Data Wrangling and Data Cleaning Using Excel - Top Three Data Cleaning Tips using Excel

 

What Is Data Wrangling?

Errors are eliminated and complex data sets are combined in the process of "data wrangling," which makes the data easier to access and interpret. Large volumes of data must be stored and organized for analysis, since the amount of data and data sources available today grow at an accelerating rate.

Rearranging, converting, and mapping data from one "raw" form to another is called "data wrangling," often referred to as "data munging," and it is done to improve its usefulness and value for a range of downstream applications, such as analytics.

The process of organizing, sanitizing, and formatting unprocessed data into a format that analysts can utilize to make decisions quickly is known as data wrangling. Data wrangling, often referred to as data cleaning or data munging, helps organizations to handle more complex data faster, generate more precise findings, and make better decisions.

Importance of Data Wrangling

The following sums up the main benefit of employing data-wrangling tools:

1. Making useable the raw data. A precise wrangling process ensures that high-quality data is incorporated into the subsequent analysis. 

2. Transferring all the data to a single, usable location from different sources.

assembling raw data in the necessary manner and comprehending the data's business context

3. In order to clean up and transform source data into a format that is consistent and repeatable based on end requirements, automated data integration technologies are employed as data wrangling approaches. 4. Companies do critical cross-data set analytics using this standardized data. 

5. Purging the data of errors and missing or faulty components

6. Data wrangling is a step in the process that gets ready for data mining, which is collecting and organizing data. 

7. Assisting business users in making timely

Benefits of Data Wrangling

1. Data wrangling transforms data into a format that is compatible with the final system, which enhances data usability. 

2. It facilitates the rapid development of data flows within user-friendly interfaces and makes scheduling and automating the data-flow process simple.

3. Integrates data from a variety of sources, including files, databases, and web services.

4. Assist users in effortlessly processing vast amounts of data and exchanging data-flow strategies.

How to Clean Data in Excel?

1. Remove Duplicates

Eliminating duplicates from data in Excel is one of the simplest methods of data cleaning. It is highly likely that it will inadvertently make duplicate copies of the data without the user's awareness. In these kinds of situations, duplicate values can be removed.

Here, you need to select the columns you want to compare for duplication. Another critical step is to check in the headers' option as you included the column names in the data set. Excel will automatically scan it by default.

Next, you must compare all columns, so go ahead and check all the columns as shown below.

Select Ok, and Excel performs the operations required and provides you with the data set after filtering out the duplicate data, as shown below.

In the next part of Excel Data Cleaning, you will understand data parsing from text to column.

2. Data Parsing from Text to Column

A comma or another data delimiter may occasionally be used to separate multiple data elements in a single cell. For illustration, let's say that address information is stored in a single column.

The street, district, state, and country are stored in the address column. The data elements are separated by commas. The street, district, state, and country from the address columns must now be separated into their own columns.

Here, you have the car manufacturer and the car model name separated by space as the data delimiter. The tabular data is shown below.

Select the data, click on the data option in the toolbar and then select "Text to Column", as shown below.

A new window will pop up on the screen, as shown below. Select the delimiter option and click on "next". In the next window, you will see another dialogue box.

In the new page dialogue box, you will see an option to select the type of delimiter your data has. In this case, you need to select the "space" as a delimiter, as shown below.

In the last dialogue box, select the column data format as "General", and the next step should be to click on the finish, as shown in the following image.

The final resultant data will be available, as shown below.

Followed by Data parsing, in this tutorial about Excel Data Cleaning, you will learn how to delete all formatting.

3. Spell Check

The feature of checking the spelling is available in MS Excel as well. To check the spellings of the words used in the spreadsheet, you can use the following method. Select the data cell, column, or sheet where you want to perform the spell check.

Now, go to the review option as shown below.

Microsoft Excel will automatically show the correct spelling in the dialogue box, as shown below. You can replace the words as per the requirement as shown below.

The final reviewed data table will like the one below.

In the next segment of this Excel Data Cleaning tutorial, you will learn about changing the text case.