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What is a PivotTable used for?

– A PivotTable is an interactive way to quickly summarize large amounts of data. You can use a PivotTable to analyze numerical data in detail, and answer unanticipated questions about your data. A PivotTable is especially designed for:

Querying large amounts of data in many user-friendly ways. Subtotaling and aggregating numeric data, summarizing data by categories and subcategories, and creating custom calculations and formulas. Expanding and collapsing levels of data to focus your results, and drilling down to details from the summary data for areas of interest to you. Moving rows to columns or columns to rows (or “pivoting”) to see different summaries of the source data. Filtering, sorting, grouping, and conditionally formatting the most useful and interesting subset of data enabling you to focus on just the information you want. Presenting concise, attractive, and annotated online or printed reports.

For example, here’s a simple list of household expenses on the left, and a PivotTable based on the list to the right:

Sales data	Corresponding PivotTable

For more information, see Create a PivotTable to analyze worksheet data,

What is pivot table in simple words?

A PivotTable is a powerful tool to calculate, summarize, and analyze data that lets you see comparisons, patterns, and trends in your data. PivotTables work a little bit differently depending on what platform you are using to run Excel.

What is pivot table and example?

A pivot table is a statistics tool that summarizes and reorganizes selected columns and rows of data in a spreadsheet or database table to obtain a desired report. The tool does not actually change the spreadsheet or database itself, it simply ‘pivots’ or turns the data to view it from different perspectives.

What is the difference between Excel and pivot table?

An Excel table is data a Pivot Table is information. A pivot table can provide more options for analysis – especially when you need to explain the raw data to other people.

What is the difference between a table and a pivot table?

Discovery – As you can see, the pivot table presents the data in a much more condensed way. Compared to the regular table, the number of rows has been halved and the number of columns is three instead of five. One of the advantages of a pivot table is the interchangeability: the ability to move row items to columns and column items to rows.

You can rearrange the data and have several different views of the same data set. You can move dimensions and measures to bring forward data of interest and hide data that is either too detailed, or irrelevant to the analysis. The pivot table shows the dimensions Customer, Product Group, and Item Desc, and the measures Quantity and Sales,

In this view, you have a summary of quantity and sales for each customer. If you want to know which items and product groups that the customers bought, you can expand the customer fields by clicking, A icon indicates that a field can be further expanded and present more details, while a icon indicates that the field can be collapsed, to reduce the number of fields and details. : Comparing straight tables and pivot tables | Qlik Sense on Windows Help

What is pivot table in SQL?

In this article – Applies to: SQL Server Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics Analytics Platform System (PDW) You can use the PIVOT and UNPIVOT relational operators to change a table-valued expression into another table. PIVOT rotates a table-valued expression by turning the unique values from one column in the expression into multiple columns in the output.

• And PIVOT runs aggregations where they’re required on any remaining column values that are wanted in the final output.
• UNPIVOT carries out the opposite operation to PIVOT by rotating columns of a table-valued expression into column values.
• The syntax for PIVOT is simpler and more readable than the syntax that may otherwise be specified in a complex series of SELECT.CASE statements.

For a complete description of the syntax for PIVOT, see FROM (Transact-SQL),

Why learn PivotTables?

