name	shift-training-year
description	Shift years in training data files (CSV + XLSX) by +N years — both filenames and content. Supports `--dry-run` for safe preview before destructive run. Use when updating training data for a new year, "เลื่อนปี", "shift year", "update year in training data", "เปลี่ยนปีใน data", or when preparing Power BI / Excel training files for next year's course.
scope_note	Apply when preparing ThepExcel training data (CSV + XLSX) for a new course year — shifts years in filenames, quoted date/order-number strings in CSVs, and Year-column values in XLSX. Creates a backup before modifying and processes files in reverse-year order to avoid double-shifting.
out_of_scope	Not for general spreadsheet edits (use /xlsx-thepexcel). Not for shifting non-year date components (months, days). Does not rename XLSX files.

Shift Training Year

Shift year references in training data files (CSV, XLSX) by a specified amount. Designed for annual updates to course training data — handles filenames, CSV content (Order Numbers, dates), and XLSX year columns.

When to Use

Updating training data files so the years match the current course year
User says "เลื่อนปี", "shift year", "update year in data/training files"
Preparing Power BI, Excel, or data analytics training materials for a new year

How It Works

Run the bundled script which handles everything:

python "<skill-path>/scripts/shift_year.py" "<folder-path>" [--shift N] [--dry-run]

folder-path: Directory containing the data files (CSV + XLSX)
--shift N: How many years to shift (default: 1). Use negative values to shift backwards.
--dry-run: Preview what would be renamed/modified without touching the filesystem. No backup is created, no files are renamed or written. Prints a summary of planned operations so the user can sanity-check pattern matches before committing to a destructive run. Strongly recommended as the first pass, especially when:
- Folder mixes CSV + XLSX with possible cross-domain year-like values (product codes, version numbers, customer birthdays, free-text comments containing 4-digit years)
- First time running the skill on a new dataset where quoted-string detection or 2000–2099 standalone-year matching might false-match
- User wants a confidence check before trusting the _backup/ safety net

What the Script Does

CSV files:

Detects which year(s) appear in each file by scanning quoted strings
Shifts years only inside quoted strings — this protects unquoted numeric values (StoreKey, CustomerKey, ProductKey, etc.) from accidental changes
Handles Order Numbers (e.g., "202401011CS952" → "202501011CS952") and dates in DD/MM/YYYY format (e.g., "01/01/2024" → "01/01/2025")
Renames files that have years in their names (e.g., contoso-online-2024.csv → contoso-online-2025.csv)

XLSX files:

Shifts any numeric cell value that looks like a year (2000-2099 range) in columns named "Year" or similar
Also scans all cells for standalone year values if no Year column is found
Does not rename XLSX files (usually named generically like TargetReport.xlsx)

Important Notes

The script processes files in reverse year order (highest year first) to prevent double-shifting when multiple years exist in the same file
Always creates a backup (_backup/) before modifying files — the backup is placed inside the target folder
CSV encoding is preserved (UTF-8)

Workflow

Default workflow is dry-run-first (rsync-style — preview, then commit):

User provides the folder path containing training data
Confirm with user: which files to process and the shift amount
Dry-run pass — run script with --dry-run and show the planned renames/modifications to the user
If the preview looks wrong (unexpected files matched, year false-matches in product codes / comments / metadata cells), adjust scope (exclude files, change shift amount) and dry-run again
Once preview looks correct → run the script for real (without --dry-run) — this creates _backup/ then modifies files
Verify a sample of the output to make sure it looks correct
If user is satisfied, the backup folder can be deleted

Example

User: เลื่อนปีใน training data ไป 1 ปี folder C:\...\Contoso

Step 1: List files in the folder
Step 2: Confirm with user
Step 3: Dry-run preview
  python "<skill-path>/scripts/shift_year.py" "C:\...\Contoso" --dry-run
  → review planned renames + content changes (no files touched yet)
Step 4: Real run (after user approves preview)
  python "<skill-path>/scripts/shift_year.py" "C:\...\Contoso"
Step 5: Spot-check a few rows from each file

Expected dry-run output

[DRY-RUN] Would rename: contoso-online-2024.csv -> contoso-online-2025.csv
[DRY-RUN] Would modify: orders.csv (124 quoted year refs: 2024->2025)
[DRY-RUN] Would skip:   TargetReport.xlsx (no Year column, 0 standalone years)
[DRY-RUN] Total: 3 renames, 2 file modifications, 0 backups created

