What is exploratory data analysis?
Exploratory Data Analysis (EDA) is a statistical approach used to analyze datasets to summarize their main characteristics.
Why is EDA important in data science?
EDA helps in understanding the data, identifying patterns, spotting anomalies, and formulating hypotheses.
What are some common techniques used in EDA?
Common techniques include data visualization, summary statistics, and correlation analysis.
Can you give an example of a visualization used in EDA?
Sure! A scatter plot is often used to visualize the relationship between two numerical variables.
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