Many of you still are not using markdown effectively.
All of you are correctly putting R code into code blocks, otherwise your R code wouldn’t run when you knit the file.
But, some people are writing long responses as comments inside code chunks.
Many other people aren’t using the formatting tools correctly outside the code chunks.
Make sure you look at your knit file and make sure it is easy to read!
Show example
Pay careful attention to the way you use headings in Rmarkdown.
## is the main section level heading### is the sub-section level heading#### is for the sub-sub-section level headingThe key point is, think about the structure of the document, and use the headings consistently.
These get used when you use a table of contents for your document.
---
title: "My Document"
output:
html_document:
toc: yes
toc_float: yes
---
R Studio projects are the way to keep everything associated with a project separate and portable.
You create a new project using File > New Project
You can create a project associated with a new folder (i.e. directory) or you can associate new project with an existing folder
a new R session (process) is started (variable names from other projects are gone)
The current working directory is set to the project directory.
Previously edited scripts/markdown files documents are restored into editor tabs
other things
Since the working directory is the same as the project directory, you can refer to files using relative paths, and they will work on anyone’s computer.
Lets say my project has a folder called “Datasets”….you can use this relative path
read.table("./Datasets/myFile.txt")
Note: the . and the ~ characters are super useful when using relative file paths….what do they mean?
By default when you print a dataframe to a markdown document, it doesn’t look that great.
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb ## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 ## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 ## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 ## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 ## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 ## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
library(pander) pander(mtcars, split.tables = 200)
| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mazda RX4 | 21 | 6 | 160 | 110 | 3.9 | 2.62 | 16.46 | 0 | 1 | 4 | 4 |
| Mazda RX4 Wag | 21 | 6 | 160 | 110 | 3.9 | 2.875 | 17.02 | 0 | 1 | 4 | 4 |
| Datsun 710 | 22.8 | 4 | 108 | 93 | 3.85 | 2.32 | 18.61 | 1 | 1 | 4 | 1 |
| Hornet 4 Drive | 21.4 | 6 | 258 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 |
| Hornet Sportabout | 18.7 | 8 | 360 | 175 | 3.15 | 3.44 | 17.02 | 0 | 0 | 3 | 2 |
| Valiant | 18.1 | 6 | 225 | 105 | 2.76 | 3.46 | 20.22 | 1 | 0 | 3 | 1 |
| Duster 360 | 14.3 | 8 | 360 | 245 | 3.21 | 3.57 | 15.84 | 0 | 0 | 3 | 4 |
| Merc 240D | 24.4 | 4 | 146.7 | 62 | 3.69 | 3.19 | 20 | 1 | 0 | 4 | 2 |
| Merc 230 | 22.8 | 4 | 140.8 | 95 | 3.92 | 3.15 | 22.9 | 1 | 0 | 4 | 2 |
| Merc 280 | 19.2 | 6 | 167.6 | 123 | 3.92 | 3.44 | 18.3 | 1 | 0 | 4 | 4 |
| Merc 280C | 17.8 | 6 | 167.6 | 123 | 3.92 | 3.44 | 18.9 | 1 | 0 | 4 | 4 |
| Merc 450SE | 16.4 | 8 | 275.8 | 180 | 3.07 | 4.07 | 17.4 | 0 | 0 | 3 | 3 |
| Merc 450SL | 17.3 | 8 | 275.8 | 180 | 3.07 | 3.73 | 17.6 | 0 | 0 | 3 | 3 |
| Merc 450SLC | 15.2 | 8 | 275.8 | 180 | 3.07 | 3.78 | 18 | 0 | 0 | 3 | 3 |
| Cadillac Fleetwood | 10.4 | 8 | 472 | 205 | 2.93 | 5.25 | 17.98 | 0 | 0 | 3 | 4 |
| Lincoln Continental | 10.4 | 8 | 460 | 215 | 3 | 5.424 | 17.82 | 0 | 0 | 3 | 4 |
| Chrysler Imperial | 14.7 | 8 | 440 | 230 | 3.23 | 5.345 | 17.42 | 0 | 0 | 3 | 4 |
| Fiat 128 | 32.4 | 4 | 78.7 | 66 | 4.08 | 2.2 | 19.47 | 1 | 1 | 4 | 1 |
| Honda Civic | 30.4 | 4 | 75.7 | 52 | 4.93 | 1.615 | 18.52 | 1 | 1 | 4 | 2 |
| Toyota Corolla | 33.9 | 4 | 71.1 | 65 | 4.22 | 1.835 | 19.9 | 1 | 1 | 4 | 1 |
