CSV Column Statistics

What This Tool Does

This tool analyzes each column in your CSV file and calculates comprehensive statistics. For numeric columns, you get min, max, mean, median, and mode. For all columns, you get count, unique values, null rate, and frequency distribution. Export the statistics as CSV for reporting or further analysis.

Statistics Provided

Basic stats (all columns):

• Count — Total number of rows
• Null count — Number of empty/null values
• Null rate — Percentage of null values
• Unique count — Number of distinct values
• Unique rate — Percentage of unique values

Numeric stats (numeric columns):

• Min — Minimum value
• Max — Maximum value
• Mean — Average value
• Median — Middle value (50th percentile)
• Mode — Most frequent value

Frequency distribution: Top N most common values with their counts and percentages.

Example Statistics

Input CSV:

name,age,salary,department
Alice,30,50000,Engineering
Bob,25,45000,Marketing
Charlie,35,60000,Engineering
Diana,,55000,Sales
Eve,28,52000,Marketing

Statistics output:

Column: name
  Count: 5, Nulls: 0 (0%), Unique: 5 (100%)
  Top values: Alice(1), Bob(1), Charlie(1)...

Column: age
  Count: 5, Nulls: 1 (20%), Unique: 4 (80%)
  Min: 25, Max: 35, Mean: 29.5, Median: 29, Mode: N/A

Column: salary
  Count: 5, Nulls: 0 (0%), Unique: 5 (100%)
  Min: 45000, Max: 60000, Mean: 52400, Median: 52000

Column: department
  Count: 5, Nulls: 0 (0%), Unique: 3 (60%)
  Top values: Engineering(2, 40%), Marketing(2, 40%), Sales(1, 20%)

When to Use This

Data exploration: Quickly understand the distribution and quality of a new dataset.

Data quality assessment: Identify columns with high null rates or data quality issues.

Feature analysis: Understand numeric feature distributions before machine learning.

Outlier detection: Min/max values help identify potential outliers.

Documentation: Include statistics in data dictionaries and documentation.

Understanding Statistics

Mean vs Median: Mean is the average. Median is the middle value. Median is less affected by outliers.

Salaries: [30k, 35k, 40k, 45k, 500k]
Mean: 130k (skewed by 500k)
Median: 40k (more representative)

Null rate: High null rates (>50%) may indicate columns that aren't being used or data collection issues.

Unique rate: 100% unique suggests an ID column. Low unique rate suggests a categorical column.

Mode: The most common value. Useful for understanding dominant categories.

Frequency Distribution

Shows the most common values in each column:

Column: status
  Top 5 values:
  - Active: 450 (75%)
  - Inactive: 100 (17%)
  - Pending: 30 (5%)
  - Suspended: 15 (2.5%)
  - Archived: 5 (0.5%)

Helps identify dominant categories and rare values.

Numeric Detection

The tool automatically detects numeric columns:

Integers: Whole numbers like 42, -17, 0.

Decimals: Numbers with decimal points like 3.14, -0.5.

Currency: Numbers with currency symbols like $100, €50.

Non-numeric: Text, dates, and mixed values get basic stats only (count, nulls, unique).

Export Options

Download as CSV: Export statistics for use in reports or further analysis.

Copy to clipboard: Quick copy for pasting into documentation.

Frequency export: Optionally include full frequency distributions in the export.

Limitations

Large files: Works best with files under 50MB. Very large files may cause slow analysis.

Advanced statistics: Doesn't calculate standard deviation, variance, percentiles beyond median, or correlations.

Date handling: Dates are treated as text. Date-specific statistics (min/max date) aren't calculated.

Frequently Asked Questions

What counts as a null value?

Empty cells, cells with only whitespace, and explicit "null" or "NULL" text are counted as null.

Can I get statistics for specific columns only?

This tool analyzes all columns. For specific columns, extract them first using CSV Column Extractor.

How is the median calculated?

For odd row counts, the median is the middle value. For even counts, it's the average of the two middle values.