DataviewJS: Sum of Frontmatter Variables, Book Database

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Topic : 1/4

Summary
  • How to simplify nested choice operators via JavaScript Objects? (DQL10_Q1, DQL10_Q3, DQL20_Q1, DQL10, DQL20)
  • How to simplify multiple OR operators via JavaScript Objects? (DVJS01_Q1, DVJS01_Q2,DVJS10_Q1, DVJS10_Q2, DVJS10_Q3, DVJS01, DVJS10)
  • How to simplify the following output?(DQL10, DQL20, DVJS01, DVJS10)
```md
This year, I've read 2 books and I've listened to 2 audiobooks (of which 1 were podcasts), for an overall 4 books and audiobooks read.

I've read 0 pages this year. And I've listened to 0.0 hours.

The average rating for the overall 4 books and audiobooks is 4.5 out of 10.

Average book length: 0 pages

Average audiobook length: 0.0 hours

Average pages read per day: 0.0 pages
```

Test

Summary
  • dataview: v0.5.46

Input

Summary

dictionary files:

  • Location: “100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data”

folder: 03

  • filename : dic_19660311
---
Date: 1966-03-11
tags: [Favorite]
Alias: "Javascript: The Definitive Guide, 7/e"
Medium: "Book"
Author: "David Flanagan"
 
Country: "US, GB"
DateStarted: "2020-06-23"
DateFinished: "2020-07-25"
Status: "done"

Year: 2020
Rating: 7
Pages: 681
Hours: 
Cover: https://m.media-amazon.com/images/W/WEBP\_402378-T2/images/I/919ZMTHDPBL.\_AC\_SX75\_CR,0,0,75,75\_.jpg
---



# Javascript: The Definitive Guide, 7/e
- What :: [Javascript: The Definitive Guide, 7/e](https://www.amazon.com/-/es/David-Flanagan/dp/1491952024/ref=sr_1_1?__mk_es_US=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=32QHTGRP393RS&keywords=Javascript&qid=1672211738&s=books&sprefix=javascript%2Cstripbooks-intl-ship%2C286&sr=1-1)
- Authors :: 
- Keywords :: 
- Summaries :: 
- Comments :: 
- Downloaded ::

folder: 04

  • filename : dic_19660411
---
Date: 1966-04-11
tags: [Favorite]
Alias: "UNIX Shells by Example, 4/e"
Medium: "Audiobook"
Author: "Ellie Quigley"

Country: "IT"
DateStarted: "2004-09-01"
DateFinished: "2005-12-25"
Status: "done"

Year: 2004
Rating: 9
Pages: 
Hours: 1200
Cover: https://m.media-amazon.com/images/W/WEBP\_402378-T2/images/I/91vUmLEjbHL.\_AC\_SX75\_CR,0,0,75,75\_.jpg
---


# UNIX Shells by Example, 4/e
- What :: [UNIX Shells by Example, 4/e](https://www.amazon.com/-/es/Ellie-Quigley/dp/013147572X/ref=sr_1_1?__mk_es_US=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=IHF5F5CXXTV0&keywords=UNIX+Shells+by+Example&qid=1672214391&s=books&sprefix=unix+shells+by+example%2Cstripbooks-intl-ship%2C250&sr=1-1)
- Authors :: 
- Keywords :: 
- Summaries :: 
- Comments :: 
- Downloaded ::

folder: 05

  • filename : dic_19660511
---
Date: 1966-05-11
tags: [Favorite]
Alias: "P_Podcast"
Medium: "Podcast"
Author: "YYY"

Country: "DE"
DateStarted: "2022-12-16"
DateFinished: "2022-12-17"
Status: "done"

Year: 2000
Rating: 3
Pages: 
Hours: 11
Cover: https://media.wnyc.org/i/200/200/c/70/2022/12/NullandVoid_1600x1200.png
---