What is a Pivot table? – This introductory lesson from our course The Excel PivotTables Guide explains what a pivot table is, and its’ areas of use. 1.1 NEW from Learnesy on Vimeo Playing in picture-in-picture Play 00:00 02:17 Settings Quality Auto Speed Normal GoogleCast Fullscreen This opens in a new window. const fullscreenSupported=”exitFullscreen”in document||”webkitExitFullscreen”in document||”webkitCancelFullScreen”in document||”mozCancelFullScreen”in document||”msExitFullscreen”in document||”webkitEnterFullScreen”in document.createElement(“video”);var isIE=checkIE(window.navigator.userAgent),incompatibleBrowser=!fullscreenSupported||isIE;window.noModuleLoading=!1,window.dynamicImportSupported=!1,window.isInIFrame=function() catch(e) }(),!window.isInIFrame&&/twitter/i.test(navigator.userAgent)&&window.playerConfig.video.url&&(window.location=window.playerConfig.video.url),window.playerConfig.request.lang&&document.documentElement.setAttribute(“lang”,window.playerConfig.request.lang),window.loadScript=function(e),window.loadVUID=function() },window.loadCSS=function(e,n) ;return i.link.rel=”stylesheet”,i.link.href=n,e.getElementsByTagName(“head”).appendChild(i.link),i.link.onload=function(),i},window.loadLegacyJS=function(e,n) /fallback`;window.playerConfig.request.referrer&&(o+=`?referrer=$ `),n.innerHTML=` `}else ))},window.loadVUID()}};function checkIE(e) var i=n(“msie”)?parseFloat(e.replace(/^.*msie (\d+).*$/,”$1″)):!1,t=n(“trident”)?parseFloat(e.replace(/^.*trident\/(\d+)\.(\d+).*$/,”$1.$2″))+4:!1;return i||t} One of the main advantages of Excel’s PivotTables is the ability to quickly and easily summarize large sets of data.

1. Instead of manually sifting through data and calculating totals, averages, and other metrics, pivot tables allow users to do all of this with just a few clicks.
2. For example, imagine you have a data set that contains information about customer orders, including the customer’s name, order date, product name, quantity, and price.

By creating a pivot table, you can quickly summarize this data to show total sales by customer, product, or date, as well as calculate average order size, profit margins, and other key metrics. This image shows a Pivot table with total sums of quantity and price total with the company names as categories and the products as sub-categories. Excel’s PivotTables are incredibly flexible when it comes to data analysis. Users can easily change how data is displayed, sorted, and filtered, allowing them to explore different aspects of the data and identify trends and patterns that may not be apparent at first glance. In this image, the pivot table is using a date-filter in which you can choose a specific day. Excel’s PivotTables are a great tool for creating interactive dashboards that allow users to explore data in a more engaging and dynamic way. By combining pivot tables with charts, slicers, and other interactive elements, users can create dashboards that allow others to easily navigate and analyze data. This image shows an Excel PivotChart for which our pivot table is the source to this visualization. One of the main advantages of pivot tables is their ability to automatically update when new data is added or existing data is changed. This means that users can create a pivot table and time and then continue to use as new data becomes available, without having to manually update the pivot table each time. This image shows where we can force the pivot table to refresh. Another benefit of pivot tables is that they can help improve data accuracy. By using pivot tables to summarize data, users can quickly find any inconsistencies or errors in the data set. For example, if a pivot table shows that the total sales for a particular product are much higher than expected, it may indicate that there is an error in the data set that needs to be corrected.

Excel’s PivotTables are an efficient way to generate reports that summarize data in a clear and concise manner. Instead of manually creating reports, use pivot tables to generate reports quickly and easily, saving time and reducing the risk of errors. For example, imagine that you need to create a monthly sales report that summarizes sales by product and region.

By creating a pivot table, you can quickly generate the report and then make the necessary adjustments or adjustments as needed. In conclusion, Excel’s PivotTables are an essential tool for anyone working with data. They provide a flexible and efficient way to analyze and present large sets of data, making it easy to identify trends and patterns that might otherwise go unnoticed.

What is pivot table formula?

– You can create formulas only in reports that are based on a non-OLAP source data. You cannot use formulas in reports that are based on an OLAP database. When you use formulas in PivotTables, you should know about the following formula syntax rules and formula behavior:

