Based on the content provided by the CSV data loaded, here are a couple of potential issues identified according to the hint regarding unusual data entries:

### Issue 1

**issue**: "Actual price listed as percentage instead of currency value"

**evidence**: "discounted_price" and "actual_price" columns contain values such as "₹399" for discounted_price and "₹1,099" for actual_price which are correct, but the discount_percentage column for all rows contains percentages (e.g., "64%"), which might be misinterpreted as actual values in the context of price columns.

**description**: "The dataset tends to list prices in currency values; however, the 'discount_percentage' column uses percentages, increasing uniformity and potentially leading to confusion when analyzing the data for pricing trends. It would be expected that all pricing-related information follow a consistent format (e.g., all in currency format or all in percentage format concerning base values)."

### Issue 2

**issue**: "Unstructured user reviews in a single entry"

**evidence**: "user_id", "user_name", "review_id", "review_title" and "review_content" columns concatenate multiple values within single cells, separated by commas, which disrupts the data structure and complicates analysis.

**description**: "Data entries in columns related to user reviews (like 'user_id', 'user_name', 'review_id', 'review_title', and 'review_content') are concatenated into single cell entries, representing what should be multiple distinct records. This unusual data entry practice deviates from a normalized relational data format, necessitating preprocessing steps to separate these values for most types of analysis. A more standard approach would involve structuring the data such that each review occupies a single row with its user ID, name, review ID, title, and content distinctly separated."

### Issue 3

**issue**: "Suspiciously high discount percentage"

**evidence**: "discounted_price" = "₹199", "actual_price" = "₹1,899" with "discount_percentage" = "90%"

**description**: "One of the products listed is showing a discount percentage of 90%, which is unusually high and could potentially be an error or misleading. This extreme discount rate might raise questions regarding the accuracy of the 'actual_price' or 'discounted_price' values, or it could be a legitimate outlier that should be verified for accuracy."


These issues highlight unusual data entries that could affect the reliability of the dataset for analysis or lead to incorrect interpretations if not addressed or considered during dataset pre-processing.