# Null and Void
- What :: [Null and Void](https://radiolab.org/episodes/null-and-void-2212)
- Authors :: 
- Keywords :: 
- Summaries :: 
- Comments :: 
- Downloaded ::

folder: 06

  • filename : dic_19660611
---
Date: 1966-06-11
tags: [Favorite]
Alias: "Perl by Example, 5/e"
Medium: "eBook"
Author: "Ellie Quigley"

Country: "FR"
DateStarted: "2014-12-17"
DateFinished: "2015-12-21"
Status: "done"

Year: 2014
Rating: 10
Pages: 888
Hours: 
Cover: https://m.media-amazon.com/images/W/WEBP\_402378-T2/images/I/41aGGHu7Q-L.\_AC\_SX75\_CR,0,0,75,75\_.jpg
---



# Perl by Example, 5/e
- What :: [Perl by Example, 5/e](https://www.amazon.com/-/es/Ellie-Quigley/dp/0133760812/ref=sr_1_1?__mk_es_US=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=207AKU6YA3671&keywords=perl+by+example&qid=1672212277&s=books&sprefix=perl+by+exampl%2Cstripbooks-intl-ship%2C432&sr=1-1)
- Authors :: 
- Keywords :: 
- Summaries :: 
- Comments :: 
- Downloaded ::

folder: 08_excluded

  • filename : dic_19750801
---
Date: 1966-06-11
tags: [Favorite]
Alias: "Perl by Example, 5/e"
Medium: "eBook"
Author: "Ellie Quigley"

Country: "FR"
DateStarted: "2014-12-17"
DateFinished: "2015-12-21"
Status: "done"

Year: 2014
Rating: 10
Pages: 888
Hours: 
Cover: https://m.media-amazon.com/images/W/WEBP\_402378-T2/images/I/41aGGHu7Q-L.\_AC\_SX75\_CR,0,0,75,75\_.jpg
---



# Perl by Example, 5/e
- What :: [Perl by Example, 5/e](https://www.amazon.com/-/es/Ellie-Quigley/dp/0133760812/ref=sr_1_1?__mk_es_US=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=207AKU6YA3671&keywords=perl+by+example&qid=1672212277&s=books&sprefix=perl+by+exampl%2Cstripbooks-intl-ship%2C432&sr=1-1)
- Authors :: 
- Keywords :: 
- Summaries :: 
- Comments :: 
- Downloaded ::

DQL10_sum_Pages_or_Hours_groupBy_P_Category_via_JavaScript_Objects_and_TABLE

Summary

Main DQL

Code Name Data type Group By Purposes Remark
DQL10
_sum_Pages_or_Hours
_groupBy_P_Category
via_JavaScript_Objects
and_TABLE		 (A dynamical page field)
P_Category:
1.“Reading”
2.“Listening”

(A page field)
Medium:
1.“Book”
2.“GraphicNovel”
3.“eBook”
4.“Article”

5.“Audiobook”
6.“Podcast”
7.“radio”		 yes
(once)		 1.To add four new dynamical fields including P_Category, Q_PagesOrHours, R_Unit and S_NumberOfDigits into each page by using the FLATTEN operator
2.To group by P_Category
3.To add two new dynamical fields including G_Medium_Counts and G_Medium_Lengths into each group
4.To add two new dynamical fields including G_Medium_Average_Lengths and today_ooo into each group

5.To do some simple statistics:
5.1 To count file.link by each group
5.2 To sum up Pages(or Hours) by each group
5.3 To get the average Pages(or Hours) by each group
5.4 To get the average Pages(or Hours) read(or listened) per day by each group

6.To display the result as a table

Notes

Summary

Q1: What does the following code mean(WHERE P_Category)?

Summary_Q1
Original Example: Q1 (To be modified)

Notes:
1.The P_Category field doesn’t exist in a note.
2.It is created by using the FLATTEN operator.
3.In other words, each Medium is dynamically categorized by P_Category.

