Common CSV Errors and How to Fix Them

When preparing CSV files for Housing.Cloud sandbox provisioning, even small formatting issues can cause import errors. This guide walks through the most common CSV errors housing admins encounter, explains what causes them, and provides step-by-step fixes.

Most errors fall into a few categories: formatting problems (dates, commas, special characters), missing or duplicate data, incorrect column names, and structural issues. Once you understand these patterns, troubleshooting becomes straightforward.

Error: "Missing required field"

What This Means

One or more rows have blank cells in columns marked as required. Housing.Cloud cannot import incomplete records.

How to Find It

The error message usually tells you which row and column has the problem, like "Row 45: sisId is required".

1. Open your CSV in Excel or Google Sheets

2. Navigate to the row number mentioned in the error

3. Look for empty cells in the specified column

How to Fix It

Fill in the missing value. For required fields like sisId, firstName, lastName, or email, you must provide valid data for every student.

If you don't have the data for a particular student, either:

• Delete that entire row (if the student shouldn't be included)

• Look up the missing information from your SIS or records

• Use a placeholder value for sandbox testing (like "Test" for firstName), but note that real data is always better for realistic testing

Preventing This Error

Before saving your CSV, use Excel's filter feature to check for blanks:

1. Select your data (Ctrl+A or Cmd+A)

2. Click Data → Filter

3. Click the dropdown arrow on each required column

4. Look for "(Blanks)" in the filter menu

5. If blanks appear, uncheck all items except "(Blanks)" to show only empty cells

6. Fill in or delete rows with missing data

Error: "Duplicate value in unique field"

What This Means

Two or more rows have the same value in a column that requires unique entries. For example, two students cannot have the same sisId or email address.

Columns That Must Be Unique

• sisId (Student Profiles CSV) — Each student must have a unique student ID

• email (Student Profiles CSV) — Each student must have a unique email address

• accountingCode (Charge Codes CSV) — Each charge must have a unique accounting code

• Bed names (Inventory CSV) — Each bed must have a unique name within your inventory

How to Find Duplicates

In Excel:

1. Select the column that has duplicates (like the sisId column)

2. Click Data → Filter

3. Click Data → Sort A to Z

4. Scroll through the sorted column and look for consecutive identical values

Or use conditional formatting:

1. Select the column

2. Click Home → Conditional Formatting → Highlight Cell Rules → Duplicate Values

3. Excel will highlight all duplicate cells in red

How to Fix It

Determine which record is correct:

• If one row has the wrong ID, correct it

• If you accidentally entered the same student twice, delete one row

• If both records are different students who happen to share an ID or email (which shouldn't happen), investigate your source data—one likely has a typo

For email duplicates, remember that some students may have multiple emails in your SIS. Choose the primary/preferred email for Housing.Cloud.

Error: "Invalid date format"

What This Means

Dates are not formatted as YYYY-MM-DD. Housing.Cloud requires this exact format for all date fields.

Common Date Format Mistakes

Note that single-digit months and days must include leading zeros (03, not 3).

How to Fix It in Excel

1. Select the entire date column (click the column letter)

2. Right-click and choose Format Cells

3. Select Custom from the Category list

4. In the Type field, enter: yyyy-mm-dd

5. Click OK

If dates still look wrong after formatting, Excel may have interpreted them as text. You'll need to re-enter them or use a formula:

• In a new column, use: =TEXT(A2,"yyyy-mm-dd") (assuming your date is in cell A2)

• Drag the formula down to apply to all rows

• Copy the new column and Paste Special → Values back into the original column

• Delete the helper column

How to Fix It in Google Sheets

1. Select the date column

2. Click Format → Number → Custom number format

3. Enter: yyyy-mm-dd

4. Click Apply

Preventing Date Issues

When exporting from your SIS, configure the export to use YYYY-MM-DD format if possible. If your SIS always exports in a different format, you may need to write an Excel formula or script to convert dates after export.

Error: "Invalid column name" or "Unexpected column"

What This Means

Your CSV's column headers don't exactly match the schema. This usually happens because of typos, extra spaces, wrong capitalization, or missing columns.

How to Find It

Compare your CSV's first row (the header row) with the schema document for your CSV type.

