Help with Compound Dataview Values

[justdoitcc]

Topic : 1/2

Summary

1. How to extract the Fund or ActionItem via the field Monitoring? (DQL01, DQL10, DVJS03, DVJS10)
2. How to filter by Fund or ActionItem via the field Monitoring, such as “Monitoring:: FundQ | Do That0403”, from the Markdown files with the case_DVIF_DSS structure? (DQL10, DVJS03, DVJS10)
3. How to transform the DQL10 query into a DVJS code with the FLATTEN methods step by step? (DVJS10, 【DQL10 > Notes > Q2】)
4. How to filter and sort an AoH(an Array of JavaScript Objects) and render a table via a DVJS code? (DVJS01)

NOTE:

1. The DVJS01 can help you to figure out the basic DVJS code.
2. The DVJS10 performs the same operations as the DQL10 with the FLATTEN methods step by step.
3. The DVJS10 can help you to figure out the DQL10, including how to use the FLATTEN operator.

---

Structures: case_DVIF_DSS

Summary

DVIF = Dataview Inline Fields

Definitions:

Structure Code: case_DVIF_DSS
Definitions: Repeat in one file using one DVIF with at least one field separators

DVIF: Use DVIF.
DSS: one DVIF with at least one field separators

D: one DVIF
SS: field separators. Commonly used separators include " | ", ", ", and so on.
Data Structure: a list
Original Structure Code expressed in regular expressions: case_DVIF(_DSS){1,}

• Examples: Q06_Monitoring
• Exercises: Q79_SumOvertime, Q87_Event

Basic Example: use one DVIF, repeated in a file

NOTE:
use one DVIF, repeated in a file
one DVIF drinks with three field separators " | "

---
Date: 2022-06-01
---

%%Column Names: "item_name", "unit_price", "caffeine_content", "item_no"%%
drinks:: Black Coffee | 120 | 300 | IT001
drinks:: Green Tea | 100 | 200 | IT002
    

Basic Example: use one DVIF, not repeated in a file

NOTE:
use one DVIF, not repeated in a file
one DVIF drinks with three field separators " | "

---
Date: 2022-06-06
---

%%Column Names: "item_name", "unit_price", "caffeine_content", "item_no"%%
drinks:: Apple Juice | 110 | 0 | IT003

    

Notes:

Summary

Q1: What is the data structure of the file dic_20220403?

Summary_Q1

Original Example: Q1 (To be explained)

NOTE:

1. Take the following file dic_20220403 as an example.
2. Each individual field Monitoring in the page is a string.
3. The field Monitoring, repeated in the page, is a list of strings.

---
Date: 2022-04-03
---

Monitoring:: FundQ | Do This0403
Monitoring:: FundQ | Do That0403
Monitoring:: FundP | Do Something Else0403

---

A1:

Another Example: A1_11

NOTE:
Before running FLATTEN Monitoring AS OneMonitoring, the field Monitoring, repeated in the page, is an array of strings as shown below.

• Here is a slice of the page hash, where page.file.name is dic_20220403.

```JSON
[
    {
        date: "2022-04-03T00:00:00.000Z",
        Monitoring: [
            "FundQ | Do This0403",
            "FundQ | Do That0403",
            "FundP | Do Something Else0403",
        ],
        file: {
            name: "dic_20220403",
            mtime: "2022-07-15T19:30:50.551Z",
        },
    },
]
```

---

Another Example: A1_12

NOTE:
After running FLATTEN Monitoring AS OneMonitoring, the Monitoring in the page is an array of strings as shown below.

• Here is a slice of the page hash, where page.file.name is dic_20220403.

```JSON
[
    {
        date: "2022-04-03T00:00:00.000Z",
        Monitoring: [
            "FundQ | Do This0403",
            "FundQ | Do That0403",
            "FundP | Do Something Else0403",
        ],
        OneMonitoring: "FundQ | Do This0403",
        file: {
            name: "dic_20220403",
            mtime: "2022-07-15T19:30:50.551Z",
        },
    },
    {
        date: "2022-04-03T00:00:00.000Z",
        Monitoring: [
            "FundQ | Do This0403",
            "FundQ | Do That0403",
            "FundP | Do Something Else0403",
        ],
        OneMonitoring: "FundQ | Do That0403",
        file: {
            name: "dic_20220403",
            mtime: "2022-07-15T19:30:50.551Z",
        },
    },
    {
        date: "2022-04-03T00:00:00.000Z",
        Monitoring: [
            "FundQ | Do This0403",
            "FundQ | Do That0403",
            "FundP | Do Something Else0403",
        ],
        OneMonitoring: "FundP | Do Something Else0403",
        file: {
            name: "dic_20220403",
            mtime: "2022-07-15T19:30:50.551Z",
        },
    },
]
```

---

Q2: What is the data structure of the file dic_20220503?

