Struct ScatterGeo 

pub struct ScatterGeo { /* private fields */ }

A structure representing a geographic scatter plot.

The ScatterGeo struct facilitates the creation and customization of geographic scatter plots with various options for data selection, grouping, layout configuration, and aesthetic adjustments. It supports plotting data points on a map using latitude and longitude coordinates, with customization for markers, lines, text labels, and comprehensive layout options.

Arguments

• data - A reference to the DataFrame containing the data to be plotted.
• lat - A string slice specifying the column name to be used for latitude coordinates.
• lon - A string slice specifying the column name to be used for longitude coordinates.
• mode - An optional Mode specifying the drawing mode (markers, lines, or both).
• text - An optional string slice specifying the column name to be used for text labels.
• group - An optional string slice specifying the column name to be used for grouping data points.
• opacity - An optional f64 value specifying the opacity of the plot elements (range: 0.0 to 1.0).
• size - An optional usize specifying the size of the markers.
• color - An optional Rgb value specifying the color of the markers. This is used when group is not specified.
• colors - An optional vector of Rgb values specifying the colors for the markers. This is used when group is specified.
• shape - An optional Shape specifying the shape of the markers. This is used when group is not specified.
• shapes - An optional vector of Shape values specifying multiple shapes for the markers when plotting multiple groups.
• line_width - An optional f64 value specifying the width of the lines (when mode includes lines).
• line_color - An optional Rgb value specifying the color of the lines.
• plot_title - An optional Text struct specifying the title of the plot.
• legend_title - An optional Text struct specifying the title of the legend.
• legend - An optional reference to a Legend struct for customizing the legend of the plot.

Example

use plotlars::{Plot, Rgb, ScatterGeo, Shape, Text, Mode};
use polars::prelude::*;

// Create sample data with cities and their coordinates
let data = df![
    "city" => ["New York", "Los Angeles", "Chicago", "Houston", "Phoenix"],
    "lat" => [40.7128, 34.0522, 41.8781, 29.7604, 33.4484],
    "lon" => [-74.0060, -118.2437, -87.6298, -95.3698, -112.0740],
    "population" => [8336817, 3979576, 2693976, 2320268, 1680992],
    "region" => ["East", "West", "Central", "South", "West"]
].unwrap();

ScatterGeo::builder()
    .data(&data)
    .lat("lat")
    .lon("lon")
    .mode(Mode::Markers)
    .text("city")
    .group("region")
    .size(15)
    .colors(vec![
        Rgb(255, 0, 0),
        Rgb(0, 255, 0),
        Rgb(0, 0, 255),
        Rgb(255, 165, 0),
    ])
    .plot_title(
        Text::from("US Cities by Region")
            .font("Arial")
            .size(20)
    )
    .legend_title("Region")
    .build()
    .plot();

Implementations

impl ScatterGeo

pub fn builder<'f1, 'f2, 'f3, 'f4, 'f5, 'f6>() -> ScatterGeoBuilder<'f1, 'f2, 'f3, 'f4, 'f5, 'f6>

Examples found in repository

examples/scattergeo.rs (line 13)

fn main() {
    // Example 1: Basic ScatterGeo with markers only
    let cities = df![
        "city" => ["New York", "Los Angeles", "Chicago", "Houston", "Phoenix"],
        "lat" => [40.7128, 34.0522, 41.8781, 29.7604, 33.4484],
        "lon" => [-74.0060, -118.2437, -87.6298, -95.3698, -112.0740],
    ]
    .unwrap();

    ScatterGeo::builder()
        .data(&cities)
        .lat("lat")
        .lon("lon")
        .text("city")
        .plot_title(Text::from("US Major Cities").font("Arial").size(20))
        .build()
        .plot();

