Let us build a complete project using NumPy (without any help).
Path: project_data = 'KAG_Conversion_Data.csv' Features:
- ad_id: unique ID for each ad
- xyzcampaignid: an ID associated with each ad campaign of XYZ company
- fbcampaignid: an ID associated with how Facebook tracks each campaign
- age: age of the person to whom the ad is shown
- gender: gender of the person to whom the add is shown
- interest: a code specifying the category to which the person’s interest belongs (interests are as mentioned in the person’s Facebook public profile)
- Impressions: the number of times the ad was shown
- Clicks: number of clicks on for that ad
- Spent: Amount paid by company xyz to Facebook, to show that ad
- Total conversion: Total number of people who enquired about the product after seeing the ad
- Approved conversion: Total number of people who bought the product after seeing the ad
Instructions: 1.Load the data. Data is already given to you in variable path
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How many unique ad campaigns (xyzcampaignid) does this data contain ? And for how many times was each campaign run ?
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What are the age groups that were targeted through these ad campaigns?
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What was the average, minimum and maximum amount spent on the ads?
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What is the id of the ad having the maximum number of clicks ?
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How many people bought the product after seeing the ad with most clicks? Is that the maximum number of purchases in this dataset?
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So the ad with the most clicks didn't fetch the maximum number of purchases. Find the details of the product having maximum number of purchases