Data Analysis Toolkit – Smart Data Analyzer

GHOSTOOLS · ANALYTICS

Data Analysis Toolkit

Explore datasets, calculate descriptive statistics, clean messy data, discover outliers, visualize relationships, and export actionable reports — all in one browser-based workspace.

Free to Use CSV & Excel Interactive Charts Browser-Based Analysis

1. Import Your Dataset

Choose a CSV or Excel file .csv, .xlsx, .xls · Maximum 15 MB

Files are processed locally in your browser. Avoid opening untrusted spreadsheets containing macros or sensitive information on shared devices.

Dataset Overview

Rows0

Columns0

Missing Cells0

Duplicate Rows0

Upload a dataset or try the sample to begin.

2. Data Preview

Search all columns

Rows per page 10 rows 25 rows 50 rows 100 rows

Your dataset preview will appear here.

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3. Data Cleaning Studio

Apply changes to your working dataset. Original imported data remains available through Reset Workspace.

Handle missing values Keep missing values Remove rows with missing values Remove columns containing missing values Fill numeric missing values with mean Fill numeric missing values with median Fill missing values with zero Fill missing values with custom text

Custom replacement value

Trim extra spaces from text cells Normalize empty strings and whitespace to missing values

Mean and median imputation apply only to numeric columns. Rows with missing values are removed if you select that option. Always inspect cleaned results before using them for business or scientific decisions.

4. Descriptive Statistics

Numeric columns include count, mean, median, standard deviation, minimum, maximum, quartiles, and outlier counts. Categorical columns show distinct values and the most frequent value.

Statistics will appear after loading data.

5. Interactive Visualization

Chart type Bar chart Line chart Scatter plot Histogram

X-axis / category

Y-axis / numeric value

Maximum categories / points 10 20 50

Load data to create a chart.

6. Correlation Heatmap

Pearson correlation coefficients for numeric column pairs. Values range from -1 to +1. Correlation indicates association, not causation.

At least two numeric columns are required.

7. Outlier Detection

Numeric column

Detection method IQR rule (1.5 × IQR) Z-score (absolute score > 3)

Choose a numeric column to detect outliers.

Outlier results will appear here.

8. Key Findings & Analysis Report

Load data to generate a summary of data quality, distributions, and potential outliers.

Frequently Asked Questions

What file formats are supported?

Upload CSV and Excel workbooks in XLSX or XLS format. Excel worksheets can be selected before loading their data.

Does this tool upload my data?

Dataset parsing, cleaning, statistics, and calculations are performed in your browser. The application does not intentionally upload your dataset to Ghostools. The third-party libraries used to read spreadsheets and draw charts are loaded from external CDNs.

How are missing values handled?

You can keep missing values, remove incomplete rows or columns, fill missing numeric values using mean or median, replace missing values with zero, or insert custom text.

How does outlier detection work?

The IQR method flags observations below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR. The Z-score method flags observations more than three standard deviations from the mean. These methods identify candidates for investigation, not necessarily errors.

What does the correlation heatmap show?

The heatmap shows Pearson correlation between numeric columns using pairwise complete observations. A value close to +1 indicates a strong positive linear association; a value close to −1 indicates a strong negative linear association.

Can I export my cleaned dataset?

Yes. Export the cleaned working dataset as CSV or JSON. You can also export descriptive statistics, detected outliers, and a text analysis report.

Free Data Tools by Ghostools

Data Analysis Toolkit · Explore. Clean. Understand.