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How to Extract (Get) Year or Month from a Date in Microsoft Excel - Office 365

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发布日期: 2024年3月26日

Extracting the year or month from a date in Microsoft Excel is a fundamental skill that greatly enhances your ability to organize, analyze, and visualize time-based data. Whether you're managing financial records, tracking project timelines, or analyzing sales trends, being able to isolate these components of a date allows for more precise filtering, sorting, and reporting. This tutorial will guide you through the process of extracting these elements, enabling you to work more effectively with date data in Excel.

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Benefits

Understanding how to extract the year or month from a date enables you to:

Improve Data Organization: Categorize data based on time periods for better management and accessibility.
Enhance Analysis: Conduct time-based analysis, such as year-over-year or month-over-month comparisons, more efficiently.
Customize Reporting: Tailor reports to focus on specific years or months, making them more relevant to your audience.

Step-by-Step Guide

Step 1: Prepare Your Dataset

Assume you have a list of dates in Column A of your Excel sheet, representing various events or transactions.

Input Dates: In A1, type "Date" as the header. Below it, in A2 onwards, enter the dates you're working with (e.g., 2023-03-15, 2022-11-24).

Step 2: Extract the Year from Dates

Add a Header for Year: In B1, type "Year".
Use the YEAR Function: In cell B2, enter the formula to extract the year from the date in A2:=YEAR(A2)
Apply to All Dates: Drag the fill handle down from B2 to copy the formula for all entries in Column A.

Step 3: Extract the Month from Dates

Add a Header for Month: In C1, type "Month".
Use the MONTH Function: In cell C2, enter the formula to extract the month from the date in A2:=MONTH(A2)
Apply to All Dates: Drag down from C2 to apply the formula to the entire column.

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Example

Imagine you are tasked with analyzing monthly sales data over several years to identify trends, seasonal patterns, and year-over-year growth. Your dataset consists of individual sales records with their corresponding dates.

Step 1: Prepare Your Sales Data

Data Setup:Column A has dates of sales transactions ranging from January 1, 2018, to December 31, 2022.Column B lists the sales amounts for each transaction.Your dataset spans from A2:B1000 (assuming 1000 total transactions).

Step 2: Extract Year and Month from Dates

Create Headers: In C1, type "Year", and in D1, type "Month".
Extract Years: In C2, enter =YEAR(A2). Drag the fill handle down to C1000.
Extract Months: In D2, enter =MONTH(A2). Drag the fill handle down to D1000.

Step 3: Create a Pivot Table for Monthly Sales Analysis

Insert Pivot Table:Select your dataset (A1:D1000).Go to Insert > PivotTable.Choose where you want the PivotTable report to be placed.
Configure the Pivot Table:Drag "Year" to the Rows area.Drag "Month" below "Year" in the Rows area.Drag "Sales" to the Values area, ensuring it's set to Sum.
Format the Month Display: To display month names rather than numbers in your PivotTable:Right-click on any month number in the PivotTable.Select "Group" > "Group Selection."Choose "Months" in the dialog box.(Note: This step may vary based on your Excel version and settings.)

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Advanced Tips

Formatting Months: To display months as names (e.g., January, February), use the TEXT function in combination with MONTH. For example:=TEXT(A2, "mmmm")This formula converts the date in A2 to its month name.
Dynamic Date Parts Extraction: To create a dynamic analysis tool, use data validation lists allowing users to select "Year" or "Month", and adjust your formulas to respond to these selections.
Combining Year and Month: For analyses that require year-month combinations (e.g., 2023-03), combine YEAR and MONTH with TEXT:=TEXT(A2, "yyyy-mm")
Pivot Table Analysis: Use extracted year and month columns as part of your PivotTable rows or columns to analyze data by time period without altering the original date format.