• PivotTable formula elements In formulas that you create for calculated fields and calculated items, you can use operators and expressions as you do in other worksheet formulas. You can use constants and refer to data from the report, but you cannot use cell references or defined names. You cannot use worksheet functions that require cell references or defined names as arguments, and you cannot use array functions.
• Field and item names Excel uses field and item names to identify those elements of a report in your formulas. In the following example, the data in range C3:C9 is using the field name Dairy, A calculated item in the Type field that estimates sales for a new product based on Dairy sales could use a formula such as =Dairy * 115%, Note: In a PivotChart, the field names are displayed in the PivotTable field list, and item names can be seen in each field drop-down list. Don’t confuse these names with those you see in chart tips, which reflect series and data point names instead.
• Formulas operate on sum totals, not individual records Formulas for calculated fields operate on the sum of the underlying data for any fields in the formula. For example, the calculated field formula =Sales * 1.2 multiplies the sum of the sales for each type and region by 1.2; it does not multiply each individual sale by 1.2 and then sum the multiplied amounts. Formulas for calculated items operate on the individual records. For example, the calculated item formula =Dairy *115% multiplies each individual sale of Dairy times 115%, after which the multiplied amounts are summarized together in the Values area.
• Spaces, numbers, and symbols in names In a name that includes more than one field, the fields can be in any order. In the example above, cells C6:D6 can be ‘April North’ or ‘North April’, Use single quotation marks around names that are more than one word or that include numbers or symbols.
• Totals Formulas cannot refer to totals (such as, March Total, April Total, and Grand Total in the example).
• Field names in item references You can include the field name in a reference to an item. The item name must be in square brackets — for example, Region, Use this format to avoid #NAME? errors when two items in two different fields in a report have the same name. For example, if a report has an item named Meat in the Type field and another item named Meat in the Category field, you can prevent #NAME? errors by referring to the items as Type and Category,
• Referring to items by position You can refer to an item by its position in the report as currently sorted and displayed. Type is Dairy, and Type is Seafood, The item referred to in this way can change whenever the positions of items change or different items are displayed or hidden. Hidden items are not counted in this index. You can use relative positions to refer to items. The positions are determined relative to the calculated item that contains the formula. If South is the current region, Region is North ; if North is the current region, Region is South, For example, a calculated item could use the formula =Region * 3%, If the position that you give is before the first item or after the last item in the field, the formula results in a #REF! error.

What is a pivot column?

Definition. If a matrix is in row-echelon form, then the first nonzero entry of each row is called a pivot, and the columns in which pivots appear are called pivot columns.

What is VLOOKUP in Excel?

What is VLOOKUP in Excel? – VLOOKUP stands for Vertical Lookup. As the name specifies, VLOOKUP is a built-in Excel function that helps you look for a specified value by searching for it vertically across the sheet. VLOOKUP in Excel may sound complicated, but you will find out that it is a very easy and useful tool once you try it. In the next section, you will understand how to use the VLOOKUP function.

What is the difference between Vlookup and pivot table?

Vlookup – Function used to find out a value in a range of data in the same worksheet or an external worksheet. Pivot Table: Used to represent bulk data in a more user friendly manner. Information can be portrayed in more vividly with the help of charts, slicers, tables etc.

Are PivotTables better than formulas?

Data Analysis in Excel: PivotTables versus COUNTIFS, SUMIFS, AVERAGEIFS formulas Data structured in a table format often makes it easy to analyze it and make better decisions. Data analysis in Excel can be done by using formulas like COUNTIFS, SUMIFS, and AVERAGEIFS, but Excel’s PivotTables make it a breeze organizing and presenting data.

• In this article, we’re going to compare the two approaches for analyzing data in Excel, using formulas and PivotTables.
• Let’s assume we have a spreadsheet that contains employee data, and we want to find the average base salaries by department, to create an annual report.
• You can download this data set by clicking the button below.

We can calculate this by using a handful of AVERAGEIF(S) functions. However, data needs to be organized first for use in AVERAGEIFS functions. First step is getting the department names from the table and remove the duplicate values to get a list of unique items.

• Sorting the department names
• Add titles
• Summarize row
• Bold characters for title and total rows
• Background colors
• Borders
• Adjusting to column widths
• Number formatting that matches the type of the data (e.g. Currency)

Finally, we can start adding the formulas. We can use references from the Department names in AVERAGEIFS formulas when selecting department names. We could also use the AVARAGEIF function, but the AVERAGEIFS function can accept more than one criteria and this is generally a better approach from a future-proofing perspective.

