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Fix Data Types in a CSV

Convert currency text and thousands separators into plain numbers.

Text case
Missing values
Column
Number column
Method
Common values: 1.5 for IQR, 3 for z-score, 3.5 for modified z.

Before and after

MeasureBeforeAfter
Rows1414
Columns55
Blank cells11
  • 2 whitespace fixed in cells
  • 14 cells converted to numbers or yes/no

Cleaned data (first 14 rows)

NameCityAgeSalaryActive
Alice Smithdhaka3452000yes
alice smithDhaka3452000Yes
Bob KhanCHITTAGONG2948500no
Carla GomezDhaka4161200yes
Dev PatelSylhetblank45000yes
Eve AdamsN/A3858300no
Frank WuDhaka36980000yes
Gita RaoSylhet3150100N/A
Hana SatoChittagong3354700no
Ivan PetrovDhaka3557000yes
Jo LeeSylhet3251300no
Kim ParkDhaka3049900yes
Lena FoxChittagong24056000no
Bob KhanCHITTAGONG2948500no

Flagged outliers are highlighted. The CSV download holds every row, not only this preview.

  1. Tools
  2. Data Science
  3. Data Cleaner
  4. Fix Data Types in a CSV

About Fix Data Types in a CSV

This page opens with Fix types on. The Salary column holds text such as "$52,000", which a spreadsheet or a script cannot add up. It becomes 52000. It is free, needs no sign-up and runs in your browser, so nothing you enter is uploaded.

The sample has 14 cells converted. Currency signs, thousands separators and bracket negatives are handled, and a column holding only yes and no values becomes true and false. A column is converted only when at least 90 percent of its filled cells read as numbers, and plain numbers are not rewritten, so ids with leading zeros are safe.

How to use Fix Data Types in a CSV

  1. 1Open Paste or upload data to load your file, or start with the sample.
  2. 2Switch on the steps you need: whitespace, case, types, missing values, duplicates, find and replace.
  3. 3To look for outliers, choose a number column and a method, and adjust the threshold if you want.
  4. 4Read Before and after for the row counts and what changed, and check the preview below it.
  5. 5Copy the cleaned CSV or download it.

Features

  • Trim and collapse whitespace.
  • Remove duplicate rows, optionally ignoring case.
  • Treat NA, N/A, null, nan and a lone dash as missing, then keep, drop, or fill with a value, the mean, the median, the most common value or the value above.
  • Fix types: currency and thousands separators, bracket negatives and yes/no, while keeping ids with leading zeros.
  • Standardise text to lower, upper or title case.
  • Find and replace in one column or all, with whole-cell, case and regular expression options.
  • Outlier detection with IQR, z-score or modified z-score, highlighted in the preview, with an option to remove them.
  • A before and after summary with counts of every change.

Worked examples

  • "$52,000", "(300)", "1 250.5" → gives 52000, -300, 1250.5

    Currency signs and separators are stripped; brackets mean negative.

Privacy: how it works

  • Your table is read and cleaned by code running in this browser tab. Nothing is uploaded, and your original file is never modified.

Tips

  • Trim whitespace first. A trailing space is the usual reason two equal-looking values count as different.
  • Turn on "treat NA as missing" before filling, so the placeholders are counted as gaps.
  • Filling with the mean pulls values towards the centre and understates spread. The median is safer when outliers exist.
  • Download a cleaned copy and keep the original. This tool never edits the source file.

Frequently asked questions

Is it really free?

Yes. There is no price, no trial and no credit card. Ulkaa Tool does the work with your own device, so there is no server bill to pass on to you.

Do I need an account?

No. There is no sign-up and no login. Open the page and use it. An Ulkaa account is not needed for anything on this tool.

Does it run in my browser?

Yes. Your data are processed by code running in your browser tab, on your own device.

Is my data uploaded?

No. Your data are never sent to Ulkaa or to anyone else. You can check this yourself by watching the Network tab in your browser developer tools while you use the tool.

Does it convert dates?

No. The same text, such as 03/04/2026, means different dates in different countries, so dates are left as they are.

More Data Cleaner pages

  • Data CleanerTidy a messy table and download it as a clean CSV, with a before and after summary.
  • Remove Duplicates From CSVDelete repeated rows and keep the first of each.
  • Fill Missing Values in a CSVReplace gaps with a sensible value, and see how many were filled.
  • Trim Whitespace in a CSVRemove stray spaces that make equal values look different.
  • Change Case in a CSVMake text consistent: Title Case, lower case or UPPER CASE.
  • Find and Replace in a CSVReplace values across every column or just one.
  • Outlier Detection in a CSVFlag the values that sit far from the rest of a column.
  • IQR Outlier CalculatorFind values outside Q1 - 1.5 x IQR and Q3 + 1.5 x IQR.
  • Z-Score Outlier DetectionFlag values more than a set number of standard deviations from the mean.
  • Modified Z-Score OutliersA robust outlier rule based on the median and the median absolute deviation.

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