Purposes:
1.To simplify multiple ‘OR’ operators via JavaScript Objects
2.For best performance
3.For easier reading
4.For easier modification
5.For easier debugging
Tips: The value of the P_Category is “Reading”, “Listening” or undefined. Therefore, the value except undefined is truthy.

```dataview

WHERE Status != null
WHERE Medium != null


// T01. define page.P_Category: Alias="Medium Category"
// page.P_Category="Reading" or "Listening"
// Each page.Medium is dynamically categorized by page.P_Category.
// #####################################################################
// let page.P_Category = page.P_Category; 
FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening"
    
}[Medium] AS P_Category


// The multiple 'OR' operators are simplified via JavaScript Objects.
WHERE P_Category



```

A1:

Another Example: A1_11

Purposes: To use multiple ‘OR’ operators

```dataview

WHERE Status != null
WHERE Medium != null



WHERE                           
      Medium = "Book"          // using multiple 'OR' operators
   OR Medium = "GraphicNovel"  // using multiple 'OR' operators
   OR Medium = "eBook"         // using multiple 'OR' operators
   OR Medium = "Article"       // using multiple 'OR' operators
   
   OR Medium = "Audiobook"     // using multiple 'OR' operators
   OR Medium = "Podcast"       // using multiple 'OR' operators
   OR Medium = "radio"         // using multiple 'OR' operators


// T01. define page.P_Category: Alias="Medium Category"
// page.P_Category="Reading" or "Listening"
// Each page.Medium is dynamically categorized by page.P_Category.
// #####################################################################
// let page.P_Category = page.P_Category; 
FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening"    
}[Medium] AS P_Category


```

Q2: How to modify the DQL10 when “typeP”, “typeQ” or “typeR” (page.P_Category: “Reading”, “Listening”, “Listening”)(units: “p”, “h”, “h”) is added to a Medium field content?

Summary_Q2
Original Example: Q2 (To be modified)
```dataview

WHERE Status != null
WHERE Medium != null


// T01. define page.P_Category: Alias="Medium Category"
// page.P_Category="Reading" or "Listening"
// Each page.Medium is dynamically categorized by page.P_Category.
// #####################################################################
// let page.P_Category = page.P_Category; 
FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening"    
}[Medium] AS P_Category


WHERE P_Category 


```

A2:

Another Example: A2_21
```dataview

WHERE Status != null
WHERE Medium != null


// T01. define page.P_Category: Alias="Medium Category"
// page.P_Category="Reading" or "Listening"
// Each page.Medium is dynamically categorized by page.P_Category.
// #####################################################################
// let page.P_Category = page.P_Category; 
FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    "typeP":  "Reading",       // Added by Justdoitcc 2022-12-30
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening",
    "typeQ":  "Listening",     // Added by Justdoitcc 2022-12-30
    "typeR":  "Listening"      // Added by Justdoitcc 2022-12-30
}[Medium] AS P_Category


WHERE P_Category

```

Q3: What does the following code mean(FLATTEN ... AS S_NumberOfDigits)?

Summary_Q3
Original Example: Code DQL10_Q3 (To be explained)

The original DQL with a new field like S_NumberOfDigits doesn’t contain a choice expression.
Purposes:
1.To simplify multiple choice functions via JavaScript Objects
2.For best performance
3.For easier reading
4.For easier modification
5.For easier debugging

```dataview
TABLE WITHOUT ID
      
      // Not to use a `choice` expression
      round(G_Medium_Average_Lengths, rows.S_NumberOfDigits[0]) + rows.R_Unit[0]
      AS "Average Lengths"



FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC


// T07. define page.S_NumberOfDigits: Alias="Number of Digits"
// P_Category="Reading"    => 0
// P_Category="Listening"  => 1
// To be used in the step:To get the Average Lengths by each group
// #####################################################################
// let page.S_NumberOfDigits = 0;
FLATTEN {
    "Reading": 0,
    "Listening": 1
}[S_NumberOfDigits] AS S_NumberOfDigits


GROUP BY P_Category AS GP_Category
SORT GP_Category DESC


```

A3:

