图论散射图诊断
pyscagnostics的Python项目详细描述
脓皮病
用于计算图论散点图诊断的Python包装器。在
Scagnostics describe various measures of interest for pairs of variables, based on their appearance on a scatterplot. They are useful tool for discovering interesting or unusual scatterplots from a scatterplot matrix, without having to look at every individual plot.
Wilkinson L., Anand, A., and Grossman, R. (2006). High-Dimensional visual analytics: Interactive exploration guided by pairwise views of point distributions. IEEE Transactions on Visualization and Computer Graphics, November/December 2006 (Vol. 12, No. 6) pp. 1363-1372.
安装
pip install pyscagnostics
使用
^{pr2}$文件
defscagnostics(*args,bins:int=50,remove_outliers:bool=True)->Tuple[dict,np.ndarray]:"""Scatterplot diagnostic (scagnostic) measures Scagnostics describe various measures of interest for pairs of variables, based on their appearance on a scatterplot. They are useful tool for discovering interesting or unusual scatterplots from a scatterplot matrix, without having to look at every individual plot. Example: `scagnostics` can take an x, y pair of iterables (e.g. lists or NumPy arrays): ``` from pyscagnostics import scagnostics import numpy as np # Simulate data for example x = np.random.uniform(0, 1, 100) y = np.random.uniform(0, 1, 100) measures, bins = scagnostics(x, y) ``` A Pandas DataFrame can also be passed as the singular required argument. The output will be a generator of results: ``` from pyscagnostics import scagnostics import numpy as np import pandas as pd # Simulate data for example x = np.random.uniform(0, 1, 100) y = np.random.uniform(0, 1, 100) z = np.random.uniform(0, 1, 100) df = pd.DataFrame({ 'x': x, 'y': y, 'z': z }) results = scagnostics(df) for x, y, result in results: measures, bins = result print(measures) ``` Args: *args: x, y: Lists or numpy arrays df: A Pandas DataFrame bins: Max number of bins for the hexagonal grid axis The data are internally binned starting with a (bins x bins) hexagonal grid and re-binned with smaller bin sizes until less than 250 empty bins remain. remove_outliers: If True, will remove outliers before calculations Returns: (measures, bins) measures is a dict with scores for each of 9 scagnostic measures. See pyscagnostics.measure_names for a list of measures bins is a 3 x n numpy array of x-coordinates, y-coordinates, and counts for the hex-bin grid. The x and y coordinates are re-scaled between 0 and 1000. This is returned for debugging and inspection purposes. If the input is a DataFrame, the output will be a generator yielding a tuples of scagnostic results for each column pair: (x, y, (measures, bins)) """
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