Methods: Briefly describe how you cleaned and analyzed the data, including any tools or techniques used. Mention the criteria for selecting insights and visualizations. - does the following text follow this format - Initial dataset was examined for cleaning and formatting. During the cleaning process, the non-numerical characters in "volume sales" column are removed and they are converted to the equivalent numeric sales. Also, there is creation of a "sales millions" column to summarize the sales in the form of millions so that the numeric data is easy to read and interpret. Various text fields are stripped and standardized and field "title" is eliminated from dataset as it is not relevant to the research question. Author names are flipped so that they can presented as first name and last name. Genre labels are normalized and less-common genres are marked as "others" bucket. Further, dataset is checked for duplicates in title and author. However, no such duplicate is identified. For data cleaning and analysis, Tableau is used as it effectively illustrates proportional shares, categorical comparison, and relationship across rank of the book and associated sales