Study Pandas With Me

Study Pandas With Me | Day 02 of Daily ML Day 02 of my Daily ML series. In this session, I covered the important fundamentals and commonly used Pandas functions needed for data analysis and machine learning. Topics covered: What is Pandas? Series and DataFrame Why Pandas is used Advantages and disadvantages Creating DataFrames and Series Loading CSV, Excel, and JSON data Understanding data with `head()`, `tail()`, `shape`, `info()`, `describe()`, and `columns` Selecting data using `[]`, `loc[]`, and `iloc[]` Data cleaning with `isnull()`, `dropna()`, `fillna()`, `drop_duplicates()`, and `rename()` Data manipulation with `sort_values()`, `groupby()`, `merge()`, `concat()`, `apply()`, and `value_counts()` Saving data using `to_csv()`, `to_excel()`, and `to_json()` This is part of my Daily ML journey, where I am building my foundations step by step from Python libraries and data analysis toward Machine Learning, Deep Learning, Transformers, LLMs, Agentic AI, and MLOps. Study along with me and build your ML foundations one day at a time. #DailyML #Pandas #Python #MachineLearning #DataScience #StudyWithMe #AI #DataAnalysis #PythonProgramming