restructure fixes

pull/49/head
Jasmine 4 years ago
parent 5a6577d054
commit 91824622aa

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# Working with Data: Spreadsheets
# Working with Data: Non-Relational Data
Many data scientists will not pick spreadsheets as their first tool for various and valid reasons. However, it's a popular way to store and explore data because it requires less work to setup and get started. In this lesson you'll learn the basic components of a spreadsheet, how to apply formulas and functions, generating charts and pivot tables, and how to sort and filter a spreadsheet. This lesson provides foundational knowledge of spreadsheets in the rare event that you find yourself working with with them. The examples will be illustrated with Microsoft Excel, but most of the parts and topics will have similar names and steps in comparison to other spreadsheet software.
Data can come from various sources, and is not limited to relational databases. This lesson focuses on non relational data and will cover spreadsheets and NoSQL.
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## Spreadsheets
## Introduction
Many data scientists will not pick spreadsheets as their first tool for various and valid reasons. However, it's a popular way to store and explore data because it requires less work to setup and get started. In this lesson you'll learn the basic components of a spreadsheet, how to apply formulas and functions, generating charts and pivot tables, and how to sort and filter a spreadsheet. This lesson provides foundational knowledge of spreadsheets in the rare event that you find yourself working with with them. The examples will be illustrated with Microsoft Excel, but most of the parts and topics will have similar names and steps in comparison to other spreadsheet software.
![An empty Microsoft Excel workbook with two worksheets](parts-of-spreadsheet.png)
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Cell
Header
## Exploring Values
Date (slash or dash) times (colon)
### Exploring Values
Date (slash or dash) times (colon)
Numbers
Text/alpha characters
Autofill?
## Formulas
### Formulas and Functions
- How to start one (equal and cell id)
- formula bar
- copying by dragging over by fill handle
## Functions
- Basic mathematics
- Sum
- Average
- XLookup/lookup functions -relationships
## Charts
### Charts
- Creating a chart
- Pivot Tables
## Misc
-Sorting
-Filtering
- Pivot table - summary totals
## NoSQL
### Types
Document
Key Value
Graph
Columnar
###
## Pre-Lecture Quiz
[Pre-lecture quiz]()

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# Working with Data: Relational Databases
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# Working with Data: NoSQL
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# Working with Data: Cleaning and Transformations
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# The Data Science Lifecycle: Capturing
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# The Data Science Lifecycle: Processing
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,19 +0,0 @@
# The Data Science Lifecycle: Analyzing
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# The Data Science Lifecycle: Communication
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,19 +0,0 @@
# The Data Science Lifecycle: Maintaining
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

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# Data Science in the Cloud: TBD
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

@ -1,8 +0,0 @@
# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,8 +0,0 @@
# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,19 +0,0 @@
# Data Science in the Cloud: TBD
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

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# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,19 +0,0 @@
# Data Science in the Wild: TBD
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

@ -1,8 +0,0 @@
# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |

@ -1,19 +0,0 @@
# Data Science in the Wild: TBD
## Pre-Lecture Quiz
[Pre-lecture quiz]()
## 🚀 Challenge
## Post-Lecture Quiz
[Post-lecture quiz]()
## Review & Self Study
## Assignment
[Assignment Title](assignment.md)

@ -1,8 +0,0 @@
# Title
## Instructions
## Rubric
Exemplary | Adequate | Needs Improvement
--- | --- | -- |
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