Related Skills

/xlsx-thepexcel — Read/edit XLSX files directly; use when year-shifted data needs further spreadsheet manipulation

name	shift-training-year
description	Shift years in training data files (CSV + XLSX) by +N years — both filenames and content. Supports `--dry-run` for safe preview before destructive run. Use when updating training data for a new year, "เลื่อนปี", "shift year", "update year in training data", "เปลี่ยนปีใน data", or when preparing Power BI / Excel training files for next year's course.
scope_note	Apply when preparing ThepExcel training data (CSV + XLSX) for a new course year — shifts years in filenames, quoted date/order-number strings in CSVs, and Year-column values in XLSX. Creates a backup before modifying and processes files in reverse-year order to avoid double-shifting.
out_of_scope	Not for general spreadsheet edits (use /xlsx-thepexcel). Not for shifting non-year date components (months, days). Does not rename XLSX files.

Shift Training Year

When to Use

Updating training data files so the years match the current course year
User says "เลื่อนปี", "shift year", "update year in data/training files"
Preparing Power BI, Excel, or data analytics training materials for a new year

How It Works

Run the bundled script which handles everything:

python "<skill-path>/scripts/shift_year.py" "<folder-path>" [--shift N] [--dry-run]

folder-path: Directory containing the data files (CSV + XLSX)
--shift N: How many years to shift (default: 1). Use negative values to shift backwards.
--dry-run: Preview what would be renamed/modified without touching the filesystem. No backup is created, no files are renamed or written. Prints a summary of planned operations so the user can sanity-check pattern matches before committing to a destructive run. Strongly recommended as the first pass, especially when:
- Folder mixes CSV + XLSX with possible cross-domain year-like values (product codes, version numbers, customer birthdays, free-text comments containing 4-digit years)
- First time running the skill on a new dataset where quoted-string detection or 2000–2099 standalone-year matching might false-match
- User wants a confidence check before trusting the _backup/ safety net

What the Script Does

CSV files:

Detects which year(s) appear in each file by scanning quoted strings
Shifts years only inside quoted strings — this protects unquoted numeric values (StoreKey, CustomerKey, ProductKey, etc.) from accidental changes
Handles Order Numbers (e.g., "202401011CS952" → "202501011CS952") and dates in DD/MM/YYYY format (e.g., "01/01/2024" → "01/01/2025")
Renames files that have years in their names (e.g., contoso-online-2024.csv → contoso-online-2025.csv)

XLSX files:

Shifts any numeric cell value that looks like a year (2000-2099 range) in columns named "Year" or similar
Also scans all cells for standalone year values if no Year column is found
Does not rename XLSX files (usually named generically like TargetReport.xlsx)

Important Notes

The script processes files in reverse year order (highest year first) to prevent double-shifting when multiple years exist in the same file
Always creates a backup (_backup/) before modifying files — the backup is placed inside the target folder
CSV encoding is preserved (UTF-8)

Workflow

Default workflow is dry-run-first (rsync-style — preview, then commit):

User provides the folder path containing training data
Confirm with user: which files to process and the shift amount
Dry-run pass — run script with --dry-run and show the planned renames/modifications to the user
If the preview looks wrong (unexpected files matched, year false-matches in product codes / comments / metadata cells), adjust scope (exclude files, change shift amount) and dry-run again
Once preview looks correct → run the script for real (without --dry-run) — this creates _backup/ then modifies files
Verify a sample of the output to make sure it looks correct
If user is satisfied, the backup folder can be deleted

Example

User: เลื่อนปีใน training data ไป 1 ปี folder C:\...\Contoso

Step 1: List files in the folder
Step 2: Confirm with user
Step 3: Dry-run preview
  python "<skill-path>/scripts/shift_year.py" "C:\...\Contoso" --dry-run
  → review planned renames + content changes (no files touched yet)
Step 4: Real run (after user approves preview)
  python "<skill-path>/scripts/shift_year.py" "C:\...\Contoso"
Step 5: Spot-check a few rows from each file

Expected dry-run output

[DRY-RUN] Would rename: contoso-online-2024.csv -> contoso-online-2025.csv
[DRY-RUN] Would modify: orders.csv (124 quoted year refs: 2024->2025)
[DRY-RUN] Would skip:   TargetReport.xlsx (no Year column, 0 standalone years)
[DRY-RUN] Total: 3 renames, 2 file modifications, 0 backups created

Related Skills

/xlsx-thepexcel — Read/edit XLSX files directly; use when year-shifted data needs further spreadsheet manipulation

shift-training-year

Shift Training Year

When to Use

How It Works

What the Script Does

Important Notes

Workflow

Example

Expected dry-run output

Related Skills

Shift Training Year

When to Use

How It Works

What the Script Does

Important Notes

Workflow

Example

Expected dry-run output

Related Skills