Steps for data exploration

Performing data exploration helps us understand the dataset and its characteristics. It involves examining the data, identifying patterns, and summarizing key insights. Here are the steps we will follow:

1. Load the dataset: Read the dataset into a pandas DataFrame to work with the data effectively.
2. Inspect the data: Display the first few rows of the DataFrame to get a glimpse of the data. Check the column names, data types, and any missing values.
3. Summary statistics: Calculate summary statistics such as the mean, median, minimum, maximum, and quartiles for numeric columns. This helps in understanding the distribution and range of values.
4. Explore categorical variables: Analyze the unique values and their frequencies for categorical variables like marketplace, product_category, and sentiment. Visualizations such as bar plots can be helpful for this analysis.
5. Distribution of ratings: Plot a histogram or bar plot to visualize...