Just wrapped up my Pandas journey in Python! 🐼✨ Explored: Series & DataFrames, indexing, cleaning, analysis, transformations & real-world use. Love how Pandas turns raw data → insights in just a few lines. Ready to apply it in DS/ML projects! 🚀

Day 29/30 of #30DaysofCode Started pandas today! Learnt about Series and DataFrames and the various functions used in pandas. Learnt how to create a CSV file in jupyter notebook and how to access a CSV file on it. #Python #Pandas #CodeNewbie #JupyterNotebook #100DaysOfCode

💡 Just learned how to fetch data from MySQL into Pandas using Python! Now I can run SQL queries and instantly analyze results in DataFrames 📊🐍 Game changer for data analysis 🚀 #Python #SQL #DataScience #LearningInPublic

Can TensorFlow read my mind and load the dataframes itself? Source: https://t.co/ohwxbkqIu7 #AIResearch #BigData #Innovation #100DaysOfCode #list #dataframe

Day 13 of #100DaysOfCode 🚀 Today I 📌 Explored Python dictionaries 📌 Learned NumPy, Pandas & Seaborn 📌 Created DataFrames & Series for handling structured data Thanks to @whyankush07 Scratch to Stack YT for making it super clear 🙌 #Python #MachineLearning #DataScience

Skrub: machine-learning with dataframes Presentation at @pydatalondon, discussing how skrub facilitates data transformations and wrangling on dataframes for machine learning and introducing the exciting "DataOps" to tune and re-apply any wrangling code

6 month complete strategy to transition to Data Engineering 𝐰𝐞𝐞𝐤 1-3 (𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧𝐬) - Distributed Fundamentals - Linux basics 𝐰𝐞𝐞𝐤 4-9 (𝐀𝐩𝐚𝐜𝐡𝐞 𝐒𝐩𝐚𝐫𝐤) - RDD overview - Dataframes in Depth - Spark SQL 𝐰𝐞𝐞𝐤 10-11 (𝐒𝐩𝐚𝐫𝐤 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞

10. Data Analysis with Python • Write Python programs to clean and prepare data • Use EDA with Pandas, NumPy, and SciPy to find insights • Apply data operations with dataframes for analysis • Build and evaluate regression models with Scikit-learn for predictions

fenic Build reliable AI and agentic applications with DataFrames. https://t.co/TNqae8W5u5

Slides are here, with demo code: https://t.co/WvS6bXT9Oj

ماذا يلزم لتحليل بياناتك باستخدام بايثون : 1️⃣ معالجة البيانات (Data Processing & Manipulation) NumPy → للتعامل مع الأرقام والمصفوفات بسرعة وفعالية pandas → للتعامل مع الجداول (DataFrames)، يعني كأنك تتعاملين مع ملف Excel داخل بايثون. مثال: قراءة ملف CSV وعرض أول 5 صفوف من

"Pandas DataFrames" by Keith Galli Learn how to create and manipulate Pandas DataFrames, including merging and joining data, handling missing data, and filtering data. https://t.co/OkPy7bFvXd

@mteusecv Ex. Pelo q vc falou ali parece ser o Pandas, ne? Doc da funcao fillna dos dataframes. Ai vai ter tudo q ela faz, os parâmetros que recebe, etc.

Time series + pandas DataFrames = a smoother workflow. 🛠️ Explore how to integrate pandas with #InfluxDB, simplify your data analysis. ↴

Latest post is up! I spoke with @hussainsultan, CEO of Xorq, about DataFrame libraries, the split between single-node and mulit-node execution, and how Xorq solves this. https://t.co/0B1bLPh4OS

@kevinwhinnery @djangocon ‘…sir where are you going? I thought you wanted to talk about dataframes!!!’