Another Example: Code DQL10_A3_31

The DQL10_A3_31 without a new field like S_NumberOfDigits contains a choice expression.

```dataview
TABLE WITHOUT ID

      // To use a `choice` expression
      choice(GP_Category = "Reading", 
          round(G_Medium_Average_Lengths, 0) + rows.R_Unit[0], 
          round(G_Medium_Average_Lengths, 1) + rows.R_Unit[0]
      ) 
      AS "Average Lengths"

FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC


// without FLATTEN ... AS S_NumberOfDigits




GROUP BY P_Category AS GP_Category
SORT GP_Category DESC


```

Code DQL10_sum_Pages_or_Hours_groupBy_P_Category_via_JavaScript_Objects_and_TABLE

Summary_code 
title: DQL10_sum_Pages_or_Hours_groupBy_P_Category_via_JavaScript_Objects_and_TABLE =>1.To add four new dynamical fields including `P_Category`, `Q_PagesOrHours`, `R_Unit` and `S_NumberOfDigits` into each `page` by using the `FLATTEN` operator 2.To group by `P_Category` 3.To add two new dynamical fields including `G_Medium_Counts` and `G_Medium_Lengths` into each `group` 4.To add two new dynamical fields including `G_Medium_Average_Lengths` and `today_ooo` into each `group` 5.To do some simple statistics: 5.1 To count `file.link` by each group 5.2 To sum up `Pages`(or `Hours`) by each group 5.3 To get the average `Pages`(or `Hours`) by each group 5.4 To get the average `Pages`(or `Hours`) read(or listened) per day by each group 6.To display the result as a table
collapse: open
icon: 
color: 
```dataview
TABLE WITHOUT ID

      GP_Category AS "Categories",  
      
      rows.file.link AS "Each Link",
      rows.Medium AS "Each Medium",
      
      rows.Q_PagesOrHours AS "Each Length",
      rows.R_Unit AS "Each Unit",
   
      G_Medium_Counts AS "Medium Counts",  
      G_Medium_Lengths AS "Medium Lengths",
    
    
      round(G_Medium_Average_Lengths, rows.S_NumberOfDigits[0]) + rows.R_Unit[0]
      AS "Average Lengths",
      
      
      round(G_Medium_Lengths / today_ooo , 1) + rows.R_Unit[0] AS "Average Lengths read/listened per day"

  
FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC

FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening"    
}[Medium] AS P_Category


WHERE P_Category


FLATTEN {
    "Reading": Pages,
    "Listening": Hours
}[P_Category] AS Q_PagesOrHours


FLATTEN {
    "Reading": " pages",
    "Listening": " hours"
}[P_Category] AS R_Unit


FLATTEN {
    "Reading": 0,
    "Listening": 1
}[P_Category] AS S_NumberOfDigits


GROUP BY P_Category AS GP_Category
SORT GP_Category DESC


FLATTEN length(rows.file.link) AS G_Medium_Counts
FLATTEN sum(rows.Q_PagesOrHours) AS G_Medium_Lengths
FLATTEN G_Medium_Lengths/G_Medium_Counts AS G_Medium_Average_Lengths


FLATTEN number(dateformat(date("2022-12-30"),"ooo")) AS today_ooo

```

Screenshots(DQL10): today=“2022-12-30”

20230117_Q80_DQL10_output_a01
20230117_Q80_DQL10_output_a011430×470 79.5 KB

DQL20_sum_Pages_or_Hours_groupBy_P_Category_groupBy_true_via_JavaScript_Objects_and_TABLE

Summary

Main DQL

Code Name Data type Group By Purposes Remark
DQL20
_sum_Pages_or_Hours
_groupBy_P_Category
_groupBy_true
_via_JavaScript_Objects
_and_TABLE		 (A dynamical page field)
P_Category:
1.“Reading”
2.“Listening”

(A page field)
Medium:
1.“Book”
2.“GraphicNovel”
3.“eBook”
4.“Article”

