144 chart features

Feature and FeatureCollection Charts

Uncomment the following line to install geemap if needed.

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# %pip install -U geemap

# %pip install -U geemap

Import libraries¶

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import calendar
import ee
import geemap
from geemap import chart

import calendar import ee import geemap from geemap import chart

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geemap.ee_initialize()

geemap.ee_initialize()

feature_by_feature¶

Features are plotted along the x-axis, labeled by values of a selected property. Series are represented by adjacent columns defined by a list of property names whose values are plotted along the y-axis.

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ecoregions = ee.FeatureCollection("projects/google/charts_feature_example")
features = ecoregions.select("[0-9][0-9]_tmean|label")

ecoregions = ee.FeatureCollection("projects/google/charts_feature_example") features = ecoregions.select("[0-9][0-9]_tmean|label")

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geemap.ee_to_df(features)

geemap.ee_to_df(features)

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x_property = "label"
y_properties = [str(x).zfill(2) + "_tmean" for x in range(1, 13)]

labels = calendar.month_abbr[1:]  # a list of month labels, e.g. ['Jan', 'Feb', ...]

colors = [
    "#604791",
    "#1d6b99",
    "#39a8a7",
    "#0f8755",
    "#76b349",
    "#f0af07",
    "#e37d05",
    "#cf513e",
    "#96356f",
    "#724173",
    "#9c4f97",
    "#696969",
]
title = "Average Monthly Temperature by Ecoregion"
x_label = "Ecoregion"
y_label = "Temperature"

x_property = "label" y_properties = [str(x).zfill(2) + "_tmean" for x in range(1, 13)] labels = calendar.month_abbr[1:] # a list of month labels, e.g. ['Jan', 'Feb', ...] colors = [ "#604791", "#1d6b99", "#39a8a7", "#0f8755", "#76b349", "#f0af07", "#e37d05", "#cf513e", "#96356f", "#724173", "#9c4f97", "#696969", ] title = "Average Monthly Temperature by Ecoregion" x_label = "Ecoregion" y_label = "Temperature"

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fig = chart.feature_by_feature(
    features,
    x_property,
    y_properties,
    colors=colors,
    labels=labels,
    title=title,
    x_label=x_label,
    y_label=y_label,
)
fig

fig = chart.feature_by_feature( features, x_property, y_properties, colors=colors, labels=labels, title=title, x_label=x_label, y_label=y_label, ) fig

feature.by_property¶

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ecoregions = ee.FeatureCollection("projects/google/charts_feature_example")
features = ecoregions.select("[0-9][0-9]_ppt|label")

ecoregions = ee.FeatureCollection("projects/google/charts_feature_example") features = ecoregions.select("[0-9][0-9]_ppt|label")

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geemap.ee_to_df(features)

geemap.ee_to_df(features)

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keys = [str(x).zfill(2) + "_ppt" for x in range(1, 13)]
values = calendar.month_abbr[1:]  # a list of month labels, e.g. ['Jan', 'Feb', ...]

keys = [str(x).zfill(2) + "_ppt" for x in range(1, 13)] values = calendar.month_abbr[1:] # a list of month labels, e.g. ['Jan', 'Feb', ...]

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x_properties = dict(zip(keys, values))
series_property = "label"
title = "Average Ecoregion Precipitation by Month"
colors = ["#f0af07", "#0f8755", "#76b349"]

x_properties = dict(zip(keys, values)) series_property = "label" title = "Average Ecoregion Precipitation by Month" colors = ["#f0af07", "#0f8755", "#76b349"]

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fig = chart.feature_by_property(
    features,
    x_properties,
    series_property,
    title=title,
    colors=colors,
    x_label="Month",
    y_label="Precipitation (mm)",
    legend_location="top-left",
)
fig

fig = chart.feature_by_property( features, x_properties, series_property, title=title, colors=colors, x_label="Month", y_label="Precipitation (mm)", legend_location="top-left", ) fig

feature_groups¶

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ecoregions = ee.FeatureCollection("projects/google/charts_feature_example")
features = ecoregions.select("[0-9][0-9]_ppt|label")

ecoregions = ee.FeatureCollection("projects/google/charts_feature_example") features = ecoregions.select("[0-9][0-9]_ppt|label")

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features = ee.FeatureCollection("projects/google/charts_feature_example")
x_property = "label"
y_property = "01_tmean"
series_property = "warm"
title = "Average January Temperature by Ecoregion"
colors = ["#cf513e", "#1d6b99"]
labels = ["Warm", "Cold"]

features = ee.FeatureCollection("projects/google/charts_feature_example") x_property = "label" y_property = "01_tmean" series_property = "warm" title = "Average January Temperature by Ecoregion" colors = ["#cf513e", "#1d6b99"] labels = ["Warm", "Cold"]

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chart.feature_groups(
    features,
    x_property,
    y_property,
    series_property,
    title=title,
    colors=colors,
    x_label="Ecoregion",
    y_label="January Temperature (°C)",
    legend_location="top-right",
    labels=labels,
)

chart.feature_groups( features, x_property, y_property, series_property, title=title, colors=colors, x_label="Ecoregion", y_label="January Temperature (°C)", legend_location="top-right", labels=labels, )

feature_histogram¶

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source = ee.ImageCollection("OREGONSTATE/PRISM/Norm91m").toBands()
region = ee.Geometry.Rectangle(-123.41, 40.43, -116.38, 45.14)
features = source.sample(region, 5000)

source = ee.ImageCollection("OREGONSTATE/PRISM/Norm91m").toBands() region = ee.Geometry.Rectangle(-123.41, 40.43, -116.38, 45.14) features = source.sample(region, 5000)

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geemap.ee_to_df(features.limit(5).select(["07_ppt"]))

geemap.ee_to_df(features.limit(5).select(["07_ppt"]))

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property = "07_ppt"
title = "July Precipitation Distribution for NW USA"

property = "07_ppt" title = "July Precipitation Distribution for NW USA"

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fig = chart.feature_histogram(
    features,
    property,
    max_buckets=None,
    title=title,
    x_label="Precipitation (mm)",
    y_label="Pixel Count",
    colors=["#1d6b99"],
)
fig

fig = chart.feature_histogram( features, property, max_buckets=None, title=title, x_label="Precipitation (mm)", y_label="Pixel Count", colors=["#1d6b99"], ) fig