In this video, the instructor explores a second example of using a count column within the raw source data to enable the creation of more flexible and powerful calculated fields.
- [Instructor] Okay, so now that I've introduced…this concept of using count columns for calculated fields,…I want to give you one more example…that's a little bit more tangible…in the case of this IMDb movie data.…So I showed you how we could calculate something…like revenue per title using that count column,…that number of titles column, but that it wasn't…particularly useful in this case…because we could just take the gross revenue field,…and summarize it by an average to give us the same answer.…I want to show you an example of a case…where you can't simply change to an average.…
You have to use that count column.…So, I'm going to pull rating out so that we're looking…at the data at the title level.…And you can see that the count is one in every case…since each title represents one row in our raw data.…Now I want to pull in two more fields here.…I'm going to pull in the cast Facebook likes, as a sum,…and the movie Facebook likes, as a sum.…And now let's say that I want to create…a new calculated field that sums these two fields together.…
- Establishing a layer convention and property filters
- Structuring your source data
- How PivotTables actually work
- Number formatting and conditional formatting
- Sorting and grouping options
- Troubleshooting incorrect sorting
- Value summarization and value calculation modes
- Inserting calculated items
- Visualizing data with PivotCharts
- Designing interactive dashboards
Skill Level Intermediate
Part 1: Introduction1m 8s
1. Getting Started
Getting to know IMDb2m 21s
2. PivotTable 101
3. PivotTable Formatting
4. Sorting, Filtering, and Grouping
5. Calculated Values, Fields, and Items
6. Visualizing Data with PivotCharts
7. Wrapping Up
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