5.“Audiobook”
6.“Podcast”
7.“radio”		 yes
(twice)		 1.To add four new dynamical fields including P_Category, Q_PagesOrHours, R_Unit and S_NumberOfDigits into each page by using the FLATTEN operator
2.To group by P_Category
3.To add two new dynamical fields including G_Medium_Counts and G_Medium_Lengths into each group
4.To add two new dynamical fields including G_Medium_Average_Lengths and today_ooo into each group

5.To do some simple statistics:
5.1 To count file.link by each group
5.2 To sum up Pages(or Hours) by each group
5.3 To get the average Pages(or Hours) by each group
5.4 To get the average Pages(or Hours) read(or listened) per day by each group
5.5 To count the overall file.link
5.6 To get the overall average Rating

6.To display the result as a table		 1.The DQL20 is based on the DQL10.
1.1 added: 5.5 To count the overall file.link
1.2 added: 5.6 To get the overall average Rating

Notes:
1.The P_Category field doesn’t exist in a note.
2.It is created by using the FLATTEN operator.
3.In other words, each page.Medium is dynamically categorized by page.P_Category.

Notes

Summary

Q1: What does the following code mean(FLATTEN ... AS S_NumberOfDigits)? ?

Summary_Q1
Original Example: Code DQL20_Q1 (To be explained)

The original DQL with a new field like S_NumberOfDigits doesn’t contain a choice expression.
Purposes:
1.To simplify multiple choice functions via JavaScript Objects
2.For best performance
3.For easier reading
4.For easier modification
5.For easier debugging

```dataview
TABLE WITHOUT ID
      
      // Not to use a `choice` expression
      map(rows, (rows) =>       
          round(rows.G_Medium_Average_Lengths, rows.rows.S_NumberOfDigits[0]) + rows.rows.R_Unit[0]
      )
      AS "Average Lengths"



FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC


// with FLATTEN ... AS S_NumberOfDigits
FLATTEN {
    "Reading": 0,
    "Listening": 1
}[S_NumberOfDigits] AS S_NumberOfDigits


GROUP BY P_Category AS GP_Category
SORT GP_Category DESC




GROUP BY TRUE

```

A1:

Another Example: Code DQL20_A1_11

The A1_11 DQL without a new field like S_NumberOfDigits contains a choice expression.

```dataview
TABLE WITHOUT ID

      // To use a `choice` expression
      map(rows, (rows) =>       
          choice(rows.GP_Category = "Reading", 
              round(rows.G_Medium_Average_Lengths, 0) + rows.rows.R_Unit[0], 
              round(rows.G_Medium_Average_Lengths, 1) + rows.rows.R_Unit[0]
         )   
      )
      AS "Average Lengths"

FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC

// without FLATTEN ... AS S_NumberOfDigits




GROUP BY P_Category AS GP_Category
SORT GP_Category DESC



GROUP BY TRUE

```

Code DQL20_sum_Pages_or_Hours_groupBy_P_Category_groupBy_true_via_JavaScript_Objects_and_TABLE

