CSV plugin
The CSV plugin allows you to visualize CSV data, which can either be read from a CSV file or entered manually.
To add a data source click on the + next to Data Sources on the left-hand menu in SquaredUp. Search for the data source and click on it to open the Configure data source page.
You can also add a data source by clicking Add data source on the Settings > Data Sources page, but pre-built dashboards are not added when using this method.
Configuring the data source
Display Name:
Enter a name for your data source. This helps you to identify this data source in the list of your data sources.Restrict access to this data source:
You can enable this option if you only want certain users or groups to have access to the data source, or the permission to link it to new workspaces. See data source access control for more information.- Click Add to add the plugin.
Next steps
Once you've added a CSV data source, you can start creating dashboards to visualize your data.
Use the File data stream to use CSV data which is saved in a file, or theRaw Text data stream to copy and paste the raw CSV data straight into the tile.
Show data on a tile using a CSV file
You can share a file on Onedrive, but you will need to set the link settings to work for Anyone, so you should consider whether this is suitable security for the data you are using.
- On a dashboard click + and then Data to add a new data tile.
- Data Stream tab:
Click on File.
If File isn't listed then perhaps the data source was added for the organization but not this workspace. Click the Data Source menu > Add new data source and look through the data sources listed.
If you still can't see the data source perhaps it doesn't exist at the organization level, so click the link at the bottom of the page to add a new data source.
Click on the Objects tab (or click Next). - Objects tab:
Click on the name you gave your Data Source to tick it.
Click on the Parameters tab (or click Next). - Parameters tab:
CSV Location:
Select Web URL.
URL:
Paste the web location of your CSV file into the box.
Has Header Row:
If your data uses the first row as the header tick the box.
Advanced Options:
Delimiter:
If the delimiter is not automatically detected, you can specify the delimiter, such as a semicolon, here.
Skip Lines:
Enter the number of lines in the file to skip before importing CSV data. This is useful in circumstances where the file includes some sort of intro text.Ignore Certificate errors:
If you activate this checkbox the data source will ignore certificate errors when accessing the server. This is useful if you have self-signed certificates.
- Timeframe tab: Timeframe is not supported for this tile.
- A suitable visualization is chosen, where possible, but at this point you might like to change the visualization used, see Visualization Settings.
In the right hand pane you can also hide and sort columns,
The Shaping and Columns sections can help you configure the visualization as you need. - Shaping tab:
Shaping allows you to perform filtering, grouping and sorting operations on the data.Data can be filtered according to whether data in a column meets or does not meet specified text or numerical value conditions. Depending on the data you are filtering, available options include: Equals, Not equals, Contains, Doesn't contain, Less than, Greater than, Before now, After now, Is empty, Is not empty.
Dates can be filtered by Before now or After now (e.g. to show overdue orders). Text matching is case sensitive.
You are able to add multiple filter conditions. Available options are:
- AND: All conditions must be satisfied (e.g.
Status-Equals-Closed
ANDType-Equals-Question
). - OR: Any condition can be satisfied (e.g.
Status-Equals-Pending
ORStatus-Equals-Closed
).
You can group and aggregate data by column.
For example, for AWS cost data you might configure the following settings to display a table or bar chart of cost per label:
- Group by:
label
- Aggregation type:
Total
- Aggregation column:
Amount
Which columns are available depends on the data stream you chose.
Configuring grouping enables different visualizations to be displayed, such as bar chart and donut. For example, grouping tickets by channel allows you to show a donut of how many tickets were logged by email vs web form.
Bucket by
If you group by a time column, and further grouping is possible, the Bucket by dropdown appears. Use this field to control how the time data is grouped, for example by
hour
,day
,month
etc.Aggregation type and column
Use this dropdown to choose how to summarize your data, for example as a
count
,average
ortotal
.
For example, you could do the following:- When creating a Bar Chart of ticket data you might configure the following settings to show a graph of tickets per day:
- Group by:
Date created
- Bucketby:
Day
- Aggregation type:
Count
- Group by:
- When creating Bar Chart of Azure Resource Group cost you could configure the following settings:
- Group by:Timestamp
- Bucketby:
Day
- Aggregation type:
Total
- Aggregate column:
Cost
The Sort section allows you to select a column to be displayed in Ascending or Descending order. While this sets the default sort order, but you can always click on a column heading to sort data in a table on the fly.
Enabling the Top toggle allows you to additionally specify the top n rows of data to display.
- AND: All conditions must be satisfied (e.g.
- Columns tab:
Use the Columns tab of the tile editor to format the columns of the table on the Data tab.SquaredUp automatically defines the metadata retrieved from data streams so the data is assigned the correct data type, however in some circumstances you may want to override this.
For example, when retrieving data using the Web API plugin, scripting, or custom query data streams (such as Splunk Enterprise plugin), the assigned data type may not be quite correct or as you expect.
Formatting columns
Use the following options to format your columns.
Comparison columns
Comparison columns are used to compare two values, for example you may want to compare the number of tickets raised this month to the number of tickets raised last month. You can choose to show the value as an absolute change (for example, 12 more tickets) or as a percentage change (for example, a 28% increase).
When a column has a Type of Number, the Add comparison
button displays at the end of the row, which you can click to open the Add comparison window.From this window, if you have multiple columns with a Type of Number, you can create a comparison column by doing the following:- Column A:
Select the first column to compare against. Automatically populated with the column of which you clicked Add comparison. - Column B:
Select the second column to compare against. - Output:
Select how to display the comparison value. This value is displayed in the Preview field. Choose from:- Absolute: Show the numerical value of Column A - Column B.
