The task for today was to write a Python script that would analyze an Excel dataset. Counting unique words inside designated dataset columns was the main goal. The procedure started with the import of necessary libraries, like the Counter class for word frequency computations and Pandas for data manipulation. The file path of the Excel document was supplied, and a list was used to designate the columns to be examined in order to make the analysis flexible. After that, a Pandas DataFrame was loaded with the data from the Excel file for additional processing. Word counts were tracked by initializing an empty dictionary. After that, the code extracted and converted the data into strings by looping over the designated columns.
Each column’s text was tokenized into words, and each word’s frequency was carefully tallied and entered into the dictionary. Printing the word counts for each column and displaying the column name, unique words, and matching frequencies was the last stage. This code is a flexible tool for text analysis in certain Excel dataset columns. It produces an organized and detailed output that can be used to get additional analytical insights.