Summary_code 
title: DQL20_sum_Pages_or_Hours_groupBy_P_Category_groupBy_true_via_JavaScript_Objects_and_TABLE =>1.To add four new dynamical fields including `P_Category`, `Q_PagesOrHours`, `R_Unit` and `S_NumberOfDigits` into each `page` by using the `FLATTEN` operator 2.To group by `P_Category` 3.To add two new dynamical fields including `G_Medium_Counts` and `G_Medium_Lengths` into each `group` 4.To add two new dynamical fields including `G_Medium_Average_Lengths` and `today_ooo` into each `group` 5.To do some simple statistics: 5.1 To count `file.link` by each group 5.2 To sum up `Pages`(or `Hours`) by each group 5.3 To get the average `Pages`(or `Hours`) by each group 5.4 To get the average `Pages`(or `Hours`) read(or listened) per day by each group 5.5 To count the overall `file.link` 5.6 To get the overall average `Rating` 6.To display the result as a table
collapse: open
icon: 
color: 
```dataview
TABLE WITHOUT ID

      rows.GP_Category AS "Categories",
      
      rows.rows.file.link AS "Each Link",
      rows.rows.Medium AS "Each Medium",
      
      rows.rows.Q_PagesOrHours AS "Each Length",
      rows.rows.R_Unit AS "Each Unit",     
   
      rows.G_Medium_Counts AS "Medium Counts",  
      rows.G_Medium_Lengths AS "Medium Lengths",      
      
      
      map(rows, (rows) =>       
          round(rows.G_Medium_Average_Lengths, rows.rows.S_NumberOfDigits[0]) + rows.rows.R_Unit[0]
      )
      AS "Average Lengths",

     
      map(rows, (rows) =>     
          round(rows.G_Medium_Lengths / today_ooo , 1) + rows.rows.R_Unit[0] 
      )
      AS "Average Lengths read/listen per day",     


      G2_OverallCounts AS "Overall Count",
      
      round(G2_OverallRatings / G2_OverallCounts , 1) AS "Average Rating(out of 10)"
      
      
FROM "100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data"

WHERE Status != null
WHERE Medium != null
SORT file.name ASC

FLATTEN {
    "Book":  "Reading",
    "GraphicNovel":  "Reading",
    "eBook":  "Reading",
    "Article":  "Reading",
    
    "Audiobook":  "Listening",
    "Podcast":  "Listening",
    "radio":  "Listening"    
}[Medium] AS P_Category


WHERE P_Category


FLATTEN {
    "Reading": Pages,
    "Listening": Hours
}[P_Category] AS Q_PagesOrHours


FLATTEN {
    "Reading": " pages",
    "Listening": " hours"
}[P_Category] AS R_Unit


FLATTEN {
    "Reading": 0,
    "Listening": 1
}[P_Category] AS S_NumberOfDigits


GROUP BY P_Category AS GP_Category
SORT GP_Category DESC


FLATTEN length(rows.file.link) AS G_Medium_Counts
FLATTEN sum(rows.Q_PagesOrHours) AS G_Medium_Lengths
FLATTEN G_Medium_Lengths/G_Medium_Counts AS G_Medium_Average_Lengths

GROUP BY TRUE


FLATTEN sum(map(rows.G_Medium_Counts, (e) => sum(default(e, 0)))) AS G2_OverallCounts
FLATTEN sum(map(rows.rows.Rating, (e) => sum(default(e, 0)))) AS G2_OverallRatings


FLATTEN number(dateformat(date("2022-12-30"),"ooo")) AS today_ooo

```

Screenshots(DQL20): today=“2022-12-30”

20230117_Q80_DQL20_output_a01
20230117_Q80_DQL20_output_a011430×391 63.3 KB

Conclusion

Summary
Code Name Unique Name What to maintain Remark
DQL10 Q80_DQL10 1.Three customizable variables in different expressions:
1.1 FROM “…”
1.2 FLATTEN {…}[Medium] AS P_Category
1.3 FLATTEN number(dateformat(date(“…”),“ooo”)) AS today_ooo
DQL20 Q80_DQL20 The same as the Q80_DQL10
DVJS01 Q80_DVJS01 1.Three customizable variables in different expressions:
1.1
// M09
let h_medium_category_of = {
    Book: “Reading”,
    GraphicNovel: “Reading”,
    eBook: “Reading”,
    Article: “Reading”,

    Audiobook: “Listening”,
    Podcast: “Listening”,
    radio: “Listening”,

};

1.2
// M11
let pages = dv.pages(‘“100_Project/01_dataviewjs/01_by_example/Q80_MediumCat/Q80_test_data”’)

1.3
// M13
let s_today = “2022-12-30”;
DVJS10 Q80_DVJS10 The same as the Q80_DVJS01

Reference

Summary

Q19_Sum

Q24_SumDuration

Q26_ReadingExercise

The DateTime formats

Related Resources

Summary

Q80_MediumCat

Q78_MediumCat

FLATTEN

Q20_Flags : Flags01

Q25_MetaFunction : Flags02

MetaFunction : Flags03

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