We used to make the formulas easier to read and manage. While Base_Salary named range represents the range that contains the base salary values, Department represents the column of department names. The last step is adding a formula for summary calculation which will give us the averages. Dividing the sum of base salary values by the count of rows gives the average values we need.

Let’s now analyze the same data using PivotTable, Begin by selecting the cell to be the top left cell of your PivotTable and click the PivotTable icon under the INSERT tab on the ribbon.

2. Add the reference for your data into the Create PivotTable dialog box and click OK to create your PivotTable.

Next, we’re going to add the columns we want to display and add number formatting. That’s it! The PivotTables are very easy to create and configure. You do not need to add any formulas and data analysis features can be added directly through table controls.

• Adding columns if there is additional content at the end of the table
• Update the format like borders, background colors and number formats.
• Repeat the copy-paste process and Remove Duplicates for the state values
• Edit the titles

• Modifying the existing formulas, we will end up with the updated calculations.

This step requires a closer attention. We must use an Absolute-Relative reference combination to preserve the calculation results. You might also want to add an IFFERROR function or conditional formatting to prevent error messages from being displayed for empty cells.

• After dealing with the possible errors, once again, we need to update the formula to calculate values for the summary row.
• Finally, our table shows 2 levels of filtered consolidated values of our base data.
• Let’s now see how a 2 nd level of data can be added into this PivotTable,
• All you need to do is drag & drop the secondary data.

You can change the calculation logic or filtering with a few clicks. Filters, also known as slicers can also be added with a click. Slicers are filters of PivotTables that can be linked multiple PivotTables and PivotCharts, You can insert any column of your data as a slicer and filter your data.

• They are faster, especially with large datasets.
• Formulas can use at most 127 conditions, PivotTables can handle much more as much as memory allows.
• Easy to apply visualization options.
• PivotCharts that can visualize data are just as easy to create as PivotTables
• You can group any data field without any additional formulas.

: Data Analysis in Excel: PivotTables versus COUNTIFS, SUMIFS, AVERAGEIFS formulas

Why is it called a pivot table?

Typically, with a pivot table the user sets up and changes the data summary’s structure by dragging and dropping fields graphically. This ‘rotation’ or pivoting of the summary table gives the concept its name.

Is A pivot table a chart?

A PivotChart is similar to an ordinary chart created in Excel, except that it plots a PivotTable’s information. Like PivotTable reports, PivotCharts are dynamic, which means you can change a PivotChart by updating the values in a PivotTable.

Can you do a Vlookup from a pivot table?

To use VLOOKUP in a PivotTable is similar to using the VLOOKUP function in any other data range or table : First, select the reference cell as the lookup value. Next, choose the data in the PivotTable for the table arguments array and then identify the column number with the output.

Why do we need pivot in SQL?

In this article, I am going to explain how we can create a dynamic pivot table in SQL Server. Pivot tables are a piece of summarized information that is generated from a large underlying dataset. It is generally used to report on specific dimensions from the vast datasets.

Essentially, the user can convert rows into columns. This gives the users the ability to transpose columns from a SQL Server table easily and create reports as per the requirements. Some pivot tables are also created to help in data analysis, mainly for slicing and dicing with the data and generate analytical queries after all.

If you see the figure below, you’ll have some idea how a pivot table is created from a table. Figure 1 – Pivot Table Example If you see the figure above, you can see that there are two tables. The table on the left is the actual table that contains the original records. The table on the right is a pivot table that is generated by converting the rows from the original table into columns.

Is pivot a function in SQL?

The PIVOT Function The query starts with a SELECT statement where the column is the column that will appear first in the pivot table. The following pivot_values are the values that will be pivoted. A FROM specifies the source of the query. The PIVOT function then closes the query.

Can you create a pivot table in SQL?

