Copilot (licence) - Sort and project using Copilot in Excel with Python Tutorial

Unlock the power of Excel with Python using Copilot! In this video titled "Sort and Project Using Copilot in Excel with Python", discover how to make data classification simple and effective. From creating scatter plots to predicting future sales, learn to harness advanced analytics for smarter decision-making. Don't miss out on transforming your Excel experience!

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Objectifs :

This video aims to demonstrate how to utilize Co-Pilot in Excel with Python to classify data, create visualizations, and make accurate forecasts based on historical data.

Chapitres :

Introduction to Co-Pilot in Excel
Co-Pilot in Excel with Python enhances data analysis capabilities, allowing users to classify data and explore projection possibilities efficiently.
Using the Product Sales Data
The demonstration utilizes an Excel file containing comprehensive product sales information, consisting of 5000 rows of data. This extensive dataset provides a solid foundation for analysis.
Data Visualization with Scatter Plots
To begin the analysis, a scatter plot is created to examine the relationship between quantity sold and turnover. This visual representation helps in identifying any correlations between these two variables.
Ranking Products by Turnover
Next, Co-Pilot is instructed to rank the products based on total turnover, from largest to smallest. This ranking allows for a quick assessment of which products are performing best in terms of sales.
Identifying Influential Commercial Levers
To delve deeper into the data, a correlation analysis is requested to identify the most influential commercial levers. This step is crucial for understanding which factors significantly impact sales performance.
Sales Forecasting for the Next Three Months
The session concludes with a request for sales predictions for the upcoming three months based on historical data. Co-Pilot selects a forecasting model, although users can opt for other advanced time series models if desired.
The Power of Python and Excel
Co-Pilot in Excel showcases the synergy between Python and Excel, offering advanced visual analytics, dynamic rankings, and precise forecasts with minimal coding. This integration empowers users to make faster and smarter decisions.

FAQ :

What is Co-Pilot in Excel?

Co-Pilot in Excel is an advanced feature that helps users analyze and visualize data more effectively by utilizing machine learning and Python capabilities.

How can I create a scatter plot in Excel?

To create a scatter plot in Excel, you can use the Co-Pilot feature to request a scatter plot based on your selected data, which will help you visualize relationships between variables.

What does turnover mean in a business context?

Turnover refers to the total revenue generated by a business from its sales of products or services over a specific time period.

How does correlation help in data analysis?

Correlation helps in data analysis by identifying the strength and direction of relationships between variables, which can inform decision-making and strategy.

What types of forecasting models can Co-Pilot use?

Co-Pilot can use various forecasting models, including basic linear models and more advanced time series models, to predict future sales based on historical data.

What are the benefits of using Python with Excel?

Using Python with Excel enhances data analysis capabilities by providing advanced functions, visual analytics, and the ability to handle large datasets efficiently.

Can I customize the visualizations created by Co-Pilot?

Yes, you can customize the visualizations created by Co-Pilot in Excel to better suit your analysis needs and preferences.

Quelques cas d'usages :

Sales Data Analysis

Using Co-Pilot in Excel, sales teams can analyze product sales data to identify trends, visualize relationships between quantity sold and turnover, and make informed decisions on inventory management.

Market Research

Market researchers can utilize Co-Pilot to create scatter plots and correlation analyses to understand consumer behavior and identify key factors influencing sales performance.

Financial Forecasting

Finance professionals can leverage Co-Pilot's forecasting models to predict future sales and revenue, helping businesses plan budgets and allocate resources effectively.

Performance Tracking

Managers can use dynamic rankings generated by Co-Pilot to track product performance over time, allowing for quick adjustments to marketing strategies based on real-time data.

Data-Driven Decision Making

Organizations can implement Co-Pilot's advanced visual analytics to support data-driven decision-making processes, improving overall efficiency and outcomes in various business operations.

Glossaire :

Co-Pilot

A feature in Excel that assists users in data analysis and visualization by leveraging advanced algorithms and machine learning capabilities.

Scatter Plot

A type of data visualization that uses dots to represent the values obtained for two different variables, allowing users to see relationships or correlations between them.

Turnover

The total revenue generated by a business from its sales of goods or services during a specific period.

Correlation Link

A statistical measure that describes the extent to which two variables change together, indicating the strength and direction of their relationship.

Forecasting Model

A mathematical model used to predict future data points based on historical data, often used in sales and financial analysis.

Advanced Series Models

Sophisticated statistical models used for time series analysis that can capture complex patterns in data, such as trends and seasonality.

Visual Analytics

The use of visual representations of data to help users understand complex information and make data-driven decisions.

Dynamic Rankings

Rankings that can change in real-time based on updated data inputs, allowing for more accurate and timely decision-making.

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you can easily classify data and use projection possibilities.

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I use this Excel file containing product sales information.

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The table is quite complete and contains 5000 lines.

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I will ask co-pilot to help me understand the data and classify it correctly.

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I start by asking him for a scatter plot to

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check if there is a relationship between quantity and turnover.

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Then I ask him to rank the products by total turnover

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from largest to smallest,

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and to visualize the 1st 10 and graph.

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It's interesting.

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I want to go further and ask for a

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correlation link to identify the most influential commercial levers.

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Finally,

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I end by asking for a precision of sales for the next 3 months based on the history.

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Co-pilot in Excel has chosen a forecasting model,

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but it can be asked to use other advanced series models.

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With co-pilot,

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Python and Excel goes far beyond traditional functions.

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It offers advanced visual analytics,

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dynamic rankings,

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and accurate forecasts in just a few lines.

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It's the combination of the power of Python

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and the simplicity of Excel for faster,

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smarter decision making.

Mandarine AI: WHAT YOU SHOULD KNOW

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