Define what a row means before querying
Begin by defining a specific research question rather than collecting records because they are available. For example: what explanations of sampling appear in the AskStatistics records returned by a specified query? This is an exploratory question about retrieved text. It does not ask how many Reddit users hold an opinion or whether the returned authors represent a wider population.
Choose one unit for the first table: one received source record per row. Decide which available fields you need to inspect, such as id, kind, subreddit, created_utc and text or title. Preserve a missing field as missing rather than substituting an invented timestamp or author. A second table can hold your coding labels, with a local reference back to the source row.
Get Reddit Data is an independent historical archive, not official Reddit or a live feed. It does not guarantee coverage periods, immutable results or a fixed schema. Your question and exclusion rules make your own reasoning inspectable, but cannot make a later remote retrieval identical. Save the actual received material if you need to rerun a local transformation.
Run a bounded search and inspect the response
Start with https://api.getredditdata.com/v1/search?q=sampling&subreddit=AskStatistics&limit=3, the homepage example. Authenticate server-side with X-API-Key: <key> or Authorization: Bearer <key>. q performs text search; subreddit specifies the community and limit caps the page. Search can return posts and comments unless kind restricts it to post or comment. No record or community coverage is guaranteed.
For a date-defined question, from and to use YYYY-MM-DD UTC and apply to created_utc, with the final day fully included. They do not filter ingestion time or accept hours. Add min_score only when the numeric threshold belongs in your selection rule. A higher score does not verify expertise, correctness or representativeness and can exclude low-scoring but relevant material.
Validate the HTTP result and data array before adding rows. Keep the parameters and actual response alongside your local extraction notes. Internal _doc order is not time, relevance or score order. limit and page each range from 1 to 100, with a separate call per page. A smaller window can organize collection without proving full coverage or an absence of duplicates.
Audit the table and explain what it can support
Read pagination.total with relation: eq means an exact query total, gte a lower bound and unknown no reliable total, possibly null. A zero on an empty first page concerns that query, while an empty deeper page can have an unknown total. Do not use either outcome as a population estimate. Preserve has_more and window_exhausted when recording the boundaries encountered.
Group flat records by present parent_id or link_id only when useful to your own analysis. Those fields are not search filters and do not ensure complete discussions or ancestry. Review duplicate identifiers locally and document exclusions; neither deduplication nor sorting recovers missing records. Separate your interpretation from the original text and state the limits of any comparison across communities or periods.
Budget one credit for every successful request, including empty pages and successful repeats. Invalid requests do not debit and upstream failures refund reservations; a client timeout may conceal a billed success. Handle 400 by fixing parameters, 401 by checking key and domain, 402 by checking balance and 429 with bounded delayed retries. Local parsing failure does not undo a charged retrieval.
The documentation explains routes and totals; pricing gives $1 per 1000 successful requests and a $50 minimum for 50000 paid credits. The Get API key page explains signup before payment and conditional trial eligibility. Your analysis runs locally: the API supplies archived records, not a finished statistical report, sentiment service or certification that your resulting table is unbiased.