Summary_Q2

Original Example: Q2 (To be explained)

NOTE:

1. Take the following file dic_20220503 as an example.
2. The Monitoring in the page is a string.

```yaml
---
Date: 2022-05-03
---

Monitoring:: FundK | Do This0503

```

---

A2_21:

Another Example: A2_21

• Here is a slice of the page hash, where page.file.name is dic_20220503.

```JSON
[
    {
        date: "2022-05-03T00:00:00.000Z",
        Monitoring: "FundK | Do This0503",
        file: {
            name: "dic_20220503",
            mtime: "2022-07-15T14:28:31.993Z",
        },
    },
]
```

---

Test

Summary

• dataview: v0.5.55

---

Input

Summary

dictionary files

• Location: “100_Project/02_dataview/Q06_Monitoring/Q06_test_data”

---

folder: 03

• filename : dic_20220303

---
Date: 2022-03-03
---
Monitoring:: FundA | Do This0303
Monitoring:: FundA | Do That0303
Monitoring:: FundB | Do Something Else0303

---

• filename : dic_20220308

---
Date: 2022-03-08
---
Monitoring:: FundM | Do This0308
Monitoring:: FundM | Do That0308
Monitoring:: FundN | Do Something Else0308

---

folder: 04

• filename : dic_20220403

---
Date: 2022-04-03
---
Monitoring:: FundQ | Do This0403
Monitoring:: FundQ | Do That0403
Monitoring:: FundP | Do Something Else0403

---

• filename : dic_20220408

---
Date: 2022-04-08
---
Monitoring:: FundR | Do This0408
Monitoring:: FundR | Do That0408
Monitoring:: FundS | Do Something Else0408

---

folder: 05_string

• filename : dic_20220503

---
Date: 2022-05-03
---
Monitoring:: FundK | Do This0503

---

• filename : dic_20220508

---
Date: 2022-05-08
---
Monitoring:: FundJ | Do Something Else0508

---

folder: 09_null

• filename : dic_20220903

---
Date: 2022-09-03
---

Monitoring::

---

• filename : dic_20220908

---
Date: 2022-09-08
---

Monitoring:: 
Monitoring:: 

---

folder: 10_undefined

• filename : dic_20221003

---
Date: 2022-10-03
---

---

DQL01_split_up_a_list_into_each_individual_element_via_FLATTEN_and_TABLE

Summary

Main DQL

Code Name	Data type	Purposes	Remark
DQL01 _split_up_a_list _into_each_individual_element _via_FLATTEN _and_TABLE	Monitoring: 1.a string 2.a list of strings OneMonitoring: a string 1.“Monitoring:: FundQ | Do That0403”	1.To filter by Monitoring 2.To sort by file.name in ascending order 3.To split up a list Monitoring into each individual element OneMonitoring 4.To filter by OneMonitoring 5.To display the result as a table 5.1 To output the Fund1 from the OneMonitoring 5.2 To output the ActionItem1 from the OneMonitoring	Note: Require the files with the case_DVIF_DSS structure

Notes

Summary

Q1: How to get the s_page.Fund_DQL and s_page.ActionItem_DQL from the s_page.Monitoring via Inline DQL?

