Friday – October 27,2023

Today’s work involved the development of a Python script for the analysis of an Excel dataset. The primary objective was to count distinct words within specified columns of the dataset. The process commenced with the importation of essential libraries, such as Pandas for data manipulation and the Counter class for word frequency calculations. To make the analysis adaptable, a list was used to specify the columns to be analyzed, and the file path to the Excel document was provided. Subsequently, the data from the Excel file was loaded into a Pandas DataFrame for further processing. To keep track of word counts, an empty dictionary was initialized. The code then iterated through the specified columns, extracting and converting data into strings. The textual content within each column was tokenized into words, and the frequency of each word was meticulously counted and stored within the dictionary. The final step involved printing the word counts for each column, presenting the column name along with the unique words and their corresponding frequencies. This code serves as a versatile tool for text analysis within targeted columns of an Excel dataset, delivering a well-structured and comprehensive output for further analytical insights.