Data Analysis Dashboard
Interacting with Graph Elements
To customize your view of the data, you can toggle individual elements on or off directly on the charts. Above each graph, you’ll see a legend with colored swatches and names (e.g., "Sales" or "Value1"). Click a swatch or its label to hide that dataset from the chart; click it again to show it. This feature is especially handy when analyzing multiple columns at once, letting you focus on specific data series without changing your selection.
About the Data Analysis Dashboard
Description
This tool was created with Grok AI.
The Data Analysis Dashboard is a simple, interactive tool designed to help you explore and visualize numerical data from CSV or JSON files. Whether you're analyzing sales figures, scientific measurements, or any dataset with numbers, this app provides a variety of charts and detailed statistical summaries to uncover insights quickly and easily.
How to Use
- Upload Your Data: Click the file input at the top to upload a CSV or JSON file containing numerical data (e.g., columns like "Sales" or "Scores").
- Select a Column: Use the dropdown menu to choose a specific numerical column to analyze, or select "All Columns" to view all numeric data.
- Filter Data: Enter a number in the filter input to show only rows where the selected column matches that value (optional).
- Choose a Chart: Pick a chart type (Line, Bar, Scatter, Pie, or Radar) from the dropdown to visualize your data.
- Interact with Charts: Use your mouse wheel to zoom in or out on Line, Bar, or Scatter charts, then drag left or right to pan across zoomed content.
- View Statistics: Check the stats grid below the chart for a detailed summary of your data. Click the "ℹ️ Statistics Info" button for explanations of each statistic.
Features
- File Support: Upload and analyze data from both CSV and JSON files with automatic parsing of numerical columns.
- Flexible Visualization: Choose from five chart types—Line, Bar, Scatter, Pie, and Radar—to view your data in different ways.
- Interactive Charts: Zoom in/out with the mouse wheel and pan horizontally by dragging on supported chart types for detailed exploration.
- Column Filtering: Focus on a specific column or filter rows by value to refine your analysis.
- Comprehensive Statistics: Get insights with 11 stats—Sum, Average, Median, Variance, Standard Deviation, Maximum, Minimum, Mean Deviation, Range, Skewness, and Kurtosis—each with detailed descriptions.
- Responsive Design: A clean, modern interface that adapts to different screen sizes for a seamless experience.
- User Guidance: Built-in notes and a statistics info modal to help you understand and navigate the tool effectively.
Statistics Descriptions
Sum: The total of all values added together in the dataset. This gives you a quick sense of the overall magnitude of your data, useful for understanding the cumulative impact or total quantity.
Average: The arithmetic mean, calculated by dividing the sum by the number of values. It represents the central tendency of your data, showing a typical value you might expect.
Median: The middle value when all data points are sorted in ascending order. If there’s an even number of values, it’s the average of the two middle ones. This measure of central tendency is robust against extreme values, unlike the average.
Variance: A measure of how much the values in your data spread out from the average, calculated as the average of squared differences from the mean (using \(n-1\) for a sample). It’s expressed in squared units and helps quantify data variability.
Standard Deviation: The square root of the variance, bringing the measure of spread back to the same units as your data. It tells you, on average, how far each value deviates from the mean, making it easier to interpret variability.
Maximum: The highest value present in your dataset. This highlights the upper boundary of your data range, useful for identifying peaks or potential outliers.
Minimum: The lowest value in your dataset. It shows the lower boundary, helping you understand the smallest observation and the full scope of your data’s range.
Mean Deviation: The average of the absolute differences between each value and the mean. This provides a straightforward measure of spread in the original units, less affected by extreme values compared to variance, offering a clear picture of typical deviation.
Range: The difference between the maximum and minimum values. It gives a simple, immediate view of the total spread of your data, highlighting the extent of variation from the lowest to the highest point.
Skewness: A measure of your data’s asymmetry around the mean. A positive value indicates a longer tail on the right (right-skewed), while a negative value suggests a longer left tail (left-skewed). Zero means symmetry, helping you understand the shape of your distribution.
Kurtosis: A measure of how heavy or light the tails of your data distribution are compared to a normal distribution. Positive kurtosis (leptokurtic) indicates heavy tails with more outliers, while negative (platykurtic) suggests lighter tails. A value near zero (mesokurtic) resembles a normal curve, aiding in outlier detection.