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Python and ML proficiency
·
Module 4
Data Manipulation with Pandas
1
Creating Pandas Series and DataFrames
Create Pandas Series and DataFrame objects from various sources
2
Inspecting DataFrame Properties and Selecting Data
Inspect DataFrame properties and select data using indexing and slicing
Data Import and Export: CSV, Excel, and JSON
Load and export data from various file formats (CSV, Excel, JSON)
4
Filtering and Sorting Data
Filter data using boolean indexing and sort by column values
5
Data Transformation: Functions & New Columns
Transform data by applying functions and creating new columns
6
Missing Data: Imputation and Removal
Handle missing data using imputation and removal strategies
7
Aggregating Data
Group data and compute aggregate statistics
8
Combining DataFrames
Merge, join, and concatenate multiple DataFrames
Previous module
NumPy for Numerical Computing
Next module
Data Visualization and Preparation