Summary_Q1

A1_11:

b_string_splited: Finished!

```md
aMonitoring=["FundA | Do This", "FundA | Do That"]
sMonitoring="FundA | Do This"

// /\s+\|\s+/ 
// ==>The spaces beside the "|" will be found and removed with "|" by `split`.
b_string_splited=`=split("FundA | Do This", "\s+\|\s+")`
//=>FundA, Do This
```

---

s_page.Fund_DQL: Finished!

```md
s_page.Fund=`=split("FundA | Do This", "\s+\|\s+")[0]`
//=>"FundA"

s_page.Fund_DQL=`split(Monitoring, "\s+\|\s+")[0]`
//=>【The DQL expression is Finished!】
```

---

s_page.ActionItem_DQL: Finished!

```md
s_page.ActionItem=`=split("FundA | Do This", "\s+\|\s+")[1]` 
//=>"Do This"  

s_page.ActionItem_DQL=`split(Monitoring, "\s+\|\s+")[1]`
//=>【The DQL expression is Finished!】
```

---

Q2: How to get the file.path of the page [[dic_20220303]] via Inline DQL?

Summary_Q2

A2_21:

```md
dic_20220303.file.path=`=[[dic_20220303]].file.path`
//=>100_Project/02_dataview/Q06_Monitoring/Q06_test_data/03/dic_20220303.md
```

---

Code DQL01_split_up_a_list_into_each_individual_element_via_FLATTEN_and_TABLE

Summary_code

title: DQL01_split_up_a_list_into_each_individual_element_via_FLATTEN_and_TABLE =>0.Require the files with the `case_DVIF_DSS` structure 1.To filter by `Monitoring` 2.To sort by `file.name` in ascending order 3.To split up a list `Monitoring` into each individual element `OneMonitoring` 4.To filter by `OneMonitoring` 5.To display the result as a table 5.1 To output the `Fund1` from the `OneMonitoring` 5.2 To output the `ActionItem1` from the `OneMonitoring`
collapse: close
icon: 
color: 
```dataview
TABLE WITHOUT ID 
      file.link AS "File",
      Monitoring AS "Original Monitoring",
      OneMonitoring AS "One Monitoring",
      split(OneMonitoring, "\s+\|\s+")[0] AS "Fund1", 
	    split(OneMonitoring, "\s+\|\s+")[1] AS "ActionItem1"      
FROM "100_Project/02_dataview/Q06_Monitoring/Q06_test_data"
WHERE Monitoring != null          
SORT file.name ASC


FLATTEN Monitoring AS OneMonitoring


WHERE OneMonitoring != null 

```

---

Screenshots(DQL01)

Part 1/2:

Part 2/2:

---

DVJS01_example_filter_sort_AoH_and_TABLE

Summary

Main DVJS

Code Name	Data type	Purposes	Remark
DVJS01 _example _filter _sort_AoH _and_TABLE	aoh_drinks: an Array of Hashes	1.To filter by h_drink.item_name 2.To filter by h_drink.unit_price 3.To filter by h_drink["caffeine content"] 4.To sort by h_drink.item_name 5.To display the result as a table	NOTE: 1.The prefix “AoH” of the variable aoh_drinks means an Array of Hashes. 2.The Hashes means JavaScript Objects in the topic.

Code DVJS01_example_filter_sort_AoH_and_TABLE

Summary_code

title: DVJS01_example_filter_sort_AoH_and_TABLE=>1.To filter by `h_drink.item_name` 2.To filter by `h_drink.unit_price` 3.To filter by `h_drink["caffeine content"]` 4.To sort by `h_drink.item_name` 5.To display the result as a table
collapse: close
icon: 
color: 
```dataviewjs
// D21.define : aoh_drinks
// AoH = an Array of Hashes = an Array of JavaScript Objects
// #####################################################################
let aoh_drinks = [
    { item_name: "Black Coffee", unit_price: 120, "caffeine content": 300, item_no: "IT001" },
    { item_name: "Green Tea", unit_price: 100, "caffeine content": 200, item_no: "IT002" },
    { item_name: "Apple Juice", unit_price: 110, "caffeine content": 0, item_no: "IT003" },
    { item_name: "Iced Chocolate", unit_price: 130, "caffeine content": 0, item_no: "IT004" },
    { item_name: "Hot Chocolate", unit_price: 105, "caffeine content": 0, item_no: "IT005" },
];


// D23. transform aoh_drinks :
// transform JavaScript arrays to Dataview Data Arrays in order to sort it
// #####################################################################
aoh_drinks = dv.array(aoh_drinks);


// D31. filter + sort aoh_drinks:
// #####################################################################
aoh_drinks = aoh_drinks
    .filter(
        (h_drink) =>
            dv.func.contains(h_drink.item_name, "Coffee") ||
            dv.func.contains(h_drink.item_name, "Tea") ||
            dv.func.contains(h_drink.item_name, "Juice") ||
            dv.func.contains(h_drink.item_name, "Chocolate")
    )
    .filter((h_drink) => h_drink.unit_price > 90 && h_drink.unit_price < 125)
    .filter((h_drink) => h_drink["caffeine content"] >= 0)
    .sort((h_drink) => h_drink.item_name, "asc");
    

// D51. render a tables : aoh_drinks
// #####################################################################
dv.header(5, "D51. Render a table: `aoh_drinks`");
dv.table(
    ["N", "Item Name", "Unit Price", "Caffeine Content", "Item No"],
    aoh_drinks.map((dictionary, index) => [
        index + 1,
        dictionary.item_name,
        dictionary.unit_price,
        dictionary["caffeine content"],
        dictionary.item_no,       
    ])
);

