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Excel 2016 - Créer un tableau croisé dynamique - Tuto #43

Numiana2015-05-25
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1M views|9 years ago
💫 Short Summary

This tutorial in Excel demonstrates how to create a pivot table (tableau croisé dynamique) to quickly analyze and cross-tabulate data, specifically showing the total operations' amounts by date and gender. It also covers the basics of pivot table creation, including selecting the data, initiating the pivot table, and designing the pivot table structure, as well as enhancing it with tips and tricks.

✨ Highlights
📊 Transcript
A pivot table in Excel is a new table that takes existing data and dynamically cross tabulates it.
00:00
It allows for quickly obtaining results from data without manual operations, sorting, or filtering.
An example will be used to demonstrate the real application of a pivot table.
To create a pivot table in Excel, click anywhere inside the table, go to the 'Insert' tab, and select 'PivotTable'.
02:18
A new window will open to confirm the selected data and the location for the pivot table.
Choosing to create the pivot table in a new worksheet automatically generates a new sheet with the pivot table layout.
The 'PivotTable Fields' window will also appear, allowing the user to specify the fields and their placements in the pivot table.
Differentiating between men and women for each day's operations
04:10
In the original table, the same day appeared on four rows, but in the pivot table, each day is on a separate row.
Adding the 'Title' field to the column area to distinguish between men and women.
Placing the 'Amount' field in the values area to get the total sum of operations for each day and gender.
The video demonstrates how to change the calculation type in the pivot table from sum to average using pivot table designers.
05:13
By clicking on the 'More Options' button, a new window for field settings is opened, allowing the user to choose the desired summary function.
The example shows how to switch the calculation from sum to average for the 'Amount' field.
💫 FAQs about This YouTube Video

1. What is a pivot table in Excel and how does it work?

A pivot table in Excel is a powerful tool that allows you to summarize and analyze data interactively. It enables you to transform lists of data into a clear and concise summary, making it easier to draw meaningful insights and make data-driven decisions. Pivot tables can quickly aggregate and display data in various ways, such as sums, averages, counts, and more, providing a flexible and dynamic analysis of the underlying information.

2. How do you create a pivot table in Excel?

Creating a pivot table in Excel is a straightforward process. You can follow these steps to create a pivot table: 1. Select the data range you want to analyze. 2. Go to the "Insert" tab on the Excel ribbon. 3. Click on "PivotTable". 4. In the Create PivotTable dialog, ensure the selected range is correct and choose where to place the pivot table (new worksheet or existing worksheet). 5. Click "OK" to create the pivot table. Once the pivot table is created, you can further customize it by adding fields to the rows, columns, and values areas to perform the desired analysis.

3. What are the benefits of using a pivot table in Excel for data analysis?

Pivot tables offer several benefits for data analysis in Excel, including: 1. Summarizing and aggregating large data sets. 2. Easily rearranging the layout to view data from different perspectives. 3. Applying filters and sorts without altering the original data. 4. Performing quick calculations such as sums, averages, and more. 5. Visualizing data with charts and graphs. 6. Enhancing decision-making by uncovering trends and patterns. Overall, pivot tables streamline the data analysis process and provide valuable insights for better decision-making.

4. What are some common operations you can perform with a pivot table in Excel?

Pivot tables in Excel support a variety of common operations for data analysis, including: 1. Summarizing data by calculating sums, averages, counts, and other functions. 2. Grouping data by date, time, or custom categories for better analysis. 3. Filtering data to focus on specific subsets for more targeted insights. 4. Displaying data in different layouts to compare and evaluate information. 5. Creating calculated fields and items to perform additional analysis within the pivot table structure. These operations empower users to explore and understand their data more effectively.