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  • Course Outline
  • 1 - Databricks
    • Getting Started
    • Working with Notebooks
      • Adding Documentation
      • Built-In Visualizations
      • Import Data
      • Export Data
  • 2 - Introduction
    • Types of Questions
      • Finding Individual Records
      • Summarizing Data
      • Exploring Data
      • Drawing Inferences From Data
      • Predicting Information
      • Finding Causality
    • Steps in Data Analytics
    • Dimensions of Data Sets
    • Dimensions of Records
    • Dimensions of Fields
    • Data Types and Scales
  • 3 - SQL
    • Basic SQL
      • What is SQL?
      • Import Data
      • Select Columns
      • Filter Rows
      • Aggregate and Group Rows
      • Filter Aggregated Rows
      • Sort Rows
    • Advanced SQL
      • Views
      • Set Operators
      • Subqueries
      • Window Functions
      • Date and Time
      • Arrays
      • JSON
      • Statistical Analysis
    • Multiple Data Sets with SQL
    • Text with SQL
      • Search Text
      • Analyzing Words
        • Prefilter the Data
        • Clean and Normalize
        • Tokenize and Count
        • Filter Stop Words
        • POS Tagging
      • Word Pairs
      • Extract Emoticons
  • 4 - Python
    • Python for Data Analytics
      • What is Python?
    • Natural Language Processing
  • 5 - R
    • R Basics
  • 6 - Visualization
    • Why Visualize Data?
    • Data Visualization with R
    • Types of Visualizations
      • Developments and Trends
      • Distributions
    • Pitfalls in Data Visualization
  • 7 - Tableau
    • Getting Data Into Tableau
  • 8 - Spreadsheets
    • What Is A Spreadsheet?
  • Data & Exercises
    • Simpsons
    • Covid19
    • TED Talks
    • Lemonade Market Research
    • Chicago Crimes
    • Tweets of German Politicians
    • Amazon Product Reviews
    • REWE Online Products
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  • Headings
  • Links
  • Lists
  • Images
  • Mixing Markdown with HTML

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  1. 1 - Databricks
  2. Working with Notebooks

Adding Documentation

We can use Markdown in Databricks notebooks to create a structured and formatted documentation alongside our analysis. This article introduces the most important features of Markdown.

PreviousWorking with NotebooksNextBuilt-In Visualizations

Last updated 4 years ago

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The following link contains a Markdown cheat sheet that summarizes the most important markups we can use:

Headings

You can create headings in Markdown using the hashtag symbol:

# This is a heading of first degree
## This is a hedaing of 2nd degree
### This is a heading of 3rd degree

Links

You can create a link in Markdown by putting the linked text in square brackets and the URL to which you want to link in brackets:

The following link takes you somewhere: [Link somewhere](htttps://somewhere.com)

Lists

You can create simple lists using the minus symbol. Nested lists are also possible by adding a tab:

This is a list:

- Top level item
- Another top level item
    - A subitem
    - Another subitem
- Last top level item

Images

You can add images to your notebook by putting an exclamation mark in front of the square brackets, in which you define an alternative text to show if the image can't be displayed. The URL of the image must be put in brackets following the square brackets. Optionally, you can add a title that is shown on hover.

![My image](https://somewhere.com/image.jpg "An image hover title")

Mixing Markdown with HTML

If Markdown isn't enough, you can use HTML within a markdown block as well. One use case for me is to include links in notebooks that open in a new tab:

# This is a heading of first degree
---
Find more information <a href="https://more.info" target="_blank">here</a>.
Markdown Cheatsheet · adam-p/markdown-here WikiGitHub
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