modeva.DataSet.eda_1d#
- DataSet.eda_1d(feature: str, dataset: str = 'main', plot_type: str = 'density', bins: int = 10, sample_size: int = None, random_state: int = 0)#
Creates a univariate visualization for analyzing the distribution of a single feature.
This function generates either a density plot, histogram, or bar chart depending on the feature type (numerical or categorical) and user preferences. It supports data sampling for large datasets and provides customizable visualization options including bin sizes for histograms.
- Parameters:
feature (str) – Name of the feature to visualize in the dataset.
dataset ({"main", "train", "test"}, default="main") – Specifies which dataset partition to use for visualization.
plot_type ({"density", "histogram"}, default="density") – Type of visualization for numerical features. Categorical features always use bar charts.
bins (int, default=10) – Number of bins for histogram visualization when plot_type is “histogram”.
sample_size (int, default=None) – Size of random sample to use for visualization. Uses all data if None.
random_state (int, default=0) – Random seed for reproducible sampling when sample_size is specified.
- Returns:
A container object with the following components:
key: “data_eda_1d”
data: Name of the dataset used
inputs: Dictionary of input parameters used
options: Dictionary of visualizations configuration for a bar / histogram / density plot. Run results.plot() to show this plot.
- Return type:
Examples
