--- title: Getting Started description: A hands-on tutorial using the Iris dataset. Load data, explore statistics, create scatter plots, and save projects in MIDAS. priority: 0.8 --- # Getting Started {#getting-started} MIDAS is an exploratory data analysis tool that runs in your browser. Your data is processed locally and never sent to external servers ([details](privacy-security)). No installation required - start analyzing right away. ## Tutorial: Exploratory Data Analysis with the Iris Dataset {#tutorial-exploratory-data-analysis-with-the-iris-dataset} ### 1. Open Sample Data {#1-open-sample-data} This tutorial uses sample data. To use your own CSV file, see [Data Preparation and Import](data-preparation). 1. Open [MIDAS](https://app.midas-app.org/) - the launcher screen appears 2. Click **Iris** dataset from the "Sample Data" section 3. The project screen opens ![Selecting Iris dataset from Sample Data section in MIDAS launcher](../shared/images/getting-started-launcher.webp) The Iris dataset contains measurements of petals and sepals from three species of iris flowers (150 rows x 5 columns, measurement unit: cm). ### 2. Explore the Data {#2-explore-the-data} Three tabs open automatically: - **Data Table** (left): Displays data in tabular format - **Statistics** (top right): Shows statistics for selected columns - **Selected Rows** (bottom right): Details of selected rows Try the interactive demo below. Click columns to select them, or click rows to view their details. Each column header shows the [data type](data-preparation#data-types) (float64, string, etc.) and [measurement scale](concepts-data-types) (interval, nominal, etc.). Click the button at the right edge of a column to sort by that column. MIDAS automatically infers data types and measurement scales when loading data. If the inference is incorrect, right-click a column to change it. Measurement scales affect statistical analysis and graph creation. For example, mean and standard deviation are not calculated for nominal columns. See [Data Preparation and Import](data-preparation) for details. ### 3. View Basic Statistics {#3-view-basic-statistics} Let's check basic statistics to understand the data overview. 1. Click a column name in the Data Table tab (e.g., `sepal_length`) 2. A histogram and statistics automatically appear in the Statistics tab on the upper right ![Statistics for sepal_length column in Statistics tab: histogram, Moments, Spread, and Quantiles](../shared/images/getting-started-statistics.webp) **[Statistics displayed](basic-statistics)**: - **Moments**: mean, std (sample standard deviation), skewness, ex. kurt (excess kurtosis) - **Spread**: iqr (interquartile range), range - **Quantiles**: 0%(min), 1%, 5%, 10%, 25%, 50%, 75%, 90%, 95%, 99%, 100%(max) **Select rows from histogram**: Click a bar in the histogram to select rows within that range. Details appear in the **Selected Rows** tab at the bottom right. You can examine selected row data in detail or analyze only data within a specific range. ![Selected row details in Selected Rows tab: row data from histogram selection displayed in tabular format](../shared/images/getting-started-selected-rows.webp) Double-click a bin to open a new Filtered Data tab containing only the data in that bin. You can view statistics and create graphs from the filtered data. The original dataset is not modified. ![FilteredData tab opened by double-clicking a histogram bin](../shared/images/getting-started-double-click-bin.webp) **Select two columns to view relationships**: 1. With `sepal_length` selected, Ctrl/Cmd+click `sepal_width` 2. The Statistics tab displays a [scatter plot matrix and statistics comparison](basic-statistics#comparing-multiple-columns-relationships) ![Relationships between two columns in Statistics tab: scatter plot matrix and statistics comparison for sepal_length and sepal_width](../shared/images/getting-started-scatter-auto.webp) ### 4. Create Graphs {#4-create-graphs} Let's visualize the data to discover patterns. #### Create a Scatter Plot {#create-a-scatter-plot} 1. Select **Analysis** → **Graph Builder...** from the menu bar 2. Select **Scatter Plot** from **Graph Type** 3. Select from each dropdown: - **X-Axis**: `sepal_length (interval)` (sepal length) - **Y-Axis**: `sepal_width (interval)` (sepal width) - **Color (Optional)**: `species (nominal)` (iris species) 4. A scatter plot appears, color-coded by species ![Scatter plot created in Graph Builder: sepal_length × sepal_width relationship color-coded by species](../shared/images/getting-started-scatter.webp) You can compare distribution patterns across species. See [Creating Graphs](graph-basics) and [Advanced Graph Creation](custom-graph) for more details. ### 5. Save Your Project {#5-save-your-project} MIDAS offers two ways to save your work. #### Save to Browser {#save-to-browser} 1. Select **File** → **Save to Browser** (or Ctrl/Cmd+S) 2. The project is automatically saved to your browser Next time you open MIDAS, saved projects appear in the "Quick Access" section of the launcher screen for quick resumption. Clearing browser data will delete saved projects, so export important projects as files too. #### Export as File {#export-as-file} 1. Select **File** → **Export Project...** (or Ctrl/Cmd+Shift+S) 2. Confirm or edit the filename (defaults to project name) 3. Click **Save** 4. A project file (.mds format) is downloaded Exported MDS files can be shared with other users. Files are automatically signed with a digital signature, enabling tamper detection. See [Project Files (MDS)](mds-file-format) for details. #### Open an Exported File {#open-an-exported-file} 1. In the MIDAS launcher screen, click **Open File** 2. Select a saved `.mds` file 3. The project loads and restores to its saved state ## Next steps {#next-steps} - **[Creating Graphs](graph-basics)** - Create bar charts, scatter plots, pair plots, and more - **[Data Preparation and Import](data-preparation)** - Load your own CSV files - **[Regression Analysis](linear-regression)** - Model data with linear regression ## See also {#see-also} - **[Project Files (MDS)](mds-file-format)** - Project file format and data privacy - **[Sample Datasets](sample-datasets)** - Other sample data included in MIDAS - **[Data Types and Measurement Scales](concepts-data-types)** - Statistical meaning of measurement scales - **[Advanced Graph Creation](custom-graph)** - Flexible visualization with Grammar of Graphics - **[PWA and Offline Use](pwa-offline)** - Install as an app and work offline - **[Report](report)** - Compile graphs and statistics into a document - **[Storage Management](storage-management)** - Delete saved projects and check storage usage