Explore Data StatisticsĀ¶
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import geolime as geo
from pyproj import CRS
import geolime as geo
from pyproj import CRS
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dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")
dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")
Global AnalysisĀ¶
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geo.correlation_heatmap(geo_object=dh, width=650, height=650)
geo.correlation_heatmap(geo_object=dh, width=650, height=650)
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geo.scatter_correlation(geo_object=dh, width=650, height=650)
geo.scatter_correlation(geo_object=dh, width=650, height=650)
Univariate AnalysisĀ¶
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geo.histogram_plot(
[{"object": dh, "property": "Fe_pct"}],
width=650,
height=400
)
geo.histogram_plot(
[{"object": dh, "property": "Fe_pct"}],
width=650,
height=400
)
Bivariate AnalysisĀ¶
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geo.density_heatmap(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
width=650,
height=400
)
geo.density_heatmap(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
width=650,
height=400
)
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geo.scatter(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
width=650,
height=400
)
geo.scatter(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
width=650,
height=400
)
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geo.scatter(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
marginal_plot="Histogram",
width=650,
height=650
)
geo.scatter(
geo_object=dh,
property_x="Fe_pct",
property_y="Al2O3",
marginal_plot="Histogram",
width=650,
height=650
)