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@@ -37,20 +37,20 @@ Press `Create` button in the top toolbar or use `Ctrl+b` (`Cmd+b` for MacOS)
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keyboard shortcut to open a new tab for an inquiry. An inquiry consists of three
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keyboard shortcut to open a new tab for an inquiry. An inquiry consists of three
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parts: SQL query, result set (result of the query execution) and visualisation
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parts: SQL query, result set (result of the query execution) and visualisation
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of the result set. A tab consists of two panels. Each of them can show one of
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of the result set. A tab consists of two panels. Each of them can show one of
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the three parts of inquiry. By default the top panel shows SQL query editor and
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the three parts of inquiry. By default, the top panel shows SQL query editor and
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the bottom panel shows the result set. You can switch any panel to any other
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the bottom panel shows the result set. You can switch any panel to any other
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view with corresponding buttons in the right side toolbar.
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view with the corresponding buttons in the right side toolbar.
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*  – Switch the panel to an SQL query editor. In that
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*  – Switch the panel to an SQL query editor. In that
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editor you can specify and run not only a `SELECT` statement for getting data
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editor, you can specify and run not only a `SELECT` statement for getting data
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but also DDL/DML statements for modifying the database.
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but also DDL/DML statements for modifying the database.
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*  – Switch the panel to the result set. Here you
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*  – Switch the panel to the result set. Here you
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can see the result of the query execution.
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can see the result of the query execution.
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*  – Switch the panel to visualisation. This
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*  – Switch the panel to visualisation. This
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panel allows building a pivot table and charts from the result set.
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panel allows building a pivot table, a graph or charts from the result set.
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> **Note:** The query editor can show you hints: SQL keywords, table and column
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> **Note:** The query editor can show you hints: SQL keywords, table and column
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> names. In a common case column names are shown in the hint if you specify the
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> names. In a common case, column names are shown in the hint if you specify the
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> table name, e.g. `SELECT table_name.`. But if there is only one table in your
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> table name, e.g. `SELECT table_name.`. But if there is only one table in your
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> database column names will be always available in the hint. Press `Ctrl+Space`
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> database column names will be always available in the hint. Press `Ctrl+Space`
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> to show a hint explicitly.
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> to show a hint explicitly.
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@@ -59,7 +59,7 @@ view with corresponding buttons in the right side toolbar.
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Press  button in the right side toolbar of an SQL
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Press  button in the right side toolbar of an SQL
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editor panel or use `Ctrl+r` or `Ctrl+Enter` (`Cmd+r` or `Cmd+Enter` for MacOS)
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editor panel or use `Ctrl+r` or `Ctrl+Enter` (`Cmd+r` or `Cmd+Enter` for MacOS)
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keyboard shortcut to execute a query in the current opened tab.
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keyboard shortcut to execute a query in the current open tab.
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> **Note:** Running is not available if a query for the current tab is not
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> **Note:** Running is not available if a query for the current tab is not
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> specified.
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> specified.
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@@ -74,14 +74,15 @@ visualisation panel.
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*  – Switch to a chart type visualisation.
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*  – Switch to a chart type visualisation.
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*  – Switch to a pivot type visualisation.
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*  – Switch to a pivot type visualisation.
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*  – Switch to a graph type visualisation.
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> **Note:** All unsaved changes in the current visualisation will be lost when
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> you switch to the other visualisation type.
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A pivot table can be represented as a regular or multi-header table or
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A pivot table can be represented as a regular or multi-header table or
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visualised with a chart.
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visualised with a chart.
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Read more details of working with pivot in [Pivot tables][2].
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Read more details of working with pivot in [Pivot tables][2].
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There are some requirements for the result set to build a graph.
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Read more in [Graph][3].
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All customised charts in sqliteviz are created with a `react-chart-editor`
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All customised charts in sqliteviz are created with a `react-chart-editor`
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component (fig. 5). The same component with some additional features is used in
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component (fig. 5). The same component with some additional features is used in
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Plotly Chart Studio. Explore its [documentation][1] to learn how to build charts
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Plotly Chart Studio. Explore its [documentation][1] to learn how to build charts
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@@ -104,3 +105,4 @@ After that, the inquiry will be in the list on `Inquiries` page.
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[1]: https://plotly.com/chart-studio-help/tutorials/#basic
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[1]: https://plotly.com/chart-studio-help/tutorials/#basic
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[2]: ../Pivot-table
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[2]: ../Pivot-table
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[3]: ../Graph
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54
Graph.md
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# Graph
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## Pivot table UI
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Sqliteviz allows building pivot tables and visualizing them. To build a graph
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run a query to get data. Then open visualisation panel by clicking 
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in any of the two side toolbars and choose a pivot mode by clicking .
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A pivot visualisation has the following settings:
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- Columns – choose one or more column names from the result set. The values in
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the chosen columns will be column names of the pivot table.
