Instacart Interview Questions (4+ Questions)

def find_cheapest_price(n: int, flights: list[list[int]], src: int, dst: int, k: int) -> int:
prices = [float("inf")] * n
prices[src] = 0

for i in range(k + 1):
    temp_prices = prices.copy()
    
    for u, v, w in flights:
        if prices[u] != float("inf") and prices[u] + w < temp_prices[v]:
            temp_prices[v] = prices[u] + w
            
    prices = temp_prices
    
return prices[dst] if prices[dst] != float("inf") else -1

When preparing for a technical interview, you may encounter questions that test your ability to manipulate and query databases using SQL. One such common question is:

Objective

Retrieve all email addresses that appear more than once in the Customers table. The result should list each duplica...

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We will need to decompose time series data into trend, seasonal, and residual components. We will be working mainly with Pandas. Pandas is a library that was specifically designed for data analysis and manipulation. We are given only one CSV file that is called Temperature Data. It contains daily statistics over multiple years. First one is trend, which is a long-term direction of the data that indicates whether temperature generally increases over the years or not. Seasonal is responsible for repeating pattern that happens on a regular cycle. Residual is everything that is left after removing the trend and seasonal components, which is mostly some unpredictable day-to-day variations. Each component should be saved into its own CSV file. We were required to use Statsmodels, which is a Python library for statistical analysis. We import this specific function, which is called seasonal decompose, that will perform our decomposition. Then we specify the model by setting it to additive. We define one full cycle as 365 days because this is an annual pattern for temperature.

SELECT
CASE
WHEN order_id % 2 != 0
AND order_id = (
SELECT
MAX(order_id)
FROM
orders
) THEN order_id
WHEN order_id % 2 != 0 THEN order_id + 1
ELSE order_id - 1
END AS corrected_order_id,
item
FROM
orders
ORDER BY
corrected_order_id;