Reproducible programming
General rules
the scripts should be written in a way, that either you, or someone else will be able to run it anytime.
Clean structure, according to the best programming practices
Variable names according the convention (use _. not " " or -, don’t use keywords)
spaces before and after
Indentation
curly brackets
don’t store unnecessary objects
avoid repetition
comment your codes in detail
Use sessionInfo() to know your package versions
Use as generalized code as possible - use names and regular expressions instead of indices.
if possible, define your paths at the beginning and use paste() or file.path() later. Or use relative paths
try to do everything from R, because changes in e.g. excel are undocumented.
Rmarkdown, R notebooks
- Rmarkdown document, with code chuncks
- Markdown language is easy to learn, see the cheatsheat
- many templates available - flexible themes
- Description, codes and figures at the same place.
- Figures are saved separately as well - or use links
- Appearance of the code depends on the chunk options.
Show code and output
plot(cars)
Show only output
Show code only, don’t run
plot(cars)- Suppress warnings and messages, if needed.
- Use cheatsheets
- easy to add pictures, links, etc.
- easy to add nice tables
##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, union| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mazda RX4 | 21.0 | 6 | 160.0 | 110 | 3.90 | 2.620 | 16.46 | 0 | 1 | 4 | 4 |
| Mazda RX4 Wag | 21.0 | 6 | 160.0 | 110 | 3.90 | 2.875 | 17.02 | 0 | 1 | 4 | 4 |
| Datsun 710 | 22.8 | 4 | 108.0 | 93 | 3.85 | 2.320 | 18.61 | 1 | 1 | 4 | 1 |
| Hornet 4 Drive | 21.4 | 6 | 258.0 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 |
| Hornet Sportabout | 18.7 | 8 | 360.0 | 175 | 3.15 | 3.440 | 17.02 | 0 | 0 | 3 | 2 |
| Valiant | 18.1 | 6 | 225.0 | 105 | 2.76 | 3.460 | 20.22 | 1 | 0 | 3 | 1 |
| Duster 360 | 14.3 | 8 | 360.0 | 245 | 3.21 | 3.570 | 15.84 | 0 | 0 | 3 | 4 |
| Merc 240D | 24.4 | 4 | 146.7 | 62 | 3.69 | 3.190 | 20.00 | 1 | 0 | 4 | 2 |
| Merc 230 | 22.8 | 4 | 140.8 | 95 | 3.92 | 3.150 | 22.90 | 1 | 0 | 4 | 2 |
| Merc 280 | 19.2 | 6 | 167.6 | 123 | 3.92 | 3.440 | 18.30 | 1 | 0 | 4 | 4 |
| Merc 280C | 17.8 | 6 | 167.6 | 123 | 3.92 | 3.440 | 18.90 | 1 | 0 | 4 | 4 |
| Merc 450SE | 16.4 | 8 | 275.8 | 180 | 3.07 | 4.070 | 17.40 | 0 | 0 | 3 | 3 |
| Merc 450SL | 17.3 | 8 | 275.8 | 180 | 3.07 | 3.730 | 17.60 | 0 | 0 | 3 | 3 |
| Merc 450SLC | 15.2 | 8 | 275.8 | 180 | 3.07 | 3.780 | 18.00 | 0 | 0 | 3 | 3 |
| Cadillac Fleetwood | 10.4 | 8 | 472.0 | 205 | 2.93 | 5.250 | 17.98 | 0 | 0 | 3 | 4 |
| Lincoln Continental | 10.4 | 8 | 460.0 | 215 | 3.00 | 5.424 | 17.82 | 0 | 0 | 3 | 4 |
