SCATTER

Excel Usage

=SCATTER(data, title, xlabel, ylabel, scatter_color, scatter_marker, point_size, grid, legend)

• data (list[list], required): Input data. Supports multiple columns (X, Y1, Y2…).
• title (str, optional, default: null): Chart title.
• xlabel (str, optional, default: null): Label for X-axis.
• ylabel (str, optional, default: null): Label for Y-axis.
• scatter_color (str, optional, default: null): Point color.
• scatter_marker (str, optional, default: “o”): Marker style.
• point_size (float, optional, default: 20): Size of points.
• grid (str, optional, default: “true”): Show grid lines.
• legend (str, optional, default: “false”): Show legend.

Returns (object): Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).

Examples

Example 1: Basic XY scatter plot

Inputs:

data
1	2
2	4
3	6
4	8

Excel formula:

=SCATTER({1,2;2,4;3,6;4,8})

Expected output:

"chart"

Example 2: Scatter plot with title and axis labels

Inputs:

data		title	xlabel	ylabel
1	2	XY Data	X Values	Y Values
2	4
3	6

Excel formula:

=SCATTER({1,2;2,4;3,6}, "XY Data", "X Values", "Y Values")

Expected output:

"chart"

Example 3: Multiple Y series with legend

Inputs:

data			legend
1	2	3	true
2	4	5
3	6	7

Excel formula:

=SCATTER({1,2,3;2,4,5;3,6,7}, "true")

Expected output:

"chart"

Example 4: Custom marker, color, and size

Inputs:

data		scatter_marker	scatter_color	point_size
1	2	s	red	50
2	4
3	6

Excel formula:

=SCATTER({1,2;2,4;3,6}, "s", "red", 50)

Expected output:

"chart"

Python Code

import sys
import matplotlib
IS_PYODIDE = sys.platform == "emscripten"
if IS_PYODIDE:
    matplotlib.use('Agg')
import matplotlib.pyplot as plt
import io
import base64
import numpy as np

def scatter(data, title=None, xlabel=None, ylabel=None, scatter_color=None, scatter_marker='o', point_size=20, grid='true', legend='false'):
    """
    Create an XY scatter plot from data.

    See: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html

    This example function is provided as-is without any representation of accuracy.

    Args:
        data (list[list]): Input data. Supports multiple columns (X, Y1, Y2...).
        title (str, optional): Chart title. Default is None.
        xlabel (str, optional): Label for X-axis. Default is None.
        ylabel (str, optional): Label for Y-axis. Default is None.
        scatter_color (str, optional): Point color. Valid options: Blue, Green, Red, Cyan, Magenta, Yellow, Black, White. Default is None.
        scatter_marker (str, optional): Marker style. Valid options: Point, Pixel, Circle, Square, Triangle Down, Triangle Up. Default is 'o'.
        point_size (float, optional): Size of points. Default is 20.
        grid (str, optional): Show grid lines. Valid options: True, False. Default is 'true'.
        legend (str, optional): Show legend. Valid options: True, False. Default is 'false'.

    Returns:
        object: Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).
    """
    try:
        if not isinstance(data, list) or not data or not isinstance(data[0], list):
            return "Error: Input data must be a 2D list."

        # Convert to numpy array
        try:
            arr = np.array(data, dtype=float)
        except Exception:
            return "Error: Data must be numeric."

        if arr.ndim != 2 or arr.shape[1] < 2:
            return "Error: Data must have at least 2 columns (X, Y)."

        # Extract X and Y series
        x = arr[:, 0]
        y_series = [arr[:, i] for i in range(1, arr.shape[1])]

        # Create figure
        fig, ax = plt.subplots(figsize=(6, 4))

        # Plot scatter points
        if len(y_series) == 1:
            ax.scatter(x, y_series[0], s=point_size, color=scatter_color if scatter_color else None, marker=scatter_marker)
        else:
            for i, y in enumerate(y_series):
                ax.scatter(x, y, s=point_size, marker=scatter_marker, label=f"Series {i+1}")

        # Set labels and title
        if title:
            ax.set_title(title)
        if xlabel:
            ax.set_xlabel(xlabel)
        if ylabel:
            ax.set_ylabel(ylabel)

        # Grid and legend
        if grid == "true":
            ax.grid(True, alpha=0.3)
        if legend == "true" and len(y_series) > 1:
            ax.legend()

        plt.tight_layout()

        if IS_PYODIDE:
            buf = io.BytesIO()
            plt.savefig(buf, format='png')
            plt.close(fig)
            buf.seek(0)
            img_bytes = buf.read()
            img_b64 = base64.b64encode(img_bytes).decode('utf-8')
            return f"data:image/png;base64,{img_b64}"
        else:
            return fig
    except Exception as e:
        return f"Error: {str(e)}"

Online Calculator