Compare commits
6 Commits
22120fcff5
...
fff6ae4ec8
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
fff6ae4ec8 | ||
|
|
4c5148c7e0 | ||
|
|
f1c1f7bdf3 | ||
|
|
9a9d51fc72 | ||
|
|
7a6703648d | ||
|
|
053a7a4614 |
@@ -37,20 +37,20 @@ Press `Create` button in the top toolbar or use `Ctrl+b` (`Cmd+b` for MacOS)
|
||||
keyboard shortcut to open a new tab for an inquiry. An inquiry consists of three
|
||||
parts: SQL query, result set (result of the query execution) and visualisation
|
||||
of the result set. A tab consists of two panels. Each of them can show one of
|
||||
the three parts of inquiry. By default the top panel shows SQL query editor and
|
||||
the three parts of inquiry. By default, the top panel shows SQL query editor and
|
||||
the bottom panel shows the result set. You can switch any panel to any other
|
||||
view with corresponding buttons in the right side toolbar.
|
||||
view with the corresponding buttons in the right side toolbar.
|
||||
|
||||
*  – Switch the panel to an SQL query editor. In that
|
||||
editor you can specify and run not only a `SELECT` statement for getting data
|
||||
editor, you can specify and run not only a `SELECT` statement for getting data
|
||||
but also DDL/DML statements for modifying the database.
|
||||
*  – Switch the panel to the result set. Here you
|
||||
can see the result of the query execution.
|
||||
*  – Switch the panel to visualisation. This
|
||||
panel allows building a pivot table and charts from the result set.
|
||||
panel allows building a pivot table, a graph or charts from the result set.
|
||||
|
||||
> **Note:** The query editor can show you hints: SQL keywords, table and column
|
||||
> names. In a common case column names are shown in the hint if you specify the
|
||||
> names. In a common case, column names are shown in the hint if you specify the
|
||||
> table name, e.g. `SELECT table_name.`. But if there is only one table in your
|
||||
> database column names will be always available in the hint. Press `Ctrl+Space`
|
||||
> to show a hint explicitly.
|
||||
@@ -59,7 +59,7 @@ view with corresponding buttons in the right side toolbar.
|
||||
|
||||
Press  button in the right side toolbar of an SQL
|
||||
editor panel or use `Ctrl+r` or `Ctrl+Enter` (`Cmd+r` or `Cmd+Enter` for MacOS)
|
||||
keyboard shortcut to execute a query in the current opened tab.
|
||||
keyboard shortcut to execute a query in the current open tab.
|
||||
|
||||
> **Note:** Running is not available if a query for the current tab is not
|
||||
> specified.
|
||||
@@ -74,14 +74,15 @@ visualisation panel.
|
||||
|
||||
*  – Switch to a chart type visualisation.
|
||||
*  – Switch to a pivot type visualisation.
|
||||
|
||||
> **Note:** All unsaved changes in the current visualisation will be lost when
|
||||
> you switch to the other visualisation type.
|
||||
*  – Switch to a graph type visualisation.
|
||||
|
||||
A pivot table can be represented as a regular or multi-header table or
|
||||
visualised with a chart.
|
||||
Read more details of working with pivot in [Pivot tables][2].
|
||||
|
||||
There are some requirements for the result set to build a graph.
|
||||
Read more in [Graph][3].
|
||||
|
||||
All customised charts in sqliteviz are created with a `react-chart-editor`
|
||||
component (fig. 5). The same component with some additional features is used in
|
||||
Plotly Chart Studio. Explore its [documentation][1] to learn how to build charts
|
||||
@@ -104,3 +105,4 @@ After that, the inquiry will be in the list on `Inquiries` page.
|
||||
|
||||
[1]: https://plotly.com/chart-studio-help/tutorials/#basic
|
||||
[2]: ../Pivot-table
|
||||
[3]: ../Graph
|
||||
|
||||
54
Graph.md
Normal file
@@ -0,0 +1,54 @@
|
||||
# Graph
|
||||
|
||||
## Pivot table UI
|
||||
|
||||
Sqliteviz allows building pivot tables and visualizing them. To build a graph
|
||||
run a query to get data. Then open visualisation panel by clicking 
|
||||
in any of the two side toolbars and choose a pivot mode by clicking .
|
||||
|
||||
A pivot visualisation has the following settings:
|
||||
|
||||
- Columns – choose one or more column names from the result set. The values in
|
||||
the chosen columns will be column names of the pivot table.
|
||||
- Rows – choose one or more column names from the result set. The values in the
|
||||
chosen columns will be row names of the pivot table.
|
||||
- Order of columns and rows.
|
||||
- Aggregator and its arguments – a function which will be used for pivot cell
|
||||
calculation. An aggregator can have from zero to two arguments. An aggregator
|
||||
argument is one of the columns of the result set.
|
||||
- View – pivot table visualisation. It can be a table, a heatmap, a chart,
|
||||
etc. See some examples of different views of the same pivot table below.