Common mistakes:

• sisId typed as "sisID" or "SisId" (wrong capitalization)

• firstName typed as "first_name" or "FirstName"

• dateOfBirth typed as "date of birth" (spaces not allowed)

• Extra spaces before or after column names ("sisId " with a trailing space)

How to Fix It

1. Open your CSV in Excel or Google Sheets

2. Look at row 1 (the header row)

3. Compare each column name to the schema

4. Correct any typos, capitalization errors, or spacing issues

5. Ensure you haven't added extra columns that aren't in the schema

Missing Required Columns

If you're missing a required column entirely:

1. Insert a new column in the correct position (column order doesn't technically matter, but matching the schema order makes troubleshooting easier)

2. Add the correct header name in row 1

3. Fill in values for all rows

Error: "Row has too many/too few columns"

What This Means

One or more rows don't have the same number of commas (columns) as the header row. This usually means a cell contains an unescaped comma, or data was copied incorrectly.

How to Find It

Open the CSV in a plain text editor like Notepad. Look for rows that have more or fewer commas than others.

For example, if your header row has 6 commas (7 columns), every data row should also have exactly 6 commas.

Common Causes

• Commas in data — A building name like "North Hall, Building A" contains a comma that breaks the CSV structure

• Line breaks in data — A cell contains a multi-line address or note that creates unexpected row breaks

• Missing trailing columns — A row ends early because the last few columns are blank, and Excel didn't add commas for them

How to Fix It

For commas in data:

Excel and Google Sheets should automatically handle this by wrapping the cell in quotes when you save as CSV. If you're seeing this error, re-save the file to ensure proper quoting:

1. Open the CSV in Excel

2. Click File → Save As

3. Choose CSV (Comma delimited) again

4. Save over the existing file

For line breaks in data:

1. Find cells that contain multi-line text (press Ctrl+F and search for line breaks if possible)

2. Remove line breaks by replacing them with spaces or semicolons

3. Or remove the multi-line content entirely if it's not needed

For missing trailing columns:

Ensure every row has values or intentional blanks for all columns. In Excel, select the last cell of each row and press Tab to add trailing commas for empty columns.

Error: "Encoding error" or "Unrecognized character"

What This Means

Your CSV contains special characters (like accented letters, curly quotes, or symbols) that weren't saved with the correct encoding. Housing.Cloud expects UTF-8 encoding.

Common Problem Characters

• Accented letters: José, Müller, Sofía

• Curly quotes or apostrophes: ' ' " " (instead of straight quotes: ' ")

• Special symbols: © ® ™ °

• Em dashes or en dashes: — – (instead of hyphens: -)

How to Fix It

In Google Sheets (easiest method):

1. Open your CSV in Google Sheets

2. Click File → Download → Comma Separated Values (.csv)

3. Google Sheets automatically uses UTF-8 encoding, which preserves special characters

In Excel (Windows):

1. Open Excel and go to File → Save As

2. In the "Save as type" dropdown, look for CSV UTF-8 (Comma delimited)

3. Select this option instead of the regular "CSV (Comma delimited)"

4. Save your file

If your version of Excel doesn't have the UTF-8 CSV option, use Google Sheets or a text editor instead.

In a text editor:

1. Open the CSV in Notepad (Windows) or TextEdit (Mac)

2. Click File → Save As

3. In the Encoding dropdown, select UTF-8

4. Save the file

Preventing Encoding Issues

If your data includes international names or special characters, always save as UTF-8 from the start. Don't copy data from Word documents or websites, as these often introduce curly quotes and other non-standard characters.

Error: "Invalid data type"

What This Means

A column expects numbers but contains text, or expects text but contains numbers. For example, a dollar amount field contains "$3,500.00" instead of "3500.00".

How to Find It

Check columns that should contain numbers (like chargeAmount, capacity, or dollarAmount) for:

• Dollar signs: $

• Commas: 3,500 should be 3500

• Text: "Free" or "N/A" instead of 0

• Symbols: %, #, or other characters

Check columns that should contain text (like names or tags) for:

• Numbers stored as formulas instead of text

• Special formatting that Excel converted to codes

How to Fix It

For number fields:

1. Select the column

2. Use Find & Replace (Ctrl+H) to remove unwanted characters:

   • Find "$" and replace with nothing

   • Find "," and replace with nothing

3. Ensure the column is formatted as Number (not Text or Currency)

For text fields:

1. Select the column

2. Right-click and choose Format Cells → Text

3. Re-enter any values that were converted to numbers or dates

Error: "Related record not found"

What This Means

Your CSV references another record that doesn't exist. This happens most often in the Inventory CSV when you reference a parent building or floor that isn't defined, or in the Occupancy CSV when you reference a sisId or bed that doesn't exist.

