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Understand business needs
·
Module 8
Data Analysis and Manipulation with Pandas
1
Creating and Inspecting Pandas DataFrames
Create and inspect pandas DataFrames from various sources (e.g., CSV, dictionaries).
2
DataFrame Selection & Filtering
Select and filter data from DataFrames using labels, positions, and conditional logic.
3
Missing Data: Drop or Fill?
Handle missing values in a DataFrame using methods like dropping or filling.
4
Removing Duplicates from DataFrames
Identify and remove duplicate records from a DataFrame.
5
Adding and Modifying DataFrame Columns
Manipulate DataFrames by adding or modifying columns.
6
Groupby Operations for Data Aggregation
Perform data aggregation and summarization using groupby operations.
Merging and Joining DataFrames
Merge and join multiple DataFrames to combine datasets.
Previous module
Python Fundamentals for Analysts
Next module
Data Visualization and Storytelling with Tableau