```

---

Screenshots(DVJS01)

---

DVJS03_split_up_a_list_into_each_individual_element_and_filter_and_TABLE

NOTE:

1. The DVJS03 performs the same operations as the DQL10.
2. The DVJS03 is mainly used for the files with the case_DVIF_DDD structure.

Summary

Main DVJS

Code Name	Data type	Purposes	Remark
DVJS03 _split_up_a_list _into_each_individual_element _and_filter _and_TABLE	Monitoring: 1.a string 2.a list of strings OneMonitoring: a string 1.“Monitoring:: FundQ | Do That0403”	The DVJS03 performs the same operations as the DQL10.	Note: Require the files with the case_DVIF_DDD(or case_DVIF_DSS) structure

Code DVJS03_split_up_a_list_into_each_individual_element_and_filter_and_TABLE

Summary_Code

title: DVJS03_split_up_a_list_into_each_individual_element_and_filter_and_TABLE =>0.Require the files with the `case_DVIF_DDD`(or `case_DVIF_DSS`) structure 1.The DVJS03 performs the same operations as the DQL10.
collapse: close
icon: 
color: 
```dataviewjs
// M11. define pages: get pages from Sources (M11, M15)
// #####################################################################
let pages = dv
    .pages('"100_Project/02_dataview/Q06_Monitoring/Q06_test_data"')
    .where((page) => page.Monitoring !== null && page.Monitoring !== undefined);
    

// M23. split up a list `Monitoring` into each individual element `OneMonitoring`
// update pages: add a new field `Fund` into each page
// update pages: add a new field `ActionItem` into each page
// 
// define a JavaScript array
// #####################################################################
let dictionaries = [];

for (let page of pages) {
    // M23.IF01: Classify '[object Object]' into '[object Array]' and '[object notArray]'
    // #####################################################################
    let sObjectType = "";
    if (dv.isArray(page.Monitoring)) {
        sObjectType = "[object Array]";
    } else {
        sObjectType = "[object notArray]";
    }

    // M23.IF02: define page.Monitoring a JavaScript array + Redefine sObjectType
    // #####################################################################
    if (sObjectType === "[object notArray]") {
        page.Monitoring = [page.Monitoring];
        sObjectType = "[object Array]";
    }


    // M23.EL03: transform the data when page.Monitoring is a JavaScript array
    // #####################################################################
    for (let i = 0; i < page.Monitoring.length; i++) {
        let OneMonitoring = page.Monitoring[i];

        // When OneMonitoring is not defined
        // Use Case: dic_20221003
        // #####################################################################
        let aSplitOneMonitoring = ["", ""];
        
        if (OneMonitoring) {
            aSplitOneMonitoring = OneMonitoring.split(/\s+\|\s+/);
        }
        
        dictionaries.push({
            file: page.file,
            date: page.date,
            OneMonitoring: OneMonitoring,
            Fund: aSplitOneMonitoring[0],
            ActionItem: aSplitOneMonitoring[1],
        });
    }

}


// M24. transform dictionaries: 
// transform JavaScript arrays to Dataview Data arrays in order to sort it
// #####################################################################
dictionaries = dv.array(dictionaries);


// M25. sort by dictionary.Fund in ascending order: M99.(at the bottom) 
// M31. filter by dictionary.Fund
// M33. filter by dictionary.ActionItem
// #####################################################################
dictionaries = dictionaries
    .sort((dictionary) => dictionary.Fund, "asc")
    .filter((dictionary) => dv.func.contains(dictionary.Fund, "FundQ"))
    .filter((dictionary) => dv.func.contains(dictionary.ActionItem, "That"));


// M41. render a table: dictionaries
// #####################################################################
dv.header(5, "M41. Render a table: `dictionaries`");
dv.table(
    ["N", "File", "Monitoring", "Fund", "Action Item"],
    dictionaries.map((dictionary, index) => [
        index + 1,
        dictionary.file.link,
        dictionary.OneMonitoring,
        dictionary.Fund,
        dictionary.ActionItem,
    ])
);

