What is Exploratory Data Analysis?
Exploratory Data Analysis (EDA) is the initial process of examining a dataset to understand its basic features. It's about uncovering patterns, distributions, and relationships within the data. EDA is crucial before jumping into formal statistical modeling or machine learning.
It involves techniques like:
- Summarizing the data (mean, median, standard deviation)
- Visualizing data with histograms, scatter plots, and box plots
- Identifying outliers
- Checking for missing values
Key Techniques
Here are some essential techniques used in EDA:
Histograms
Used to visualize the distribution of a single variable.
Scatter Plots
Used to examine the relationship between two variables.
Box Plots
Help identify the median, quartiles, and potential outliers in a dataset.