**Data cleaning** is an essential step in data analysis. Before you can derive any meaningful insights from your data, it must be **accurate and free of inconsistencies**. 

Cleaning data involves correcting or removing **incorrect**, **corrupted**, **duplicated**, or **improperly formatted data**. Here's why it's crucial:

- Clean data represents the information correctly, leading to **more accurate analysis and decision-making**;
- In some cases, ensuring data integrity is not just beneficial but **legally required**.

> **Note**
>
> The syntax of formulas may differ between various versions of Excel. In some cases, a `,` separator is used instead of a `;`.

# Task

Let's practice using these tools:
- Eliminate extra spaces in the **Category** column on the **Products** sheet.
- Replace **"FL"** with **"Florida"** in the **Location** column on the **Branches** sheet.
- Highlight the bottom 20% of sales in the **Total_Sale** column on the **Sales** sheet.

> **Note**
>
> To download all these sheets, refer to the <a 
href="https://codefinity.com/courses/v2/0328349f-0845-49dc-9814-060940bbcef3/54b8e6db-049f-4801-8e09-22d2dc1d4a98/49bf4ab4-0c72-412a-94f8-b9156f0639e2"
target="_blank"
style="color: #ff8a00; font-weight: 600; text-decoration: none; transition: 0.3s ease-in-out;"
onmouseover="this.style.color='#ff0000'"
onmouseout="this.style.color='#d27204'">first chapter</a> and import them from CSV files.

What is the simplest method to remove extra spaces in text data?

Data Analysis with Excel provides a practical guide to mastering the most essential data management, manipulation, and analysis techniques using Microsoft Excel. You'll gain proficiency in Excel's powerful capabilities, progressing through data analysis methods, and creating dynamic visualizations and interactive dashboards. By the end, you'll learn to automate reporting and apply advanced analytics, equipping you to make informed, data-driven decisions efficiently.

Learn how to import, clean, and transform data with advanced Excel functions to prepare datasets for in-depth analysis. Master techniques to navigate complex data with lookup functions.

Delve into the core of Excel's analytical power by mastering conditional analyses, statistical functions, and PivotTables. This section teaches you how to extract meaningful insights from large datasets using a variety of analytical tools.

Gain the skills to create statistical charts to build interactive dashboards that communicate data visually. Learn to automate repetitive tasks and generate reports efficiently, enhancing productivity and data interaction.

It covers correlation analysis to determine relationships between variables using Pearson’s correlation coefficient, linear regression to explore variable relationships, the addition of trendlines for pattern analysis in forecasting, and the use of t-tests and z-tests in hypothesis testing to evaluate statistical significance.

Data Analysis with Excel

Data Cleanup

Task