```

---

Screenshots(DVJS03)

---

Explanation: the DVJS03

Summary

Overview

Main variables

• The following table presents the main variables in the DVJS03.
• a Hash = an JavaScript Object

Variables	Data type	Lifetime	Declared by	Remark
pages	Array	When the code is completed	let	AoH = an Array of Hashes
page	Hash	In the {} curly brackets
dictionaries	Array	When the code is completed	let	AoH = an Array of Hashes
dictionary	Hash	In the {} curly brackets

The data structure of the pages

• The pages array consists of each page hash.
• The page is pages[i], where i=0, …, pages.length-1.

The data structure of the page

• Take the dic_20220303 file for example.
• filename : dic_20220303

---
Date: 2022-03-03
---

Monitoring:: FundA | Do This0303
Monitoring:: FundA | Do That0303
Monitoring:: FundB | Do Something Else0303

---

• The plain page hash from a file is created by the dv.pages() function and consists of three hashes : the page.file hash, the YAML fields and the Dataview inline fields.
• Here is a slice of the page hash, where page.file.name is dic_20120919.
• At Step M23, the following hash is transformed into two hashes, which are stored in the dictionaries array.

```JSON
{
  file: {
    name: 'dic_20220303',
    ctime: '2022-03-03T19:30:50.586+08:00',
  },
  date: '2022-03-03T00:00:00.000+08:00',
  Monitoring: ['FundA | Do This0303', 'FundA | Do That0303', 'FundB | Do Something Else0303'],
}
```

---

Step M11: Sources

• 【M11】: Suppose that there are many files located in the path 100_Project/02_dataview/Q06_Monitoring/Q06_test_data .

---

• 【M15】: Suppose that the file where page.Monitoring does not strictly equal null and undefined is to be taken into consideration.

---

• Here is the code.

```dataviewjs
// M11. define pages: get pages from Sources (M11, M15)
// #####################################################################
let pages = dv
    .pages('"100_Project/02_dataview/Q06_Monitoring/Q06_test_data"')
    .where((page) => page.Monitoring !== null && page.Monitoring !== undefined);
```

Step M23: Split up

• 【M23】: Split up multiple group Dataview inline fields in the file into individual groups. (pages, page ==> dictionaries, dictionary)
• Now let’s transform from thing per date (we have single page for each date) into thing per dictionary (we want to have as many rows in a table as all dictionaries extracted from all pages).
• The dictionary is a new row(hash) which consists of five fields sush as page.file,page.date,page.Monitoring, page.Fund,and page.ActionItem.
• The dictionaries is a new table(array), which consists of each dictionary row(hash).

Take the dic_20220303 for example：The Monitoring is an array

• file name : dic_20220303

---
Date: 2022-03-03
---

Monitoring:: FundA | Do This0303
Monitoring:: FundA | Do That0303
Monitoring:: FundB | Do Something Else0303

---

• There is ==more== than one Monitoring in the original page file.

the original data structure

• The plain page hash from a file is created by the dv.pages() function and consists of three hashes : the page.file hash, the YAML fields and the Dataview inline fields.

• At Step M23, the following hash is transformed into three hashes, which are stored in the dictionaries array.

