Tareef Kawaf’s Post

Hello Everyone! This project is the outcome of my dedication throughout the Data Analyst bootcamp at MySkill. It highlights my journey of becoming proficient in SQL, Python, and Data Visualization. By utilizing a simulated e-commerce dataset and case study provided by MySkill to tackle real-world scenarios, I gained hands-on experience that made my learning practical and insightful. Content: 1. PostgreSQL (Slide 9) 2. Python (Slide 25) 3. Data Visualization (Slide 49)

Get started with Pandas 🐼 Hey everyone! I'm thrilled to share a handy cheatsheet by Favio Vazquez that helped me kickstart my work with Pandas in Python. Whether you're a beginner looking to get your feet wet or an experienced developer aiming to polish your data manipulation skills, this cheatsheet is a game-changer. Here's what you'll find: - Essential commands for data wrangling - Tricks for efficient data filtering and sorting - Nifty function calling Pandas is a cornerstone for data analysis in Python, and mastering it can significantly boost your productivity and analytical capabilities. I encourage you to download the cheatsheet and see how it can help streamline your projects! Feel free to share your thoughts or ask questions in the comments below. Let's dive into data with more confidence and expertise! https://lnkd.in/dgv_xaHs

Progress Update! I’m halfway through the Data Analysis with Python course on freeCodeCamp by Santiago Basulto. 🎉 Completed 17 out of 28 challenges, covering: - Data Analysis basics - Jupyter Notebooks - Numpy and Pandas essentials Learning to read data (CSV, SQL, Excel), process it with NumPy and Pandas, and visualize using Matplotlib and Seaborn. Excited to keep progressing! #DataAnalysis #Python #LearningJourney #freeCodeCamp #DataScience #SelfStudy

“Excited to announce that I have successfully completed the analytics with SQL and Python course! This course has helped me gain a deeper understanding of data analysis and visualization, as well as the ability to write foundational SQL statements like SELECT, INSERT, UPDATE, and DELETE. I also learned how to filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses, I am now confident in my ability to work with advanced concepts like Stored Procedures, Views, Inner & Outer JOINs, and query data from multiple tables. I am also familiar with the Pandas,Matplotlib and NumPy libraries in Python, which are essential tools for data manipulation, analysis, and visualization. I am excited to apply these skills to real-world problems and make a meaningful impact in the field of data science!”

Hello, Everyone! ✨ I'm excited to present my third portfolio, which marks the beginning of Python Part 3. This portfolio has been a collaborative effort from Nirmala Fauzhia, Ahmad Novan Alfian, and Moch Isna Ardian Cahyana. I would like to express my gratitude in advance to Suwarti Suwarti ✅ and MyEduSolve for their support. In this Part 3 portfolio, we delve into various fundamental Python concepts, including: 1. Numpy - Import Numpy - Checking Numpy Version - Creating a Numpy Array - Use a Tuple to Create a Numpy Array - Dimensions in Array (0 Dimensions Array, 1 Dimensions Array, 2 Dimensions Array Containing 2 Array, 3 Dimensions Array With 2 Dimensions Array, Both Containing Two Array, 5 Dimension Array and Verify That Has 5 Dimensions) - Check How Many Dimensions The Array Have - Get The One Element From The Following Array - Get The Third and Fourth Element From The Following Array and Add Then - Access The Element On The First Row, Second Column  - Access The Element on The 2nd, 5th Column - Access The Third Element Of The Second Array Of The First Array 2. Pandas 2.1 Object Series - Convert Data Into Series From - Convert From Series to Array - Displays Index From Series  - How to Call Data From Series - Implicit Index - Explicit Index 2.2 Loc and Iloc - Create Series From Series With Loc and Iloc 2.3 Data Frame   2.4 Titanic CSV  - Load Data Titanic  - Displays Data From Head - Displays Info Data - Displays The Number of Rows and The Number of Columns - Displays Data From Columns - Displays Data From Index - Displays Information From Columns in The From of Number - Displays The Sum Of Not Null From Head - Displays The Sum Is Null From Head - Displays The Amount From Head - Displays The Mean of Columns - Displays The Median of Columns - Displays The Modus of Columns - Displays The Minimal of Columns - Displays The Maximal of Columns 2.5 Mini Project Preparation You can access the portfolio via the attached comment, where I've provided a GitHub link for your convenience. Please feel free to review and save it. We would greatly appreciate it if you could share it with others, as we hope it proves beneficial to all. Looking forward to the next portfolio. Thank you for your support! #MyEduSolve #Python #JupyterNotebook #Anaconda #DataAnalyst #Coding #MSIBBatch5

I'm reeeeeally enjoying Alex Freberg's Analyst Builder platform, learning lots of new concepts even on the "easy" questions and translating questions into code. It's free to sign up, has a very helpful Discord community, courses ranging from Excel, to MySQL and Python. I hadn't heard of a Cross Join before, seems powerful (especially to make sandwiches 😅) If you're breaking into data analysis and further, check it out! #dataanalysis #dataanalytics #dataanalysisskills #datacareer

I'm happy that I have completed my third project at OESON! I had been learning the various Python libraries over the past few months in order to assess commodities and give investor insights. My practical Python expertise has increased as a result of this project, and I've been able to use new abilities for a variety of tasks. With special thanks to Tanishq Chouhan and Aritri Debnath (Ghosh) for the guidance and support. #Oeson #DataAnalyst #Analytics #Statistics #DataSciencentist

🎉 I am excited to share the completion of my latest project at Mentorness! 🚀 I just wrapped up an in-depth COVID-19 analysis report, leveraging PostgreSQL 16 for SQL analysis and Python for date format conversion. 📊💻 Throughout this project, SQL proved invaluable for extracting and manipulating data efficiently, while Python came in handy for fine-tuning date formats to ensure accuracy in our analysis. Here are some highlights: - Leveraged PostgreSQL 16 for robust SQL analysis, uncovering key insights. - Utilized Python for seamless date format conversions, ensuring data accuracy. - Uncovered critical patterns and trends to inform decision-making processes. I'm proud of the valuable insights generated from this analysis, and I'm eager to apply these learnings to future projects. 💡 Check out the presentation slides for a glimpse into the findings #DataAnalysis #PostgreSQL #Python #COVID19Analysis #Mentorness #DataScience #DataVisualization

Hello, Namaste connections👋, today is the sixth day of my learning ,where I learned the Python and SQL. It was the very excited and enjoyable learning throughout the lecture. Thank you so much Krish Naik Sir and Chandoo Sir for such incredible content. Stay connected for further updates and looking to learn something more from next videos. #day6 #25dayschallenge #consistent #dataanalyst #krishnaiksir Today's learning day 6/25 Topic covered: 1. Advanced Python - Class Variables and Methods 2. Learn SQL for Data Analysis (Chandoo) . . . . #challenge #problemsolving #25dayschallenge #analysis #day6 #completed #consistency #dataanalysis #learningeveryday #Krishnaiksir #challengeaccepted 

Hello everyone, I have finished the 4 hours course ''Writing Efficient Python Code" on DataCamp as part of my DI501 - Data Informatics course. I've practiced different approaches and comparing them by using %timeit, code profiling methods(%lprun, %mprun). Moreover, I have learned how to use Numpy and pandas methods and objects to eliminate loops, increase efficiency of the script. I'm eager to apply these skills in real-world projects. Every small win is a big deal!