Mito
Mito for Streamlit
  • Mito Documentation
  • Getting Started
    • Installing Mito
      • Fixing Common Install Errors
      • Installing Mito in a Docker Container
      • Installing Mito for Streamlit
      • Installing Mito for Dash
      • Installing Mito in a Jupyter Notebook Directly
      • Installing Mito in Vertex AI
      • Setting Up a Virtual Environment
  • Data Copilot
    • Data Copilot Core Concepts
    • Agent
    • Chat
    • Autocomplete
    • Smart Debugging
    • Configuration Options
    • AI Data Usage FAQ
  • Mito Spreadsheet
    • Core Concepts
    • Creating a Mitosheet
      • Open Existing Virtual Environments
    • Importing Data
      • Importing CSV Files
      • Importing from Excel Files
      • Importing Dataframes
      • Importing from a remote drive
      • Import: Generated UI from any Python Function
      • Importing from other sources
    • Graphing
      • Graph Creation
      • Graph Styling
      • Graph Export
    • Pivoting/Group By
    • Filter
      • Filter By Condition
      • Filter By Value
    • Mito AI
    • Summary Statistics
    • Type Changes
    • Spreadsheet Formulas
      • Custom Spreadsheet Functions
      • Formula Reference
      • Using VLOOKUP
    • Editing Individual Cells
    • Combining Dataframes
      • Merge (horizontal)
      • Concatenate (horizontal)
      • Anti-merge (unique)
    • Sort Data
    • Split Text to Columns
    • Deleting Columns
    • Deleting Rows
    • Column Headers
      • Editing Column Headers
      • Promote Row to Header
    • Deduplicate
    • Fill NaN Values
    • Transpose
    • Reset Index
    • Unpivot a Dataframe (Melt)
    • Formatting
      • Column Formatting
      • Dataframe Colors
      • Conditional Formatting
    • Exporting Data
      • Download as CSV
      • Download as Excel
      • Generate code to create Excel and CSV reports
    • Using the Generated Code
      • Turn generated code into functions
    • Changing Imported Data
    • Code Snippets
    • Custom Editors: Autogenerate UI from Any Function
    • Find and Replace
    • Bulk column header edits
    • Code Options
    • Scheduling your Automation
    • Keyboard Shortcuts
    • Upgrading Mito
    • Enterprise Logging
  • Mito for Streamlit
    • Getting Started with Mito for Streamlit
    • Streamlit Overview
    • Create a Mito for Streamlit App
    • API Reference
      • Understanding import_folder
      • RunnableAnalysis class
      • Column Definitions
    • Streamlit App Gallery
    • Experienced Streamlit Users
    • Common Design Patterns
      • Deploying Mito for Streamlit in a Docker Image
      • Using Mito for Final Mile Data Cleaning
  • Mito for Dash
    • Getting Started
    • Dash Overview
    • Your First Dash App with Mito
    • Mito vs. Other Dash Components
    • API Reference
      • Understanding import_folder
    • Dash App Gallery
    • Common Design Patterns
      • Refresh Sheet Data Periodically
      • Change Sheet Data from a Select
      • Filter Other Elements to Data Selected in Mito
      • Graph New Data after Edits to Mito
      • Set Mito Spreadsheet Theme
  • Tutorials
    • Pass a dataframe into Mito
    • Create a line chart of time series data
    • Delete Columns with Missing Values
    • Split a column on delimiter
    • Rerun analysis on new data
    • Calculate the difference between rows
    • Calculate each cell's percent total of column
    • Import multiple tables from one Excel sheet
    • Share Mito Spreadsheets Across Users
  • Misc
    • Release Notes
      • April 15 - Now Streaming (0.1.18)
      • March 21 - Smarter, Faster, Stronger Agents
      • February 25 - Agent Mode QoL Improvements
      • February 18 - Mito Agents
      • January 2nd - Inline Completions Arrive
      • December 6th - Smarter Workflow
      • November 27th - @ Mentions, Mito AI Server
      • November 4th, 2024 - Hello Mito AI
      • October 8, 2024 - JupyterLab 4
      • Aug 29th, 2024
      • June 12, 2024
      • March 19, 2024
      • March 13th, 2024
      • February 12th, 2024: Graphing Improvements
      • January 25th, 2024
      • January 5th, 2023: Keyboard Shortcuts
      • December 6, 2023: New Context Menu
      • November 28, 2023: Mito's New Toolbar
      • November 7, 2023: Multiplayer Dash
      • October 23, 2023: RunnableAnalysis class
      • October 16, 2023: Mito for Dash, Custom Editors
      • September 29, 2023: VLOOKUP and Find and Replace!
      • September 7, 2023
      • August 2, 2023: Mito for Streamlit!
      • July 10, 2023
      • May 31, 2023: Mito AI Recon
      • May 19, 2023: Mito AI Chat!
      • April 27, 2023: Generate Functions, Performance improvements, bulk column header transformations
      • April 18, 2023: Cell Editor Improvements, BYO Large Language Model, and more
      • April 10, 2023: AI Access, Excel-like Cell Editor, Performance Improvements
      • April 5, 2023: Range formulas, Pandas 2.0, Snowflake Views
      • March 29, 2023: Excel Range Import Improvements
      • March 14, 2023: Mito AI, Public Interface Versioning
      • February 28, 2023: In-place Pivot Errors
      • February 7, 2023: Excel-like Formulas, Snowflake Import
      • January 23, 2023: Excel range importing
      • January 8, 2023: Custom Code snippets
      • December 26, 2022: Code snippets and bug fixes
      • December 12, 2022: Group Dates in Pivot Tables, Reduced Dependencies
      • November 15, 2022: Filter in Pivot
      • November 9, 2022: Import and Enterprise Config
      • October 31, 2022: Replay Analysis Improvements
      • Old Release Notes
      • August 10, 2023: Export Formatting to Excel
    • Mito Enterprise Features
    • FAQ
    • Terms of Service
    • Privacy Policy
  • Mito
Powered by GitBook

© Mito

On this page
  • Exporting a graph
  • How to use the Exported HTML graph code

Was this helpful?

  1. Mito Spreadsheet
  2. Graphing

Graph Export

Export your graphs as Python code, images or HTML files to share your insights with your peers.

Exporting a graph

  1. Click the Export button in the Chart Design tab.

  2. Click the export method you want:

    1. Copy Show Graph Code: Copy the Plotly graph code that displays the graph in the notebook to your clipboard so you can paste it into a code cell.

    2. Copy Export HTML Graph Code: Copy the Plotly graph code that exports the graph as an interactive HTML file to your clipboard so you can paste it into a code cell. Executing the code will create the html file in the same folder the notebook is in.

    3. Download as PNG: Download the graph as a PNG to your Downloads folder.

How to use the Exported HTML graph code

Interactive graphs are a fantastic way to share analyses with colleagues. It allows them to zoom in on specific sections of the graph and identify specific data points.

To create an HTML graph file:

  1. Create a graph using Mito

  2. Click the Copy Export HTML Graph Code button in the Export dropdown on the Chart Design tab of the toolbar.

  3. Paste the code into a new code cell and execute the code.

  4. The html file will appear in the the same folder as your notebook.

The file contains all of the libraries and data needed to repopulate the graph, so you can attatch the file to an email or post it on an internal wiki without anything else.

PreviousGraph StylingNextPivoting/Group By

Last updated 1 year ago

Was this helpful?