SUM, AVG, or other aggregate functions – You can also use the GROUP BY and CASE statements to create pivot tables that show other types of data, such as the average price for each product. For example, the following query would create a pivot table that shows the average price for each product: SELECT product, AVG ( CASE WHEN price THEN price ELSE NULL END ) AS avg_price FROM sales GROUP BY product The resulting pivot table would look something like this:

product	avg_price
ProductA	10
ProductB	20
ProductC	15

In summary, to create a pivot table in SQL, you can use the GROUP BY and CASE statements along with aggregation functions like SUM and AVG to calculate and display the data you want to see in the pivot table. This approach allows you to easily summarize and analyze large amounts of data, and can be very useful for making business decisions. : How to make a pivot table in SQL

What is the basic difference between pivot and pivot table?

Example of using Pivot_Table Method – Here is an example of how to use the pivot_table method to create a pivot table: In this example, we first create a sample DataFrame df that contains sales data for four products (A, B, C, D) for the months of January, February. To create a pivot table, we use the pivot_table method to specify the Sales column as the values in the pivot table, the Product column as the rows of the pivot table, and the Month column as the columns of the pivot table. As you can see, the pivot_table method has created a pivot table that summarizes the sales data by grouping it into categories (Product and Month) and calculating the mean of the sales data. This pivot table makes it easy to compare the sales data for different products and months and quickly identify patterns in the data.

Let me present you three main differences between pivot and pivot_table methods: 1. One major difference between the pivot and pivot_table methods is that pivot_table allows for aggregation of the data, whereas pivot does not. This means that pivot_table can be used to calculate statistics such as sum, mean, or count, while pivot can only reshape the data without performing any calculations.2.

Another difference between the two methods is that pivot_table can handle duplicate values in the index and columns arguments, while pivot cannot. If there are duplicate values in the index or columns arguments when using pivot, a ValueError will be raised.

1. Pivot_table, on the other hand, can handle duplicate values by using the aggfunc argument to specify the aggregation function to be used.3.
2. A third difference between pivot and pivot_table is that pivot_table accepts a multi-level index and columns, while pivot only accepts single-level index and columns.

This means pivot_table can handle more complex data structures, while pivot is limited to simpler data structures. In conclusion, pivot and pivot_table are two powerful methods in the Pandas library for reshaping and reorganizing data in a DataFrame. Both methods can be used to transform data from a wide format to a long format, or vice versa.

However, there are several key differences between the two methods. pivot is a simpler method that is used to reshape data by specifying the index, columns, and values of a DataFrame, while pivot_table is a more powerful method that is used to create a pivot table from a DataFrame. pivot_table allows for aggregation of the data and can handle duplicate values, whereas pivot does not.

Additionally, pivot_table accepts multi-level index and columns, while pivot only accepts single-level index and columns.

What is the main difference between PivotTables in Excel and Google Sheets?

Data analysis and visualization – Both Excel and Google Sheets offer a vast collection of formulas, though Excel’s is slightly more extensive—we’re talking nearly 500. This makes tasks like accounting, data organization, and statistical analysis a breeze. Where Excel really shines is in advanced data analysis, Navigate to the Data tab, and you’ll notice an option to perform a What-If Analysis, This enables you to test scenarios using Excel’s advanced formulas. For example, you could use this feature to determine how many units you’d need to sell in the final month of the quarter to achieve financial goals. Google Sheets also allows you to generate pivot tables, but it doesn’t let you manipulate or visualize the data with advanced pivot table features. In fact, Excel proves itself supreme when it comes to creating any type of data visualization. For example, when I selected a large set of data and clicked Excel’s Recommended Charts option, it presented various logical ways that I could present elements of the data, such as units and unit costs over time. Google Sheets lacks this feature and offers fewer data visualization options altogether. When I selected the entire data set, Sheets created a nonsensical graph rather than automatically pulling relevant data. To make it look anything like Excel’s chart, I’d have to manually adjust it.

What is the difference between pivot and power pivot in Excel?

The normal pivot version just lists fields within this single table or source that we’re pointing to. Power Pivot allows us to access any of the fields in any of the tables in our data model, and then analyze them based on any relationships that we’ve defined. So that’s the most obvious of the differences.