： 給y軸加標籤barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)")運行結果：
11. xlab = "X軸標籤" ： 給x軸加標籤
# 11. xlab = "X軸標籤" ： 給x軸加標籤barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份")運行結果：
12. horiz = TRUE/FASLE : 調整為水平柱形圖
# 12. horiz = TRUE/FASLE : 調整為水平柱形圖barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE)運行結果：
13. density = "數量" ： 設置底紋的密度
# 13. density 設置底紋的密度barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100)運行結果：
14. angle = "數字"： 設置底紋的斜率
# 14. angle 設置底紋的斜率barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100,angle = 30)運行結果：
15. las =0/1(縱向/橫向) ： 設置坐標軸標籤的方向
# 15. las =0/1(縱向/橫向) ： 設置坐標軸標籤的方向barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100,angle = 30,las = 1)運行結果：
16. space ="數字(值越大，間隔越大)" ： 各個條形間的寬度(間隔)
# 16. space ="數字(值越大，間隔越大)" ： 各個條形間的寬度(間隔)barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100,angle = 30,las = 1,space = 0.6)運行結果：
17. axisnames = FALSE/TRUE ： 是否顯示條形標籤
# 17. axisnames = FALSE/TRUE ： 是否顯示條形標籤barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100,angle = 30,las = 1,space = 0.6,axisnames = FALSE)運行結果：
18. legend.text = "傳參" ： 添加圖例文本
# 18. legend.text 添加圖例文本barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份", horiz = TRUE,density = 100,angle = 30,las = 1,space = 0.6,axisnames = FALSE,legend.text = x)運行結果：
19. cex.names = "數字(數值越大，字體越大)" : 控制類別名稱字體的大小
# 19. cex.names = "數字(數值越大，字體越大)" : 控制類別名稱字體的大小barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份",cex.names = 1.5)運行結果：
20. cex.axis = "數字(數值越大，字體越大)" : 控制Y軸比例尺數值的大小
# 20. cex.axis = "數字(數值越大，字體越大)" : 控制Y軸比例尺數值的大小barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份",cex.names = 1.5,cex.axis = 0.8)運行結果：
20. axisnames = FALSE ：不顯示X軸類別名稱
# 21. axisnames = FALSE ：不顯示X軸類別名稱barplot(x,names.arg = y,col = colors,border = "NA",main = "2020年各個月份的銷售額(萬元)",sub = "哈佛在等我呢",ylab = "銷量(萬元)",xlab = "月份",cex.names = 1.5,cex.axis = 0.8,axisnames = FALSE)運行結果：
若感興趣，大家可複製、粘貼以上代碼，自行學習。代碼皆源自本人去年所學，並於最近花了兩三天的時間調試、編寫出來。可見，有時候寫代碼並非都代表效率高！如本文中的操作，還不如直接使用Excel，反而更快捷，美觀度也不輸用代碼繪製。具體操作如下圖視頻及連結所示，皆由本人憑基礎親自製作，分享給大家：學習連結：
https://www.bilibili.com/video/BV11Q4y1f7VH?spm_id_from=333.999.0.0
溫馨提示：連結視頻下方評論區有模板獲取地址
溫馨提示：
視頻中Excel可視化模板的獲取連結請詳見以下連結的評論區：
https://www.bilibili.com/video/BV11Q4y1f7VH?spm_id_from=333.999.0.0
註：本文源於我平時所學，於這兩天整理、歸納、總結出來的學習筆記。因在在多數企業中，工作一般不使用R語言繪圖(Excel, Tableau, BI, 以及其它工具用得比較多。大家可自行挑選一兩款用得比較順手的工具來上手即可。在這裡，我首推Excel。一來，在各行各業的辦公崗位中，Excel的使用頻率特別高，二來，用Excel也可以製作出好看的基礎可視化圖表)，所以尚有諸多參數未能一一列舉出來。另外本人所學有限，本文只是拋磚引玉，大家如對R語言可視化感興趣，可自行參照幫助文檔進行更加全面的學習。
感謝閱讀！