• Here is a slice of the page hash from the dic_20220303 file.

```JSON
{
  file: {
    name: 'dic_20220303',
    ctime: '2022-03-03T19:30:50.586+08:00',
  },
  date: '2022-03-03T00:00:00.000+08:00',
  Monitoring: ['FundA | Do This0303', 'FundA | Do That0303', 'FundB | Do Something Else0303'],
}
```

---

• The page hash is transformed into three new hashes as follows.

the new data structure

• The dictionaries array consists of each dictionary hash.
• The plain dictionary hash is created from the pages at Step M23 and consists of three hashes : the page.file hash, the YAML fields and the Dataview inline fields.
• At Step M23, the following hashes are created from the above page hash.
• Here’s one dictionary hash, which the dictionaries array consists of.

```JSON
{
  file: {
    name: 'dic_20220303',
    ctime: '2022-03-03T19:30:50.586+08:00',
  },
  date: '2022-03-03T00:00:00.000+08:00',
  Monitoring: 'FundA | Do This0303',
  Fund: 'FundA'
  ActionItem: 'Do This0303' 
}
```

---

• Here’s another dictionary hash, which the dictionaries array consists of.

```JSON
{
  file: {
    name: 'dic_20220303',
    ctime: '2022-03-03T19:30:50.586+08:00',
  },
  date: '2022-03-03T00:00:00.000+08:00',
  Monitoring: 'FundA | Do That0303',
  Fund: 'FundA'
  ActionItem: 'Do That0303'
}
```

---

• Here’s the other dictionary hash, which the dictionaries array consists of.

```JSON
{
  file: {
    name: 'dic_20220303',
    ctime: '2022-03-03T19:30:50.586+08:00',
  },
  date: '2022-03-03T00:00:00.000+08:00',
  Monitoring: 'FundB | Do Something Else0303',
  Fund: 'FundB'
  ActionItem: 'Do Something Else0303'
}
```

---

Step M24: transform JavaScript arrays to Dataview Data arrays

```dataviewjs
// M24. transform dictionaries: 
// transform JavaScript arrays to Dataview Data arrays in order to sort it
// #####################################################################
dictionaries = dv.array(dictionaries);
```

Step M25: sort by dictionary.Fund

• 【M25】: Sort the dictionaries array by the dictionary.Fund in ascending order.

Step M31: filter by dictionary.Fund

• 【M31】: Suppose that the row where dictionary.Fund includes “FundQ” is to be taken into consideration.
• 【M33】: Suppose that the row where dictionary.ActionItem includes “That” is to be taken into consideration.
• Here is the code.

```dataviewjs
// M25. sort by dictionary.Fund in ascending order: M99.(at the bottom) 
// M31. filter by dictionary.Fund
// M33. filter by dictionary.ActionItem
// #####################################################################
dictionaries = dictionaries
    .sort((dictionary) => dictionary.Fund, "asc")
    .filter((dictionary) => dv.func.contains(dictionary.Fund, "FundQ"))
    .filter((dictionary) => dv.func.contains(dictionary.ActionItem, "That"));
```

Step M41: TABLE

• 【M41】: Display each of the list as a table.

```javascript
[
    index + 1,
    dictionary.file.link,
    dictionary.Monitoring,
    dictionary.Fund,
    dictionary.ActionItem,
]
```

---

• Here is the code.

```dataviewjs
// M41. render a table: dictionaries
// #####################################################################
dv.header(5, "M41. Print a table of the `dictionaries`");
dv.table(
    ["N", "File", "Monitoring", "Fund", "Action Item"],
    dictionaries.map((dictionary, index) => [
        index + 1,
        dictionary.file.link,
        dictionary.Monitoring,
        dictionary.Fund,
        dictionary.ActionItem,
    ])
);
```

Example: Get each name from an AoH

```md
a_Drinks=`$=
[
    { item_name: "Black Coffee", unit_price: 120, "caffeine content": 300, item_no: "IT001" },
    { item_name: "Green Tea", unit_price: 100, "caffeine content": 200, item_no: "IT002" },
    { item_name: "Apple Juice", unit_price: 110, "caffeine content": 0, item_no: "IT003" },
    { item_name: "Iced Chocolate", unit_price: 130, "caffeine content": 0, item_no: "IT004" },
    { item_name: "Hot Chocolate", unit_price: 105, "caffeine content": 0, item_no: "IT005" },
]
.map((e) => e["item_name"])
`
//=>Black Coffee, Green Tea, Apple Juice, Iced Chocolate, Hot Chocolate
```

---

Conclusion

Summary

• Only by knowing how to use the FLATTEN operator can many complex problems be simplified.
• It is recommended to try to read the entire documentation, not just the DQL10 query.

