[DOC] Pivot Table#3825
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janezd
reviewed
May 31, 2019
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| **Outputs** | ||
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| - Pivot Table: contingency matrix as set in the widget |
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... as showed? as seen? showed?
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| - Pivot Table: contingency matrix as set in the widget | ||
| - Filtered Data: subset selected from the plot | ||
| - Grouped Data: data table grouped by row values |
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Maybe - Grouped Data: aggregates over groups defined by row values?
| - Filtered Data: subset selected from the plot | ||
| - Grouped Data: data table grouped by row values | ||
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| **Pivot Table** summarizes the data of a more extensive table into a table of statistics. The statistics can include sums, averages, counts, etc. The widget also allows selecting a subset from the plot and grouping by row values, which have to be a discrete variable. Data with only numeric variables cannot be displayed in the plot. |
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plot? Probably table? (This appears twice.)
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| 1. Discrete or numeric variable that will be used for row values. Numeric variables are considered as integers in this case. Variable values will appear as rows in the table. |
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The last sentence is perhaps redundant. You can also remove "in this case." Also perhaps that will be.
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| 1. Discrete or numeric variable that will be used for row values. Numeric variables are considered as integers in this case. Variable values will appear as rows in the table. | ||
| 2. Discrete variable that will be used for column values. Variable values will appear as columns in the table. | ||
| 3. Values that will be used for aggregation. Aggregated values will appear as cells in the table. |
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Consider removing that will be; also above.
| 3. Values that will be used for aggregation. Aggregated values will appear as cells in the table. | ||
| 4. Aggregation methods: | ||
| - For any variable type: | ||
| - *Count*: number of instances that appear in the data |
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- *Count*: size of the group, that is, the number of instances with the given row and column value.
I'm not totally sure this is better, though. :)
| 4. Aggregation methods: | ||
| - For any variable type: | ||
| - *Count*: number of instances that appear in the data | ||
| - *Count defined*: number of non-empty (not NaN) instances in the data. |
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Huh, maybe "number of instances with this combination of the row and column value, for which the value that is used for aggregation is defined".
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| Example of a pivot table with only discrete variables selected. We are using *heart-disease* data set for this example. We are using the values of *diameter narrowing* as row values, namely 0 and 1. Our columns are values of *gender*, namely female and male. We are using *thal* as values in our cells. |
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We are using the values of *diameter narrowing* as row values -> Rows correspond to values of *diameter narrowing* variable.
You can skip namely.
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| Example of a pivot table with numeric variables. We are using *heart-disease* data set for this example. We are using the values of *diameter narrowing* as row values, namely 0 and 1. Our columns are values of *gender*, namely female and male. We are using *rest SBP* as values in our cells. |
| Example | ||
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| We are using *Forest Fires* for this example. The data is loaded in the [Datasets](../data/datasets.md) widget and passed to **Pivot Table**. *Forest Fires* datasets reports forest fires by the month and day they happened. We can aggregate all occurrences of forest fires by selecting *Count* as aggregation method and using *month* as row and *day* as column values. Since we are using *Count*, it does not matter what our *Values* variable will be, so we will leave it as is. |
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it does not matter what our *Values* variable will be -> maybe *Values* is unimportant (or something similar)
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Comments addressed as well as possible. |
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Issue
Pivot Table needs docs.
#3823
Description of changes
Add documentation for the widget.
Includes