| Toyota Corona | 21.5 | 4 | 120.1 | 97 | 3.7 | 2.465 | 20.01 | 1 | 0 | 3 | 1 |
| Dodge Challenger | 15.5 | 8 | 318 | 150 | 2.76 | 3.52 | 16.87 | 0 | 0 | 3 | 2 |
| AMC Javelin | 15.2 | 8 | 304 | 150 | 3.15 | 3.435 | 17.3 | 0 | 0 | 3 | 2 |
| Camaro Z28 | 13.3 | 8 | 350 | 245 | 3.73 | 3.84 | 15.41 | 0 | 0 | 3 | 4 |
| Pontiac Firebird | 19.2 | 8 | 400 | 175 | 3.08 | 3.845 | 17.05 | 0 | 0 | 3 | 2 |
| Fiat X1-9 | 27.3 | 4 | 79 | 66 | 4.08 | 1.935 | 18.9 | 1 | 1 | 4 | 1 |
| Porsche 914-2 | 26 | 4 | 120.3 | 91 | 4.43 | 2.14 | 16.7 | 0 | 1 | 5 | 2 |
| Lotus Europa | 30.4 | 4 | 95.1 | 113 | 3.77 | 1.513 | 16.9 | 1 | 1 | 5 | 2 |
| Ford Pantera L | 15.8 | 8 | 351 | 264 | 4.22 | 3.17 | 14.5 | 0 | 1 | 5 | 4 |
| Ferrari Dino | 19.7 | 6 | 145 | 175 | 3.62 | 2.77 | 15.5 | 0 | 1 | 5 | 6 |
| Maserati Bora | 15 | 8 | 301 | 335 | 3.54 | 3.57 | 14.6 | 0 | 1 | 5 | 8 |
| Volvo 142E | 21.4 | 4 | 121 | 109 | 4.11 | 2.78 | 18.6 | 1 | 1 | 4 | 2 |
So you can pass model objects, summaries, etc
pander(lm(mpg~wt, data=mtcars))
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 37.29 | 1.878 | 19.86 | 8.242e-19 |
| wt | -5.344 | 0.5591 | -9.559 | 1.294e-10 |
pander(chisq.test(mtcars$cyl))
| Test statistic | df | P value |
|---|---|---|
| 15.98 | 31 | 0.9881 |
pander(anova(lm(mpg~cyl, data=mtcars)))
| Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
|---|---|---|---|---|---|
| cyl | 1 | 817.7 | 817.7 | 79.56 | 6.113e-10 |
| Residuals | 30 | 308.3 | 10.28 | NA | NA |
pander(summary(prcomp(mtcars)))
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | |
|---|---|---|---|---|---|---|
| mpg | -0.03812 | 0.009185 | 0.9821 | 0.04763 | -0.08833 | -0.1438 |
| cyl | 0.01204 | -0.003372 | -0.06348 | -0.228 | 0.2387 | -0.7938 |
| disp | 0.8996 | 0.4354 | 0.03144 | -0.005087 | -0.01074 | 0.007424 |
| hp | 0.4348 | -0.8993 | 0.02509 | 0.03572 | 0.01655 | 0.001654 |
| drat | -0.00266 | -0.0039 | 0.03972 | -0.05713 | -0.1333 | 0.2272 |
| wt | 0.006239 | 0.004861 | -0.08491 | 0.128 | -0.2435 | -0.1271 |
| qsec | -0.006671 | 0.02501 | -0.07167 | 0.8865 | -0.2142 | -0.1896 |
| vs | -0.002729 | 0.002198 | 0.004203 | 0.1771 | -0.01689 | 0.1026 |
| am | -0.001963 | -0.005794 | 0.05481 | -0.1357 | -0.0627 | 0.2052 |
| gear | -0.002605 | -0.01127 | 0.04852 | -0.1299 | -0.2762 | 0.335 |
| carb | 0.005766 | -0.02778 | -0.1029 | -0.2689 | -0.8552 | -0.2838 |
| PC7 | PC8 | PC9 | PC10 | PC11 | |
|---|---|---|---|---|---|
| mpg | -0.03924 | 0.02271 | -0.00279 | 0.03063 | -0.01586 |
| cyl | 0.425 | -0.189 | 0.04268 | 0.1317 | 0.1454 |
| disp | 0.0005824 | -0.0005841 | 0.003533 | -0.005399 | 0.000942 |
| hp | -0.002213 | 4.748e-06 | -0.003734 | 0.001863 | -0.002153 |
| drat | 0.03485 | -0.9386 | -0.01413 | 0.1841 | -0.09738 |
| wt | -0.1866 | 0.1562 | -0.3906 | 0.8299 | -0.01986 |
| qsec | 0.2548 | -0.1029 | -0.09591 | -0.2042 | 0.01107 |
| vs | -0.08079 | -0.002133 | 0.684 | 0.3031 | 0.6257 |
| am | 0.2009 | -0.02273 | -0.5724 | -0.1628 | 0.7332 |
| gear | 0.8016 | 0.2175 | 0.1561 | 0.2035 | -0.1909 |
| carb | -0.1655 | 0.003972 | 0.1276 | -0.24 | 0.0558 |
| PC1 | PC2 | PC3 | PC4 | PC5 | |
|---|---|---|---|---|---|
| Standard deviation | 136.5 | 38.15 | 3.071 | 1.307 | 0.9065 |
| Proportion of Variance | 0.927 | 0.07237 | 0.00047 | 8e-05 | 4e-05 |
| Cumulative Proportion | 0.927 | 0.9994 | 0.9998 | 0.9999 | 1 |
| PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | |
|---|---|---|---|---|---|---|
| Standard deviation | 0.6635 | 0.3086 | 0.286 | 0.2507 | 0.2107 | 0.1984 |
| Proportion of Variance | 2e-05 | 0 | 0 | 0 | 0 | 0 |
| Cumulative Proportion | 1 | 1 | 1 | 1 | 1 | 1 |
Create a new project called “test” associated wit a new directory. Open the project, then create a markdown document that has three sections. Make sure your document has a table of contents. Knit it to be sure that it works.