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About Lynda.com Lynda.com is free to all members of the University. Visit courses. it. ox. ac.uk/lynda and sign in with your Single Sign-On SSO credentials. They can all be downloaded from the ITLC Portfolio at http //portfolio. it. ox. ac.uk/resource/course-pack/data-analysis-pivottables-researchacademicdata/2013 The fields in the PivotTable Field List appear as checkboxes in the task pane dialog box see diagram 4 above. To add fields to the PivotTable simply drag the field name to the...
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How to fill out pivottables to summarise
How to fill out pivottables to summarise
01
To fill out pivot tables and summarize data, follow these steps:
02
Open the spreadsheet or data source where the data is located.
03
Select the data range you want to include in the pivot table.
04
Click on the 'Insert' tab in the toolbar and choose 'PivotTable'.
05
In the 'Create PivotTable' dialog box, make sure the data range is correct and select where you want the pivot table to be placed (new worksheet or existing worksheet).
06
Click 'OK' to create the pivot table.
07
Once the pivot table is created, you can drag and drop the fields from the data source into the 'Rows', 'Columns', and 'Values' areas in the pivot table field list.
08
Customize the summary functions by selecting the field in the 'Values' area, clicking on the small arrow next to 'Summarize Values By', and choosing the desired function (e.g., sum, average, count, etc.).
09
Use the 'Filters' area to filter the data based on specific criteria.
10
Format the pivot table as needed by applying formatting options from the 'Design' tab in the toolbar.
11
Refresh the pivot table when the source data is updated by clicking on the 'Refresh' button in the 'PivotTable Tools' tab.
Who needs pivottables to summarise?
01
Pivot tables are useful for anyone who wants to summarize and analyze data efficiently. Some individuals or groups that may benefit from using pivot tables include:
02
- Business analysts who need to analyze sales data, customer data, or any other data to identify trends and patterns.
03
- Financial professionals who need to analyze financial statements, budgets, or investment data to make informed decisions.
04
- Project managers who need to track project progress, resources, and budgets.
05
- Researchers who need to analyze survey data, experiment results, or any other research data.
06
- Students and educators who need to analyze data for research projects or educational purposes.
07
- Data analysts who need to explore and summarize large datasets for reporting or data visualization.
08
- Anyone who deals with large amounts of data and needs a user-friendly way to summarize and analyze it effectively.
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