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Reference

Summary

DVIF Structures

Q06_Monitoring: case_DVIF_DSS

• Q06_Monitoring: Part01: Solutions
• Q06_Monitoring: Part02_DQL10+DVJS10:Solutions

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Q79_SumOvertime: case_DVIF_DSS

• Q79_SumOvertime: Solutions

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Q87_Event: case_DVIF_DSS

• Q87_Event: Solutions

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Q05_Schedule: case_DVIF_DSS

• How to split up multiple group Dataview inline fields in the file into individual groups?
  • Using the DQL FLATTEN: mikael: Manage date/milestones using dataview on 2022-06-29
  • Structures:

```md
---
Date: 2020-05-01
---

Schedule:: Release of Z6 book 2020-05-14

```

OR

```md
---
Date: 2020-03-01
---

Schedule:: Release of J1 book 2020-06-15
Schedule:: Release of K1 book 2020-03-08

```

---

Q01_TermDefinition: case_DVIF_DDD

• How to split up multiple group Dataview inline fields in the file into individual groups?
  • Using the DVJS code based on the DVJS03: Luis_Aldama92: DataviewJS Snippet Showcase 162 on 2022-04-25 , Luis_Aldama92: DataviewJS Snippet Showcase 155 on 2022-04-16
  • Structures:

```md
---
date: 2012-09-22
---
term:: "Name of Term W1"
definition:: "Definition of Term W1"

```

OR

```md
---
date: 2012-09-19
---
term:: "Name of Term A1"
definition:: "Definition of Term A1"

term:: "Name of Term Z1"
definition:: "Definition of Term Z1"

```

---

Q02_Meals: case_DVIF_DDD

• How to split up multiple group Dataview inline fields in the file into individual groups?
  • Using the DVJS code based on the DVJS03 : lexane: DataviewJS Snippet Showcase 115 on 2022-07-21
  • Structures:

```md
---
date: 2018-04-01
---

typerepas:: "meal type J"
heurerepas:: "hour meal J"
faimavantrepas:: "before hunger J"
repas:: "meal J"
faimapresrepas:: "after hunger J"

```

OR

```md
---
date: 2018-03-01
---

typerepas:: "meal type M"
heurerepas:: "hour meal M"
faimavantrepas:: "before hunger M"
repas:: "meal M"
faimapresrepas:: "after hunger M"

typerepas:: "meal type E"
heurerepas:: "hour meal E"
faimavantrepas:: "before hunger E"
repas:: "meal E"
faimapresrepas:: "after hunger E"

```

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case_DVIF_DDD

• How to split up multiple group Dataview inline fields in the file into individual groups?
  • Using the DVJS code based on the DVJS03 :BobWCB: How to generate multiple rows for records within one file? #1090 on 2022-05-15
  • Structures:

```md
---
date: 2022-03-01
---
%%record_1%%
field1:: value01
field2:: value02
field3:: value03

%%record_2%%
field1:: value10
field2:: value20
field3:: value30

```

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YAML Structures

Q17_Purchases: case_YAML_Y-YYY

• Q17_Purchases: Solutions

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Q27_ProjectPerson: case_YAML_Y_AoH

• Q27_ProjectPerson: Solutions

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FLST Structures

Q92_FileLists

• Q92_FileLists: Solutions
• Q92_FileLists: Input only

Q: How to use the file.lists data to design a Markdown file as a table in the database, where each record consists of multiple columns?

Answers

• There are at least four methods to do that by using the file.lists data.

Code Name	Data type	Structures	Headings(list items)	Headings(task items)	Remark
DQL61	file.lists	case_FLST_HLDDD	what happened today	what happened today
DQL63	file.lists	case_FLST_HLDDD	what happened today	what happened today
DQL65	file.lists	case_FLST_HLDDD	what happened today	what happened today
DQL30	file.lists	case_FLST_HLDSS	other events	other tasks
DQL20	file.lists	case_FLST_HLSSS	some events	some tasks
DQL10	file.lists	case_FLST_HLSS	milestones	main tasks

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Q18_QAA: case_FLST_LD-DDD

• Q18_QAA: Solutions_S1

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Related resources

Summary

Q79_Push

• Q79_Push: Solutions

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