Pandas
Master data manipulation with Pandas. Explore DataFrames, data cleaning, and advanced analysis techniques to process large datasets efficiently in Python.
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Learning Objectives
What You will Learn in This Course
Master DataFrames and Series object structures.
Efficiently load and export data from various formats (CSV, Excel, SQL).
Perform advanced data cleaning and preprocessing.
Implement powerful data transformations and groupings.
Master multi-indexing and pivot tables.
Perform complex time-series analysis.
Merge and join datasets from multiple sources.
Integrate Pandas with visualization libraries like Matplotlib/Seaborn.
Course Schedule
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Advanced Manipulation
Handle Multi-indexing, hierarchical data, and complex joins/merges.
Time Series Dynamics
Manage Dates, times, offset aliases, resample, and categorical data.
Text & Categorical Wrangling
Perform Advanced string processing and use memory-efficient types.
Performance Optimization
Optimize Memory usage, Vectorization, and use pandas built-in plotting.
Data Pipeline Integration
Automate ETL processes using Pandas and SQL integration.
Real-world Case Study
Analyze a massive multi-file dataset to derive business insights.
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