Today’s tasks revolved around creating a Python script to analyze an Excel dataset. The main goal was to determine the number of distinct words in specific columns of the dataset. The process began with importing necessary libraries, like Pandas for data manipulation and the Counter class for word frequency calculations. To make the analysis flexible, a list was employed to identify the columns to be examined, and the file path to the Excel document was specified. Subsequently, the data from the Excel file was loaded into a Pandas DataFrame for further handling. To keep track of word counts, an empty dictionary was initialized. The code then looped through the designated columns, extracting and converting data into text strings. The text within each column was broken down into individual words, and the frequency of each word was carefully tallied and saved in the dictionary. The final step involved displaying the word counts for each column, presenting the column name alongside the unique words and their respective frequencies. This script functions as a versatile tool for text analysis in targeted columns of an Excel dataset, producing a well-organized and comprehensive output for deeper analytical insights.