The new research based on idea of "crm implementation consultant" query and some Fiverr data scrapping.
Data Preprocessing: Clean the data, handle missing values, and format columns as needed. Extract relevant information such as name, level, rating, price, etc.
Answer Pain Questions: Identify potential pain questions that both buyers and sellers might have on Fiverr. These could include questions about services, pricing, expertise, etc. You can formulate these questions based on the data you have, and then answer them using the information from the dataset.
Data Analysis and Correlation: Calculate statistical measures such as mean, median, and standard deviation for different variables like ratings, number of orders, and prices. Use these statistics to identify correlations between variables like price and level, number of orders and stars, etc.
Visualization: Create visualizations to represent the correlations you've identified. You can use libraries like Matplotlib or Seaborn to create bar charts, scatter plots, or any other visualization that helps convey your findings effectively.
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