Analyze Slack Data with Apache Spark

🐍📈 Data Science With Python Core Skills — In this learning path you'll cover a range of core skills that any Python data scientist worth their salt should know #python #learnpython

Today I explored one of the most powerful data structures in Python – Dictionaries 🐍 📌 Key Takeaways: 🔹 Dictionaries store data in key-value pairs 🔹 Keys are unique, but values can be duplicated 🔹 Easy data access using keys 🔹 Efficient for storing structured data 💡 Important Operations Covered: ✔️ Creating dictionaries using {} and dict() ✔️ Accessing values using keys and .get() ✔️ Removing elements using del, .pop(), .clear() ✔️ Understanding dictionary length using len() ✔️ Using .popitem() to remove the last inserted item 📊 Dictionaries are widely used in real-world applications like: ➡️ JSON data handling ➡️ APIs ➡️ Database-like structures Learning dictionaries strengthens the foundation for real-world Python development 💻 🔥 Consistency is the key — one step closer to mastering Python! Global Quest Technologies ✨ #GlobalQuestTechnologies #GQT #Python #PythonProgramming #100DaysOfCode #CodingJourney #LearnPython #DataStructures #Programming #Developer #CodingLife #TechLearning #SoftwareDevelopment #PythonBasics #CareerGrowth

Pandas is a popular Python library used for data manipulation and analysis. It is especially useful for working with structured data like tables.

Starting small end-to-end projects  🚀 Revisiting basics with a small dataset to strengthen my foundation using SQL, Python, and Power BI 📊 Learning by doing 💡 #KaliyonaSQL #KaliyonaDataAnalytics #KaliyonaWithGayathriBhat

Python Learning Journey Today I explored some core fundamentals that build a strong foundation in Python development: ◆ Installed VS Code and set up the Python environment ◆ Learned about different Python flavors: CPython (default implementation) Jython (Java integration) IronPython (.NET framework) PyPy (fast execution with JIT) Anaconda Python (data science ecosystem) RubyPython (experimental) ◆ Understood Python versions and compatibility ◆ Compared Java vs Python with real examples ◆ Practiced basic syntax like printing messages using print() Key concepts covered: Identifiers in Python Data Types & their types (int, float, list, tuple, dict, etc.) Typecasting Operators in Python eval() function Conditional statements (if, else, elif) Range data type and its variants Every day is a step closer to mastering Python. Consistency is the key! #Globalquesttechnologies #G R Narendra Reddy #Python #Coding Journey #Learning Python #VSCode #Programming #Developer #100DaysOfCode #TechSkills

Predict loan defaults with Machine Learning using Apache Spark! 💸📊 Guide: https://lnkd.in/d7_BciSV #MachineLearning #DataScience #BigData #ApacheSpark #AI #DataAnalytics #Python #Programming #100DaysOfCode

Predict life expectancy with Machine Learning using Apache Spark! 🩺📊 Guide: https://lnkd.in/dEMRMyhP #MachineLearning #DataScience #BigData #ApacheSpark #AI #DataAnalytics #Python #Programming #100DaysOfCode

Unlock the full potential of Python for data analysis and visualization with USDSI’s comprehensive guide. Learn workflows, libraries, and best practices to turn raw data into actionable insights. Download the Guide today: https://lnkd.in/emPkRFGH #DataScience #Python #Analytics #Visualization #PythonForDataScience #DataAnalytics #DataVisualization #LearnPython #DataScienceTools #BigDataAnalytics #DataDriven #AnalyticsSkills #DataInsights #TechSkills #CareerInData #DataScienceLearning #USDSICertification #USDSI

DB Administration in SQL through a Python package. Building out one piece of a larger data pipeline—establishing local database connections, creating structured tables, inserting records, and querying live data directly from Python. This is where application logic meets data infrastructure, turning code into systems that store, validate, and move real information. More to come as the system continues to expand. #fscj #aiprogram #python #ai #data