Paypal Interview Questions (13+ Questions)

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SELECT
id,
REPLACE(text, 'Python', 'PySpark') AS text,
date,
likes,
comments,
shares,
platform
FROM {{ ref("social_media") }}

WITH sales_agg AS (
SELECT
product_id,
SUM(quantity) AS total_quantity,
SUM(revenue) AS total_revenue
FROM {{ ref("sales") }}
GROUP BY product_id
),
inventory_agg AS (
SELECT
product_id,
SUM(stock) AS total_stock
FROM {{ ref("inventory") }}
GROUP BY product_id
)
SELECT
p.product_id,
p.name,
p.category,
COALESCE(s.total_quantity, 0) AS total_quantity,
COALESCE(s.total_revenue, 0) AS total_revenue,
COALESCE(i.total_stock, 0) AS total_stock
FROM {{ ref("products") }} p
LEFT JOIN sales_agg s
ON p.product_id = s.product_id
LEFT JOIN inventory_agg i
ON p.product_id = i.product_id

Introduction

Mastering SQL queries is a vital skill for data professionals, and understanding how to extract meaningful insights from relational databases is a common topic in interviews. Below, we will explore an example of how to write an SQL query to determine the average order value for each...

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SELECT
account_id,
SUM(
CASE
WHEN transaction_type = 'deposit' THEN amount
WHEN transaction_type = 'withdrawal' THEN - amount
ELSE 0
END
) AS final_balance
FROM
transactions
GROUP BY
account_id
ORDER BY
account_id ASC;

def permute(nums: list[int]) -> list[list[int]]:
res = []

def dfs(current_perm):
    if len(current_perm) == len(nums):
        res.append(current_perm.copy())
        return
        
    for num in nums:
        if num in current_perm:
            continue
            
        current_perm.append(num)
        dfs(current_perm)
        current_perm.pop()
        
dfs([])
return res

def insert(intervals: list[list[int]], new_interval: list[int]) -> list[list[int]]:
res = []

for i in range(len(intervals)):
    if new_interval[1] < intervals[i][0]:
        res.append(new_interval)
        return res + intervals[i:]
    elif new_interval[0] > intervals[i][1]:
        res.append(intervals[i])
    else:
        new_interval = [
            min(new_interval[0], intervals[i][0]),
            max(new_interval[1], intervals[i][1])
        ]
        
res.append(new_interval)
return res

Objective

To solve the given SQL interview question, you need to write a query that calculates and ranks the profit margin percentages for each product. A profit margin percentage is calculated as ((selling_price - cost_price) / cost_price) * 100. The SQL query should retrieve the product name...

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