| Chrysler Imperial | 14.7 | 8 | 440.0 | 230 | 3.23 | 5.345 | 17.42 | 0 | 0 | 3 | 4 |
| Fiat 128 | 32.4 | 4 | 78.7 | 66 | 4.08 | 2.200 | 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 | 19.90 | 1 | 1 | 4 | 1 |
| Toyota Corona | 21.5 | 4 | 120.1 | 97 | 3.70 | 2.465 | 20.01 | 1 | 0 | 3 | 1 |
| Dodge Challenger | 15.5 | 8 | 318.0 | 150 | 2.76 | 3.520 | 16.87 | 0 | 0 | 3 | 2 |
| AMC Javelin | 15.2 | 8 | 304.0 | 150 | 3.15 | 3.435 | 17.30 | 0 | 0 | 3 | 2 |
| Camaro Z28 | 13.3 | 8 | 350.0 | 245 | 3.73 | 3.840 | 15.41 | 0 | 0 | 3 | 4 |
| Pontiac Firebird | 19.2 | 8 | 400.0 | 175 | 3.08 | 3.845 | 17.05 | 0 | 0 | 3 | 2 |
| Fiat X1-9 | 27.3 | 4 | 79.0 | 66 | 4.08 | 1.935 | 18.90 | 1 | 1 | 4 | 1 |
| Porsche 914-2 | 26.0 | 4 | 120.3 | 91 | 4.43 | 2.140 | 16.70 | 0 | 1 | 5 | 2 |
| Lotus Europa | 30.4 | 4 | 95.1 | 113 | 3.77 | 1.513 | 16.90 | 1 | 1 | 5 | 2 |
| Ford Pantera L | 15.8 | 8 | 351.0 | 264 | 4.22 | 3.170 | 14.50 | 0 | 1 | 5 | 4 |
| Ferrari Dino | 19.7 | 6 | 145.0 | 175 | 3.62 | 2.770 | 15.50 | 0 | 1 | 5 | 6 |
| Maserati Bora | 15.0 | 8 | 301.0 | 335 | 3.54 | 3.570 | 14.60 | 0 | 1 | 5 | 8 |
| Volvo 142E | 21.4 | 4 | 121.0 | 109 | 4.11 | 2.780 | 18.60 | 1 | 1 | 4 | 2 |
| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mazda RX4 | 21.00 | 6.00 | 160.00 | 110.00 | 3.90 | 2.62 | 16.46 | 0.00 | 1.00 | 4.00 | 4.00 |
| Mazda RX4 Wag | 21.00 | 6.00 | 160.00 | 110.00 | 3.90 | 2.88 | 17.02 | 0.00 | 1.00 | 4.00 | 4.00 |
| Datsun 710 | 22.80 | 4.00 | 108.00 | 93.00 | 3.85 | 2.32 | 18.61 | 1.00 | 1.00 | 4.00 | 1.00 |
| Hornet 4 Drive | 21.40 | 6.00 | 258.00 | 110.00 | 3.08 | 3.21 | 19.44 | 1.00 | 0.00 | 3.00 | 1.00 |
| Hornet Sportabout | 18.70 | 8.00 | 360.00 | 175.00 | 3.15 | 3.44 | 17.02 | 0.00 | 0.00 | 3.00 | 2.00 |
| Valiant | 18.10 | 6.00 | 225.00 | 105.00 | 2.76 | 3.46 | 20.22 | 1.00 | 0.00 | 3.00 | 1.00 |
| Duster 360 | 14.30 | 8.00 | 360.00 | 245.00 | 3.21 | 3.57 | 15.84 | 0.00 | 0.00 | 3.00 | 4.00 |
| Merc 240D | 24.40 | 4.00 | 146.70 | 62.00 | 3.69 | 3.19 | 20.00 | 1.00 | 0.00 | 4.00 | 2.00 |
| Merc 230 | 22.80 | 4.00 | 140.80 | 95.00 | 3.92 | 3.15 | 22.90 | 1.00 | 0.00 | 4.00 | 2.00 |
| Merc 280 | 19.20 | 6.00 | 167.60 | 123.00 | 3.92 | 3.44 | 18.30 | 1.00 | 0.00 | 4.00 | 4.00 |
| Merc 280C | 17.80 | 6.00 | 167.60 | 123.00 | 3.92 | 3.44 | 18.90 | 1.00 | 0.00 | 4.00 | 4.00 |
| Merc 450SE | 16.40 | 8.00 | 275.80 | 180.00 | 3.07 | 4.07 | 17.40 | 0.00 | 0.00 | 3.00 | 3.00 |
| Merc 450SL | 17.30 | 8.00 | 275.80 | 180.00 | 3.07 | 3.73 | 17.60 | 0.00 | 0.00 | 3.00 | 3.00 |
| Merc 450SLC | 15.20 | 8.00 | 275.80 | 180.00 | 3.07 | 3.78 | 18.00 | 0.00 | 0.00 | 3.00 | 3.00 |