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
There are several built-in chart views for a pivot. But you can build your own
|
||||
with `Custom chart` view (fig. 4).
|
||||
|
||||

|
||||
|
||||
> **Note:** You can switch to other pivot views and back to `Custom chart` –
|
||||
> all your custom chart settings will be remembered. But if you switch the
|
||||
> visualisation mode from pivot to any other mode, unsaved changes will be lost.
|
||||
|
||||
You can save any visualisation as an image by clicking .
|
||||
|
||||
## Pivot table SQL
|
||||
|
||||
Pivot table (in the form of a result set) can be built on the SQL-level and,
|
||||
technically speaking, can be visualised as any other result set. Practically
|
||||
though there are a couple of challenges with that:
|
||||
|
||||
1. Visualising a dataset of long/tall shape is much more convenient in Plotly
|
||||
(chart editor) rather than one of wide/fat shape.
|
||||
2. SQLite doesn't have a special constructs like `PIVOT` or `CROSSTAB` in
|
||||
its SQL dialect.
|
||||
|
||||
[How to build a pivot table in SQL(ite)][1] explores two options with static
|
||||
(or beforehand-known) and dynamic columns.
|
||||
|
||||
[1]: ../How-to-build-a-pivot-table-in-SQ-Lite
|
||||
|
||||
10
Home.md
@@ -6,10 +6,11 @@ Welcome to the sqliteviz wiki!
|
||||
3. [Multiple file import][9]
|
||||
4. [Manage inquiries][2]
|
||||
5. [Export current database][4]
|
||||
6. [Pivot table][3]
|
||||
7. [Predefined inquiries][5]
|
||||
8. [Sharing][11]
|
||||
9. [Diagnostic information][6]
|
||||
6. [Graph][13]
|
||||
7. [Pivot table][3]
|
||||
8. [Predefined inquiries][5]
|
||||
9. [Sharing][11]
|
||||
10. [Diagnostic information][6]
|
||||
|
||||
## Examples and tutorials
|
||||
1. [How to rename tables and columns after CSV import][8]
|
||||
@@ -32,3 +33,4 @@ Welcome to the sqliteviz wiki!
|
||||
[10]: How-to-build-a-pivot-table-in-SQLite
|
||||
[11]: Sharing
|
||||
[12]: How-to-rename-tables-and-columns-after-csv-import
|
||||
[13]: Graph
|
||||
|
||||
|
Before Width: | Height: | Size: 64 KiB After Width: | Height: | Size: 94 KiB |
|
Before Width: | Height: | Size: 52 KiB After Width: | Height: | Size: 66 KiB |
|
Before Width: | Height: | Size: 59 KiB After Width: | Height: | Size: 76 KiB |
8
img/graph.svg
Normal file
@@ -0,0 +1,8 @@
|
||||
<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path d="M5 4C5 5.10457 4.10457 6 3 6C1.89543 6 1 5.10457 1 4C1 2.89543 1.89543 2 3 2C4.10457 2 5 2.89543 5 4Z" fill="#A2B1C6"/>
|
||||
<path d="M17 7.5C17 8.88071 15.8807 10 14.5 10C13.1193 10 12 8.88071 12 7.5C12 6.11929 13.1193 5 14.5 5C15.8807 5 17 6.11929 17 7.5Z" fill="#A2B1C6"/>
|
||||
<path d="M8 13.5C8 14.8807 6.88071 16 5.5 16C4.11929 16 3 14.8807 3 13.5C3 12.1193 4.11929 11 5.5 11C6.88071 11 8 12.1193 8 13.5Z" fill="#A2B1C6"/>
|
||||
<path d="M2.93128 5.31436L3.90527 5.08778L5.48693 11.8867L4.51294 12.1133L2.93128 5.31436Z" fill="#A2B1C6"/>
|
||||
<path d="M12.9447 7.79159L13.5548 8.58392L7.30516 13.3962L6.69507 12.6038L12.9447 7.79159Z" fill="#A2B1C6"/>
|
||||
<path d="M14.1316 6.51712L3.13166 3.51723L2.86844 4.48202L13.8684 7.48191L14.1316 6.51712Z" fill="#A2B1C6"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 858 B |
3
index.md
@@ -4,10 +4,11 @@ Sqliteviz is a single-page offline-first PWA for fully client-side visualisation
|
||||
|
||||
With sqliteviz you can:
|
||||
|
||||
- run SQL queries against a SQLite database and create Plotly charts and pivot tables based on the result sets
|
||||
- run SQL queries against a SQLite database and create Plotly charts, graphs and pivot tables based on the result sets
|
||||
- import a CSV, JSON or NDJSON file into a SQLite database and visualize imported data
|
||||
- export result set to CSV file
|
||||
- manage inquiries and run them against different databases
|
||||
- import/export inquiries from/to a JSON file
|
||||
- export a modified SQLite database
|
||||
- use it offline from your OS application menu like any other desktop app
|
||||
|
||||
|
||||
@@ -8,6 +8,7 @@
|
||||
"/docs/multiple-csv-file-import/",
|
||||
"/docs/manage-inquiries/",
|
||||
"/docs/export-current-database/",
|
||||
"/docs/graph/",
|
||||
"/docs/pivot-table/",
|
||||
"/docs/predefined-inquiries/",
|
||||
"/docs/sharing/",
|
||||
@@ -29,4 +30,4 @@
|
||||
]
|
||||
}
|
||||
]
|
||||
}]
|
||||
}]
|
||||
|
||||