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- Rows – choose one or more column names from the result set. The values in the
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chosen columns will be row names of the pivot table.
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- Order of columns and rows.
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- Aggregator and its arguments – a function which will be used for pivot cell
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calculation. An aggregator can have from zero to two arguments. An aggregator
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argument is one of the columns of the result set.
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- View – pivot table visualisation. It can be a table, a heatmap, a chart,
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etc. See some examples of different views of the same pivot table below.
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There are several built-in chart views for a pivot. But you can build your own
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with `Custom chart` view (fig. 4).
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> **Note:** You can switch to other pivot views and back to `Custom chart` –
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> all your custom chart settings will be remembered. But if you switch the
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> visualisation mode from pivot to any other mode, unsaved changes will be lost.
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You can save any visualisation as an image by clicking .
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## Pivot table SQL
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Pivot table (in the form of a result set) can be built on the SQL-level and,
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technically speaking, can be visualised as any other result set. Practically
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though there are a couple of challenges with that:
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1. Visualising a dataset of long/tall shape is much more convenient in Plotly
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(chart editor) rather than one of wide/fat shape.
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2. SQLite doesn't have a special constructs like `PIVOT` or `CROSSTAB` in
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its SQL dialect.
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[How to build a pivot table in SQL(ite)][1] explores two options with static
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(or beforehand-known) and dynamic columns.
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[1]: ../How-to-build-a-pivot-table-in-SQ-Lite
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10
Home.md
@@ -6,10 +6,11 @@ Welcome to the sqliteviz wiki!
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3. [Multiple file import][9]
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3. [Multiple file import][9]
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4. [Manage inquiries][2]
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4. [Manage inquiries][2]
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5. [Export current database][4]
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5. [Export current database][4]
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6. [Pivot table][3]
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6. [Graph][13]
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7. [Predefined inquiries][5]
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7. [Pivot table][3]
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8. [Sharing][11]
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8. [Predefined inquiries][5]
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9. [Diagnostic information][6]
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9. [Sharing][11]
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10. [Diagnostic information][6]
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## Examples and tutorials
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## Examples and tutorials
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1. [How to rename tables and columns after CSV import][8]
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1. [How to rename tables and columns after CSV import][8]
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@@ -32,3 +33,4 @@ Welcome to the sqliteviz wiki!
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[10]: How-to-build-a-pivot-table-in-SQLite
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[10]: How-to-build-a-pivot-table-in-SQLite
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[11]: Sharing
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[11]: Sharing
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[12]: How-to-rename-tables-and-columns-after-csv-import
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[12]: How-to-rename-tables-and-columns-after-csv-import
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[13]: Graph
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Before Width: | Height: | Size: 64 KiB After Width: | Height: | Size: 94 KiB |
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Before Width: | Height: | Size: 52 KiB After Width: | Height: | Size: 66 KiB |
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Before Width: | Height: | Size: 59 KiB After Width: | Height: | Size: 76 KiB |
8
img/graph.svg
Normal file
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<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
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<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"/>
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<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"/>
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<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"/>
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<path d="M2.93128 5.31436L3.90527 5.08778L5.48693 11.8867L4.51294 12.1133L2.93128 5.31436Z" fill="#A2B1C6"/>
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<path d="M12.9447 7.79159L13.5548 8.58392L7.30516 13.3962L6.69507 12.6038L12.9447 7.79159Z" fill="#A2B1C6"/>
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<path d="M14.1316 6.51712L3.13166 3.51723L2.86844 4.48202L13.8684 7.48191L14.1316 6.51712Z" fill="#A2B1C6"/>
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</svg>
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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
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With sqliteviz you can:
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With sqliteviz you can:
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- run SQL queries against a SQLite database and create Plotly charts and pivot tables based on the result sets
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- run SQL queries against a SQLite database and create Plotly charts, graphs and pivot tables based on the result sets
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- import a CSV, JSON or NDJSON file into a SQLite database and visualize imported data
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- import a CSV, JSON or NDJSON file into a SQLite database and visualize imported data
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- export result set to CSV file
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- export result set to CSV file
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- manage inquiries and run them against different databases
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- manage inquiries and run them against different databases
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- import/export inquiries from/to a JSON file
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- import/export inquiries from/to a JSON file
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- export a modified SQLite database
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- export a modified SQLite database
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- use it offline from your OS application menu like any other desktop app
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- use it offline from your OS application menu like any other desktop app
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@@ -8,6 +8,7 @@
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"/docs/multiple-csv-file-import/",
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"/docs/multiple-csv-file-import/",
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"/docs/manage-inquiries/",
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"/docs/manage-inquiries/",
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"/docs/export-current-database/",
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"/docs/export-current-database/",
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"/docs/graph/",
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"/docs/pivot-table/",
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"/docs/pivot-table/",
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"/docs/predefined-inquiries/",
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"/docs/predefined-inquiries/",
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"/docs/sharing/",
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"/docs/sharing/",
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