tghas.blogg.se

Splom ( dimensions = ), dict ( label = 'Glucose', values = dfd ), dict ( label = 'BloodPressure', values = dfd ), dict ( label = 'SkinThickness', values = dfd ), dict ( label = 'Insulin', values = dfd ), dict ( label = 'BMI', values = dfd ), dict ( label = 'DiabPedigreeFun', values = dfd ), dict ( label = 'Age', values = dfd )], marker = dict ( color = dfd, size = 5, colorscale = 'Bluered', line = dict ( width = 0.5, color = 'rgb(230,230,230)' )), text = textd, diagonal = dict ( visible = False ))) title = "Scatterplot Matrix (SPLOM) for Diabetes DatasetData source:" +\ Import aph_objs as go import pandas as pd dfd = pd. update_layout ( title = 'Iris Data set', dragmode = 'select', width = 600, height = 600, hovermode = 'closest', ) fig. Splom ( dimensions = ), dict ( label = 'sepal width', values = df ), dict ( label = 'petal length', values = df ), dict ( label = 'petal width', values = df )], text = df, marker = dict ( color = index_vals, showscale = False, # colors encode categorical variables line_color = 'white', line_width = 0.5 ) )) fig. # Define indices corresponding to flower categories, using pandas label encoding index_vals = df. With this powerful interface, it’s easy to set up, deploy and run Zebra’s Fixed Industrial Scanners and Machine Vision Smart Cameras, eliminating the need for different tools and reducing training and deployment time. The flowers are labeled as `Iris-setosa`, # `Iris-versicolor`, `Iris-virginica`. Zebra Aurora brings a new level of simplicity to controlling enterprise-wide manufacturing and logistics automation solutions. read_csv ( '' ) # The Iris dataset contains four data variables, sepal length, sepal width, petal length, # petal width, for 150 iris flowers. Import aph_objects as go import pandas as pd df = pd.