| Cadillac Fleetwood | 10.40 | 8.00 | 472.00 | 205.00 | 2.93 | 5.25 | 17.98 | 0.00 | 0.00 | 3.00 | 4.00 |
| Lincoln Continental | 10.40 | 8.00 | 460.00 | 215.00 | 3.00 | 5.42 | 17.82 | 0.00 | 0.00 | 3.00 | 4.00 |
| Chrysler Imperial | 14.70 | 8.00 | 440.00 | 230.00 | 3.23 | 5.34 | 17.42 | 0.00 | 0.00 | 3.00 | 4.00 |
| Fiat 128 | 32.40 | 4.00 | 78.70 | 66.00 | 4.08 | 2.20 | 19.47 | 1.00 | 1.00 | 4.00 | 1.00 |
| Honda Civic | 30.40 | 4.00 | 75.70 | 52.00 | 4.93 | 1.61 | 18.52 | 1.00 | 1.00 | 4.00 | 2.00 |
| Toyota Corolla | 33.90 | 4.00 | 71.10 | 65.00 | 4.22 | 1.83 | 19.90 | 1.00 | 1.00 | 4.00 | 1.00 |
| Toyota Corona | 21.50 | 4.00 | 120.10 | 97.00 | 3.70 | 2.46 | 20.01 | 1.00 | 0.00 | 3.00 | 1.00 |
| Dodge Challenger | 15.50 | 8.00 | 318.00 | 150.00 | 2.76 | 3.52 | 16.87 | 0.00 | 0.00 | 3.00 | 2.00 |
| AMC Javelin | 15.20 | 8.00 | 304.00 | 150.00 | 3.15 | 3.44 | 17.30 | 0.00 | 0.00 | 3.00 | 2.00 |
| Camaro Z28 | 13.30 | 8.00 | 350.00 | 245.00 | 3.73 | 3.84 | 15.41 | 0.00 | 0.00 | 3.00 | 4.00 |
| Pontiac Firebird | 19.20 | 8.00 | 400.00 | 175.00 | 3.08 | 3.85 | 17.05 | 0.00 | 0.00 | 3.00 | 2.00 |
| Fiat X1-9 | 27.30 | 4.00 | 79.00 | 66.00 | 4.08 | 1.94 | 18.90 | 1.00 | 1.00 | 4.00 | 1.00 |
| Porsche 914-2 | 26.00 | 4.00 | 120.30 | 91.00 | 4.43 | 2.14 | 16.70 | 0.00 | 1.00 | 5.00 | 2.00 |
| Lotus Europa | 30.40 | 4.00 | 95.10 | 113.00 | 3.77 | 1.51 | 16.90 | 1.00 | 1.00 | 5.00 | 2.00 |
| Ford Pantera L | 15.80 | 8.00 | 351.00 | 264.00 | 4.22 | 3.17 | 14.50 | 0.00 | 1.00 | 5.00 | 4.00 |
| Ferrari Dino | 19.70 | 6.00 | 145.00 | 175.00 | 3.62 | 2.77 | 15.50 | 0.00 | 1.00 | 5.00 | 6.00 |
| Maserati Bora | 15.00 | 8.00 | 301.00 | 335.00 | 3.54 | 3.57 | 14.60 | 0.00 | 1.00 | 5.00 | 8.00 |
| Volvo 142E | 21.40 | 4.00 | 121.00 | 109.00 | 4.11 | 2.78 | 18.60 | 1.00 | 1.00 | 4.00 | 2.00 |
mtcars %>%
DT::datatable(filter = 'top',
options = list(scrollX = TRUE, keys = TRUE, pageLength = 5),
rownames = FALSE)- easy to share with collaborators
Exercises:
set up git with Rstudio
set up your github account with workflowr
create a new project using wflow_start()
create a new markdown file in the analysis folder, my_first_project
load luad file from extdata
delete empty columns using a for cycle and if statements.
modify days since birth that it appears in years. google the exact number of days in a year.
Create tables for Diagnosis.Age, Sex, Race.Category and American.Joint.Committee.on.Cancer.Tumor.Stage.Code
do chi-sq test for American.Joint.Committee.on.Cancer.Tumor.Stage.Code and Sex Plot the data (e.g. barplot, counts by gender)
do linear regression for the Mutation.Count and stage, gender and age. show the results in table. Plot the data.