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- R Debugging
Since debugging R programs is a challenge, it is best practices to test units and each R syntax update instead of building a complex expression first. Up to 80% of R debugging may be due to invalid syntax, missing or invalid R objects. In addition, it is ideal to copy and update a working R code example instead of writing R code from scratch if possible. For debugging %>% R piping code, it is best to test each component first and then to combine them. Interpreting R error messages can be confusing.
Need help with R functions, ex. lm() syntax: help(lm), help("lm"), ?lm, ?"lm"
Below are common errors and potential solutions. It is best to test one statement at a time.
- Typos, Capitalization and Mis-spelling
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- If you see “unexpected symbol”, check for missing commas
- Packages, Libraries Are Not Loaded
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- Could not find function "x"...
- This likely means that you typed the function name incorrectly, or forgot to install or load a package.
- Objects
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- Object 'x' not found
- This means that an object you are referencing does not exist. Perhaps code above did not run properly?
- Function Syntax: Closing & Continuing Punctuation
- Logic
- Error in if
- This likely means an if statement was applied to something that was not TRUE or FALSE.
- Factors
- Plotting
- Error: Insufficient values in manual scale. 3 needed but only 2 provided. ggplot()
- R Markdown
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ERROR TYPE |
SOLUTIONS |
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Invalid or Missing Packages, Path names, Libraries not Loaded |
Load and confirm packages, path names and libraries |
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Invalid or Missing Data Frames, Objects or Variables |
Confirm correct and existing data frames (instead of matrix), objects and vars, lower case all names since case-sensitive, correct order of tasks (select, filter, etc.) within DPLYR (SQL) functions, apply group_by() before summary functions to prevent overall summaries |
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Invalid or Missing Functions or Operations |
Confirm functions exist and correctly applied, confirm variable and function types are consistent |
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Invalid or Missing Parameters and Options |
Confirm correct function usage, case-sensitive, cut/paste working example |
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Invalid or Missing Data or Format |
Confirm data import is correct, lower case data since case-sensitive, remove extra spaces before and after data values, confirm correct date format, apply factors to assign invalid data as NA, data by descriptive stats, freq counts, min, max, etc. |
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Invalid Logic |
Confirm process logic flow, test and view inputs and outputs of each function |
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Subscript out of Bounds |
Confirm correct starting, ending and incrementing values, apply dim() to check # of rows and columns |
|
NA or Missing Values |
Confirm NA and missing values, convert NA to missing values, confirm joins and appends, apply ignore missing values parameter options |
|
Incorrect Variable Types |
Apply conversion functions to convert to character, numeric or dates before using in functions, confirm correct date format |
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Incorrect Symbols |
Apply correct symbols: Assignment (<-), Direct Row and Column Reference ([]), Operators (==, &, |, !), Piping (output of first function %>% is input to second function) |
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Unbalanced Quotes, Parentheses |
Confirm balanced quotes (‘) and parentheses , [], () |
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Invalid Custom Functions |
Confirm correct function structure syntax, parameters and collection of R functions, test using simple data frames, variables and values |