    // Example 2: ScatterGeo with grouping by region
    let cities_with_regions = df![
        "city" => ["New York", "Los Angeles", "Chicago", "Houston", "Phoenix", "Philadelphia", "San Antonio", "San Diego", "Dallas", "San Jose"],
        "lat" => [40.7128, 34.0522, 41.8781, 29.7604, 33.4484, 39.9526, 29.4241, 32.7157, 32.7767, 37.3382],
        "lon" => [-74.0060, -118.2437, -87.6298, -95.3698, -112.0740, -75.1652, -98.4936, -117.1611, -96.7970, -121.8863],
        "population" => [8336817, 3979576, 2693976, 2320268, 1680992, 1584064, 1547253, 1423851, 1343573, 1021795],
        "region" => ["Northeast", "West", "Midwest", "South", "West", "Northeast", "South", "West", "South", "West"]
    ]
    .unwrap();

    ScatterGeo::builder()
        .data(&cities_with_regions)
        .lat("lat")
        .lon("lon")
        .mode(Mode::Markers)
        .text("city")
        .group("region")
        .size(20)
        .colors(vec![
            Rgb(255, 0, 0),
            Rgb(0, 255, 0),
            Rgb(0, 0, 255),
            Rgb(255, 165, 0),
        ])
        .shapes(vec![
            Shape::Circle,
            Shape::Square,
            Shape::Diamond,
            Shape::Cross,
        ])
        .plot_title(
            Text::from("US Cities by Region")
                .font("Arial")
                .size(24)
                .x(0.5),
        )
        .legend_title(Text::from("Region").size(14))
        .build()
        .plot();

    // Example 3: ScatterGeo with lines connecting cities (flight paths)
    let flight_path = df![
        "city" => ["New York", "Chicago", "Denver", "Los Angeles"],
        "lat" => [40.7128, 41.8781, 39.7392, 34.0522],
        "lon" => [-74.0060, -87.6298, -104.9903, -118.2437],
    ]
    .unwrap();

    ScatterGeo::builder()
        .data(&flight_path)
        .lat("lat")
        .lon("lon")
        .mode(Mode::LinesMarkers)
        .text("city")
        .size(15)
        .color(Rgb(0, 123, 255))
        .line_width(2.0)
        .line_color(Rgb(255, 123, 0))
        .opacity(0.8)
        .plot_title(Text::from("Flight Path: NY to LA").font("Arial").size(20))
        .build()
        .plot();

    // Example 4: World cities with custom styling
    let world_cities = df![
        "city" => ["London", "Paris", "Tokyo", "Sydney", "Cairo", "Mumbai", "Beijing", "Rio de Janeiro", "Toronto"],
        "lat" => [51.5074, 48.8566, 35.6762, -33.8688, 30.0444, 19.0760, 39.9042, -22.9068, 43.6532],
        "lon" => [-0.1278, 2.3522, 139.6503, 151.2093, 31.2357, 72.8777, 116.4074, -43.1729, -79.3832],
        "continent" => ["Europe", "Europe", "Asia", "Oceania", "Africa", "Asia", "Asia", "South America", "North America"],
        "population_millions" => [9.0, 2.2, 13.9, 5.3, 9.5, 12.4, 21.5, 6.7, 2.9]
    ]
    .unwrap();

    ScatterGeo::builder()
        .data(&world_cities)
        .lat("lat")
        .lon("lon")
        .mode(Mode::Markers)
        .text("city")
        .group("continent")
        .size(25)
        .opacity(0.7)
        .colors(vec![
            Rgb(255, 0, 0),
            Rgb(0, 255, 0),
            Rgb(0, 0, 255),
            Rgb(255, 255, 0),
            Rgb(255, 0, 255),
            Rgb(0, 255, 255),
        ])
        .plot_title(
            Text::from("Major World Cities by Continent")
                .font("Arial")
                .size(24),
        )
        .legend_title(Text::from("Continent").size(16))
        .build()
        .plot();
}

Trait Implementations

impl Clone for ScatterGeo

fn clone(&self) -> ScatterGeo

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Serialize for ScatterGeo

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.