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Data Cleanup | Data Management and Manipulation
Data Analysis with Excel
course content

Conteúdo do Curso

Data Analysis with Excel

Data Analysis with Excel

1. Data Management and Manipulation
2. Basic Data Analysis
3. Data Visualization and Automation
4. Advanced Data Analytics Techniques

bookData Cleanup

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 first chapter and import them from CSV files.

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

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

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Seção 1. Capítulo 2
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