Coding Interview Resources

HTTP status codes — quick cheat sheet ✅ 200 OK: request succeeded 🆕 201 Created: new resource saved 📝 204 No Content: success, nothing to return 🔀 301 Moved Permanently: use new URL ↪️ 302 Found: temporary redirect 🧾 304 Not Modified: use cached version 🙅 400 Bad Request: invalid input 🪪 401 Unauthorized: missing/invalid auth 🚫 403 Forbidden: authenticated but not allowed ❓ 404 Not Found: resource doesn’t exist ⏳ 408 Request Timeout: client took too long 🧯 409 Conflict: state/version clash 💥 500 Internal Server Error: server crashed 🛠️ 502 Bad Gateway: upstream failed 🕸️ 503 Service Unavailable: overloaded/maintenance ⌛ 504 Gateway Timeout: upstream too slow tips • return precise codes; don’t default to 200/500 • include a machine-readable error body (code, message, details) • never leak stack traces in production • pair 304 with ETag/If-None-Match for caching

If-else in Python 👆

Data Structures Cheatsheet 👆

Data Analytics Pattern Identification....;; Trend Analysis: Examining data over time to identify upward or downward trends. Seasonal Patterns: Identifying recurring patterns or trends based on seasons or specific time periods Correlation: Understanding relationships between variables and how changes in one may affect another. Outlier Detection: Identifying data points that deviate significantly from the overall pattern. Clustering: Grouping similar data points together to find natural patterns within the data. Classification: Categorizing data into predefined classes or groups based on certain features. Regression Analysis: Predicting a dependent variable based on the values of independent variables. Frequency Distribution: Analyzing the distribution of values within a dataset. Pattern Recognition: Identifying recurring structures or shapes within the data. Text Analysis: Extracting insights from unstructured text data through techniques like sentiment analysis or topic modeling. These patterns help organizations make informed decisions, optimize processes, and gain a deeper understanding of their data.

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