Pandas (2.3.1) A-Z | 02B

🚀 Course: Pandas (2.3.1) A-Z
🔁 Module 02: Data Cleaning
🧠 Lecture B: Cleaning Columns

👇 Link to the notebook:
https://tinyurl.com/2b4cm387

🚀 Pandas data cleaning tutorial for handling missing values and cleaning columns in DataFrames with Pandas 2.3.1 so your analysis stays accurate and reliable. Learn practical Python data cleaning techniques: detecting and standardizing missing data, choosing between dropna, fillna, and interpolation for time series, and using linear and time-based interpolation on temperature readings. See how to trim and lowercase text, fix whitespace and symbols, standardize categorical labels, and convert messy columns to numeric, datetime, and efficient categorical dtypes while avoiding conversion errors and parsing issues. Watch to strengthen your data preprocessing skills and prepare for more advanced data transformation.

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