python notebook in HTML format.

Scoring guide (Rubric) - Foundations for Data Science Criteria Points Question 1 Find the summary statistics for numerical columns and observations. (use describe function) 4 Question 2 r observations on the acceptance rate for each campaign 4 Question 3 bservationYou need to a python notebook in HTML format. Happy Learning!

Scoring guide (Rubric) - Foundations for Data Science Criteria Points Question 1 Find the summary statistics for numerical columns and observations. (use describe function) 4 Question 2 observations on the acceptance rate for each campaign 4 Question 3 r observations on acceptance rate for each campaign according to the income level 7 Question 4 Write the code and your observations on average amount spent on different products across all campaigns 7You need to a python notebook in HTML format. Happy Learning!

Scoring guide (Rubric) - Foundations for Data Science Criteria Points Question 1 Find the summary statistics for numerical columns andr observations. (use describe function) 4 Question 2 observations on the acceptance rate for each campaign 4 Question 3 observations on acceptance rate for each campaign according to the income level 7 Question 4 Write the code and your observations on average amount spent on different products across all campaigns 7 Question 5 Write the code and your observations on average number of purchases from different channels across all campaigns 7 Question 6 Write the code and your observations on percentage acceptance for different categorical variables across all campaigns 7 Question 7 Write the code and your observations on the percentage amount spent on different products for each category of the mentioned categorical variables 7 Question 8 servations on percentage purchases from different channels for different categories of the income_cat column 4 Question 9 Find the correlation matrix for the columns mentioned below and visualize the same using heatmap 3 Question 10 Based on your analysis, write the conclusions and recommendations for the CMO to help make the next marketing campaign strategy 10 Question 5 Write the code and your observations on average number of purchases from different channels across all campaigns 7 Question 6 Write the code and your observations on percentage acceptance for different categorical variables across all campaigns 7 Question 7 Write the code and your observations on the percentage amount spent on different products for each category of the mentioned categorical variables 7 Question 8 servations on percentage purchases from different channels for different categories of the income_cat column 4 Question 9 Find the correlation matrix for the columns mentioned below and visualize the same using heatmap 3 Question 10 Based on your analysis, write the conclusions and recommendations for the CMO to help make the next marketing campaign strategy 10s on acceptance rate for each campaign according to the income level 7 Question 4 Write the code and your observations on average amount spent on different products across all campaigns 7 Question 5 Write the code and your observations on average number of purchases from different channels across all campaigns 7 Question 6 Write the code and your observations on percentage acceptance for different categorical variables across all campaigns 7 Question 7 Write the code and your observations on the percentage amount spent on different products for each category of the mentioned categorical variables 7 Question 8 servations on percentage purchases from different channels for different categories of the income_cat column 4 Question 9 Find the correlation matrix for the columns mentioned below and visualize the same using heatmap 3 Question 10 Based on your analysis, write the conclusions and recommendations for the CMO to help make the next marketing campaign strategy