Data analysis
Definition
Data analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information and support decision-making. In Python, it involves using libraries such as Pandas and NumPy to manipulate datasets.
5 Must Know Facts For Your Next Test
- Data analysis often starts with data cleaning to handle missing or inconsistent data.
- Python's Pandas library provides powerful data manipulation capabilities through DataFrames.
- NumPy is used for numerical operations in Python, especially when dealing with arrays.
- Visualization tools like Matplotlib and Seaborn are essential for understanding data trends and patterns.
- Understanding basic statistics is crucial for interpreting results from data analysis.
Review Questions
- What are the key steps involved in data analysis?
- How does a Pandas DataFrame differ from a NumPy array?
- Why is data visualization important in the context of data analysis?
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Related terms
Pandas: A Python library providing high-performance, easy-to-use structures and data analysis tools.
NumPy: A fundamental package for scientific computing in Python that supports large multi-dimensional arrays and matrices.
Matplotlib: $$ A plotting library for the Python programming language $$
