Column Statistics
Generate statistical insights for your data columns
What This Tool Does
The Column Statistics tool analyzes numeric columns in your JSON dataset and calculates comprehensive statistical measures including mean, median, mode, minimum, maximum, standard deviation, and quartiles. It helps you understand data distribution, identify outliers, and gain insights into your numeric data patterns. This analysis is essential for data exploration, quality assessment, and making data-driven decisions.
Who It's For
- Data analysts exploring datasets
- Statisticians performing analysis
- Researchers analyzing study data
- Data scientists profiling data
Typical Use Cases
- Data exploration and profiling
- Quality checks on numeric data
- Identifying outliers and anomalies
- Understanding data distribution
- Statistical reporting and analysis
Input JSON Array
Statistical Analysis
Statistics will appear here...
How It Works
Parse and Identify
The tool parses your JSON array and identifies all numeric fields across all objects, filtering out non-numeric data.
Collect Values
For each numeric field, all values are collected and sorted, preparing them for statistical calculations.
Calculate Statistics
Statistical measures are computed: mean (average), median (middle value), mode (most frequent), min, max, standard deviation, and quartiles.
Display Results
Results are presented in an organized format showing all statistical measures for each numeric column, making patterns and insights immediately visible.
Examples
Example 1: Product Prices Analysis
Input:
[
{"product": "Widget", "price": 29.99, "quantity": 10},
{"product": "Gadget", "price": 49.99, "quantity": 5},
{"product": "Tool", "price": 19.99, "quantity": 15},
{"product": "Device", "price": 99.99, "quantity": 2}
]Output:
Field: price
Count: 4
Mean: 49.99
Median: 39.99
Min: 19.99
Max: 99.99
Std Dev: 32.91
Field: quantity
Count: 4
Mean: 8
Median: 7.5
Min: 2
Max: 15
Std Dev: 5.48Example 2: Mixed Data Types
Input:
[
{"id": 1, "score": 85, "grade": "B"},
{"id": 2, "score": 92, "grade": "A"},
{"id": 3, "score": 78, "grade": "C"}
]Output:
Field: id
Count: 3
Mean: 2
Median: 2
Min: 1
Max: 3
Field: score
Count: 3
Mean: 85
Median: 85
Min: 78
Max: 92
Note: "grade" is not numeric and was skippedCommon Errors
- No numeric fields: Dataset must contain at least one numeric field
- Not an array: Input must be a JSON array of objects
- Empty array: Cannot calculate statistics for empty dataset
- All null values: Fields with all null values cannot be analyzed
When to Use This Tool
Use This Tool When:
- You need to understand the distribution of numeric data
- You're performing exploratory data analysis
- You want to identify outliers or unusual values
- You need statistical summaries for reporting
- You're validating data quality and ranges
Compared to Other Tools:
- vs Data Type Analyzer: Use this for numeric analysis; use analyzer for type detection
- vs CSV Viewer: Use this for statistics; use viewer for visual inspection
- vs Key Frequency Counter: Use this for numeric stats; use counter for field presence
Limitations & Important Notes
File Size Limits
This tool processes data in your browser. JSON files larger than 5MB may cause performance issues. For very large datasets, consider sampling your data or using specialized statistical software.
Data Integrity
While this tool accurately calculates statistics, it does not validate whether the values are correct or meaningful for your domain. Always verify results against your business context.
Numeric Fields Only
This tool analyzes numeric fields only. String, boolean, and other non-numeric fields are automatically skipped. Ensure your data contains numeric values for analysis.
For Reference Only
Statistical results are provided for reference and exploration. Always validate findings with domain experts and perform comprehensive analysis before making critical decisions.
Privacy: All calculations happen locally in your browser. Your data is never sent to our servers.