Module 2: Pandas - data manipulation
Pandas is a popular open-source Python library widely used for data manipulation and analysis. It provides data structures and functions that allow users to work with structured data effortlessly. Pandas is particularly useful for handling tabular data like spreadsheets, SQL tables, and CSV files, making it a powerful tool for data cleaning, transformation, and exploration.
The two primary data structures in Pandas are the Series and DataFrame. A Series is a one-dimensional labeled array that can hold various data types, while a DataFrame is a two-dimensional labeled data structure resembling a table, with rows and columns.
Data manipulation with Pandas is a crucial aspect of data analysis and data science in Python. Pandas is a powerful library that provides easy-to-use data structures and functions for efficient data manipulation and analysis. Some key aspects of data manipulation with Pandas include:
🔸DataFrame and Series
🔸Data Loading and Inspection
🔸Data Selection and Filtering
🔸Data Cleaning and Preprocessing
🔸Data Transformation
🔸Data Visualization
🔸Handling Time Series Data
Timecodes
0:00 - intro
1:47 - pandas installation
5:10 - data frames
8:52 - read and write DataFrame
18:02 - row and column filtering
33:02 - data visualization with pandas
35:57 - missing value treatment
47:00 - duplicate value treatment
👉👉 For more courses:
Explore Our Website 🌐: https://craftknowledge.com/
Join Our Telegram Channel 📱: https://t.me/craftknowledge
Like Us on Facebook 👍: / craft.knowledge
Connect With Us on LinkedIn 🤝: / craft-knowledge
Subscribe to Our YouTube Channel 🎬: / @craft.knowledge
#Data-Engineering #Data-Analytics #Python #Better-compensatin #Beginners #Tutorial