datacheck

Data Check

Inspect and validate a data file before analysis. Report findings with suggested fixes. Do not auto-fix.

When to Use

• Before any analysis or visualization on a new data file
• When parsing errors or unexpected values appear
• When switching to a different dataset mid-session
• User says "check", "inspect", "what's in this", "profile" a data file

When NOT to Use

• File has already been checked in this session and nothing changed
• User just wants to read a specific value (use Read tool directly)

Workflow

Step 1: Raw File Inspection

Before loading into R/Stata, check the raw file:

file <filename>                          # encoding detection
head -c 500 <filename> | cat -v          # hidden chars: ^M (CR), BOM, non-UTF8
wc -l <filename>                         # row count sanity check
head -3 <filename>                       # peek at delimiter and header

Flag these issues:

Symptom	Meaning
^M at line ends	Classic Mac \r or Windows \r\n line endings
\xEF\xBB\xBF at start	UTF-8 BOM marker
Only 1 line from wc -l	Entire file on one line (wrong line endings)
Mixed delimiters	Inconsistent separator characters

Step 2: Load and Summarize

R-first. Use Stata only when the file is .dta and project context is Stata-based.

For CSV files:

df <- read.csv("file.csv", stringsAsFactors = FALSE)

For Stata .dta files:

library(haven)
df <- read_dta("file.dta")

Report this table:

Item	Value
Dimensions	rows x cols
Column names	list all
Column types	numeric, character, factor, labelled, date
Total missing	count and %

Then per column:

Column          Type        Missing   Unique   Example Values
─────────────────────────────────────────────────────────────
age             numeric     12 (2%)   45       18, 25, 34, 67, 89
gender          labelled    0 (0%)    3        1=Male, 2=Female, 3=Other
weight_var      numeric     0 (0%)    847      0.23, 1.05, 2.11