![]() ![]() For example, instead of weekly, you can group dates in a biweekly interval. Similarly, you can group dates by specifying any other number of days. This will group the dates by weeks as shown below: In such a case, you can either start the date on December 30, 2013, or Janu(both Mondays).To change this grouping and to begin the week from Monday, you need to change the start date (by default it picks the start date from the source data). So the grouping would be from Saturday to Friday every week. If you click OK at this point, your data would be grouped by weeks starting with Janu– which is a Saturday.In Number of days, enter 7 (or use the spin button to make the change).Note that for this to work, you need to select Days option only.You need to group by days and specify the number of days to be used while grouping. There is no inbuilt option to group by weeks.As soon as you do this, you would notice that the Number of Days option (at the bottom right) becomes available. In the Grouping dialogue box, select Days and deselect any other selected option(s).Here is how you can group dates by weeks: When working with dates in Pivot Tables, grouping dates by week is a bit different than grouping by months, quarters, or years. While analyzing data such as store sales or website traffic, it makes sense to analyze it on a weekly basis. You can simply drag the years’ field to the columns area to get the years in columns and months is rows. This would group the date field and summarize the data as shown below:Īgain, this would lead to a new field of Years getting added to the PivotTable fields. You can select more than one option by simply clicking on it. In the Grouping dialogue box, select Months as well as Years.Similar to the way we grouped the data by quarters, we can also do this by months.Īgain, it is advisable to use both Year and Month to group the data instead of only using months (unless you only have data for one or less than a year). The benefit of having this new field is that now you can analyze the data with quarters in rows and years in columns, as shown below:Īll you need to do is drop the Year field from Row area to Columns area. When you ungroup the data, this field will vanish. This field has been created in the Pivot Cache to quickly group and summarizes data. Note that this new field that has appeared is not a part of the data source. If you look at the field list, you will notice a new field has automatically been added. When you group dates by more than one time-frame group, something interesting happens. Note: I am using the tabular form layout in the above snapshot. This would summarize the data by Years and then within years by Quarters. In the Grouping dialogue box, select Quarters as well as Years.In a real life scenario, you are most likely to analyze these quarters for each year separately. Hence, for each quarter, the sales value is the sum of sales values in Quarter 1 in 20. The issue with this pivot table is that it combines the Quarterly sales value for 2014 as well as 2015. This would summarize the pivot table by quarters. In the Grouping dialogue box, select Quarters and deselect any other selected option(s). ![]() Here is how you can group these by quarters: In the above dataset, it makes more sense to drill down to quarters or months to have a better understanding of the sales. In this case, it would be better to have the quarterly or monthly data. This summarization by years may be useful when you have more number of years. This would summarize the pivot table by years.
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