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Create OHLC Aggregates from Tick Data in Python

RobinhoodData Scientist · Onsite
MediumData ScientistOnsiteData Manipulation (SQL/Python)

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This question evaluates a candidate's ability to perform time-series bucketing and OHLC aggregation from tick data, testing skills in data parsing, stateful aggregation, and handling missing-interval forward-filling; it falls under Data Manipulation (SQL/Python) and assesses practical application rather than purely conceptual understanding.

price_stream

+-----------+-------+ | timestamp | price | +-----------+-------+ | 0 | 3 | | 1 | 2 | | 2 | 4 | | 3 | 10 | | 8 | 11 | +-----------+-------+

Scenario

Streaming trading application receives tick data as "price:timestamp" pairs. You must generate 10-second OHLC aggregates and forward-fill gaps.

Question

Write a Python function that

parses an input string like "3:0,2:1,4:2,10:3,10:4,10:5,10:6,10:7,10:8,10:9,10:10,11:8";

buckets rows into [0- 10), [10- 20)… intervals by timestamp;

for every interval outputs first_price, last_price, min_price, max_price;

if an interval has no rows, copy the previous interval’s last_price into every statistic for the missing bucket.

Hints

Use floor(timestamp/ 10) to find a bucket, keep running dict {bucket: [first,last,min,max]}, track last seen price for forward-fill.