My first excel data cleaning

My introduction to data analysis and science curriculum included learning Microsoft Excel, a software program developed by Microsoft for data collection, organization, analysis, calculation, and visualization. Upon opening Excel, the interface consists of various tools organized into a ribbon containing tabs like Home, Insert, Page Layout, Formulas, Charts, and Data. At the top is the Quick access toolbar with icons for Save, Undo, and Redo.

Cells, formed at the intersection of rows and columns, are the basic units of the grid. Understanding the fundamental components of Excel, I proceeded to clean a dirty dataset. Data cleaning involves sorting, filtering, number formatting, and conditional formatting.

Sorting arranges data in a specific order, either alphabetically (text), numerically (largest to smallest or vice versa), or chronologically (oldest to newest or vice versa). Filtering allows you to display data meeting certain criteria while temporarily hiding the rest. Number formatting changes the display of numbers without altering their actual values. Conditional formatting highlights cells based on rules or criteria, aiding in spotting trends or outliers.

The dataset contained numerous duplicates, necessitating the removal of these duplicates. Text functions are particularly useful in cleaning data. UPPER() converts text to uppercase, LOWER() converts it to lowercase, PROPER() capitalizes the first letter of each word, TRIM() removes extra spaces, LEFT() extracts the leftmost characters, RIGHT() extracts the rightmost characters, MID() extracts characters from the middle, LEN() returns the length of text, and FIND() determines the position of a substring.

Although I had only begun my journey with Excel on my first week, I found data cleaning to be an engaging process and was eager to learn more.