Common Examples

• Inventory CSV: A room row lists "floorName: Floor 2", but no Floor 2 exists in your inventory

• Inventory CSV: A floor row lists "buildingName: North Hall", but no North Hall building exists

• Occupancy CSV: A residency row lists "sisId: 123456", but that student doesn't exist in your Profiles CSV

• Occupancy CSV: A residency row lists "bedName: North-201-A", but that bed doesn't exist in your Inventory CSV

How to Fix It

For Inventory hierarchy issues:

1. Review your building, floor, room, and bed names

2. Ensure every floor references a valid buildingName

3. Ensure every room references a valid floorName

4. Ensure every bed references a valid roomName

5. Check for typos in names (extra spaces, capitalization differences)

For Occupancy CSV issues:

1. Verify that every sisId in your Occupancy CSV exists in your Profiles CSV

2. Verify that every bedName in your Occupancy CSV exists in your Inventory CSV

3. Check for exact name matches (case-sensitive, no extra spaces)

Preventing This Error

Build CSVs in the correct order:

1. Profiles CSV first — Establishes all sisIds

2. Inventory CSV second — Establishes all building, floor, room, and bed names

3. Charge Codes CSV third — Establishes accountingCodes

4. Occupancy CSV last — References sisIds from Profiles and bedNames from Inventory

This way, you can verify that all referenced records exist before creating dependent data.

Error: "File is too large"

What This Means

Your CSV file exceeds the system's upload limit. This rarely happens with sandbox data, but may occur if you're importing thousands of records or accidentally included unnecessary columns with large amounts of text.

How to Fix It

1. Remove unnecessary columns — Delete any columns that aren't part of the required or optional schema

2. Trim long text fields — If you have notes or description fields, shorten or remove them

3. Split into multiple files — Divide your data into two or more CSV files and import them separately (e.g., students A-M in one file, N-Z in another)

File Size Guidelines

Most sandbox CSV files should be small:

• Profiles CSV: 100-500 students = ~50 KB to 200 KB

• Inventory CSV: 500-2,000 beds = ~100 KB to 500 KB

• Charge Codes CSV: 10-50 codes = ~5 KB to 20 KB

If your file is over 1 MB, double-check that you haven't accidentally included thousands of extra rows or large text blocks.

Error: "File not found" or "Upload failed"

What This Means

The file upload didn't complete, or the file path is incorrect. This is usually a browser or network issue, not a problem with your CSV itself.

How to Fix It

1. Check your internet connection

2. Try uploading in a different browser (Chrome, Firefox, Edge)

3. Clear your browser cache and cookies

4. Disable browser extensions that might interfere with uploads

5. Try uploading from a different device or network

If the issue persists, contact your Housing.Cloud implementation team and describe the error message you're seeing.

General Troubleshooting Tips

Start Small

If you're having trouble with a large CSV, create a test file with just 5-10 rows of data. This makes it much easier to spot formatting issues and validate that your structure is correct before importing hundreds of records.

Compare to Working Examples

If you've successfully imported one CSV before, use it as a template for future files. Copy the header row and structure, then replace the data rows with your new records.

Use Text View to Debug

Open your CSV in Notepad or TextEdit to see the raw comma-separated format. This reveals hidden characters, encoding issues, and structural problems that spreadsheets hide.

Validate Before Submitting

Before sending CSVs to Housing.Cloud, run through this checklist:

• First row is column headers, exactly matching the schema

• No blank rows

• All required fields have values

• Dates are YYYY-MM-DD

• Numbers have no formatting ($, commas, etc.)

• No duplicate values in unique fields

• File extension is .csv

• File opens correctly in Excel showing data in columns

Keep Backups

Always save a copy of your working Excel file (.xlsx) with formulas and formatting intact. If something goes wrong with the CSV version, you can regenerate it from your Excel backup without losing work.

Ask for Help

If you're stuck on an error you can't resolve, contact your Housing.Cloud implementation team. Include:

• The exact error message

• Which CSV file is causing the issue (Profiles, Inventory, etc.)

• The row number mentioned in the error (if any)

• A sample of your CSV (first 10 rows) so they can see the structure

The implementation team can often spot issues quickly and provide specific guidance for your data.

Related Articles

• Working with CSV Files: A Beginner's Guide — Learn CSV basics and formatting rules

• Creating Your Student Profiles CSV — Build your student data file

• Creating Your Housing Inventory CSV — Build your building and room data file

• Creating Your Charge Codes CSV — Build your billing rates file

• Preparing Data for Your Sandbox Environment — Overview of the sandbox setup process