- Percentage: Show the ratio of Column B to Column A as a percent.
- Click Update to create the comparison. A new column is added to the Output table.
Additional options
Some data types have advanced settings that can be configured in the options section, which is displayed whenever you change the data Type or by clicking expand
next to the column Name. - Column A:
- Optionally, configure Monitoring and KPIs.
- When you have finished click Save.
Show data on a tile using CSV Raw Text
This data stream is designed to quickly handle small amounts of data and is therefore limited to 20,480 characters. If you need to work with larger amounts of data, use the File data stream to read directly from the source file. Alternatively you may want to aggregate the data to use here.
- On a dashboard click + and then Data to add a new data tile.
- Data Stream tab:
Click on Raw Text.
If Raw Text isn't listed then perhaps the data source was added for the organization but not this workspace. Click the Data Source menu > Add new data source and look through the data sources listed.
If you still can't see the data source perhaps it doesn't exist at the organization level, so click the link at the bottom of the page to add a new data source.
Click on the Objects tab (or click Next). - Objects tab:
Click on the name you gave your Data Source to tick it.
Click on the Parameters tab (or click Next). - Parameters tab:
CSV Text:
Paste your raw CSV data into the box.
Has Header Row:
If your data uses the first row as the header tick the box.
Advanced Options:
If the delimiter, i.e. comma, is not automatically detected, you can specify the delimiter, such as a semicolon, here. - Timeframe tab: Timeframe is not supported for this tile.
- A suitable visualization is chosen, where possible, but at this point you might like to change the visualization used, see Visualization Settings.
In the right hand pane you can also hide and sort columns,
The Shaping and Columns sections can help you configure the visualization as you need. - Shaping tab:
Shaping allows you to perform filtering, grouping and sorting operations on the data.Data can be filtered according to whether data in a column meets or does not meet specified text or numerical value conditions. Depending on the data you are filtering, available options include: Equals, Not equals, Contains, Doesn't contain, Less than, Greater than, Before now, After now, Is empty, Is not empty.
Dates can be filtered by Before now or After now (e.g. to show overdue orders). Text matching is case sensitive.
You are able to add multiple filter conditions. Available options are:
- AND: All conditions must be satisfied (e.g.
Status-Equals-Closed
ANDType-Equals-Question
). - OR: Any condition can be satisfied (e.g.
Status-Equals-Pending
ORStatus-Equals-Closed
).
You can group and aggregate data by column.
For example, for AWS cost data you might configure the following settings to display a table or bar chart of cost per label:
- Group by:
label
- Aggregation type:
Total
- Aggregation column:
Amount
Which columns are available depends on the data stream you chose.
Configuring grouping enables different visualizations to be displayed, such as bar chart and donut. For example, grouping tickets by channel allows you to show a donut of how many tickets were logged by email vs web form.
Bucket by
If you group by a time column, and further grouping is possible, the Bucket by dropdown appears. Use this field to control how the time data is grouped, for example by
hour
,day
,month
etc.Aggregation type and column
Use this dropdown to choose how to summarize your data, for example as a
count
,average
ortotal
.
For example, you could do the following:- When creating a Bar Chart of ticket data you might configure the following settings to show a graph of tickets per day:
- Group by:
Date created
- Bucketby:
Day
- Aggregation type:
Count
- Group by:
- When creating Bar Chart of Azure Resource Group cost you could configure the following settings:
- Group by:Timestamp
- Bucketby:
Day
- Aggregation type:
Total
- Aggregate column:
Cost
The Sort section allows you to select a column to be displayed in Ascending or Descending order. While this sets the default sort order, but you can always click on a column heading to sort data in a table on the fly.
Enabling the Top toggle allows you to additionally specify the top n rows of data to display.
- AND: All conditions must be satisfied (e.g.
- Columns tab:
Use the Columns tab of the tile editor to format the columns of the table on the Data tab.SquaredUp automatically defines the metadata retrieved from data streams so the data is assigned the correct data type, however in some circumstances you may want to override this.
For example, when retrieving data using the Web API plugin, scripting, or custom query data streams (such as Splunk Enterprise plugin), the assigned data type may not be quite correct or as you expect.
Formatting columns
Use the following options to format your columns.
Comparison columns
Comparison columns are used to compare two values, for example you may want to compare the number of tickets raised this month to the number of tickets raised last month. You can choose to show the value as an absolute change (for example, 12 more tickets) or as a percentage change (for example, a 28% increase).
When a column has a Type of Number, the Add comparison
button displays at the end of the row, which you can click to open the Add comparison window.From this window, if you have multiple columns with a Type of Number, you can create a comparison column by doing the following:- Column A:
Select the first column to compare against. Automatically populated with the column of which you clicked Add comparison. - Column B:
Select the second column to compare against. - Output:
Select how to display the comparison value. This value is displayed in the Preview field. Choose from:- Absolute: Show the numerical value of Column A - Column B.
- Percentage: Show the ratio of Column B to Column A as a percent.
- Click Update to create the comparison. A new column is added to the Output table.
Additional options
Some data types have advanced settings that can be configured in the options section, which is displayed whenever you change the data Type or by clicking expand
next to the column Name. - Column A:
- Optionally, configure Monitoring and KPIs.
- When you have finished click Save.