LOGLOG

Excel Usage

=LOGLOG(data, title, xlabel, ylabel, plot_color, linestyle, marker, legend)

• data (list[list], required): Input data.
• 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.
• plot_color (str, optional, default: null): Line color.
• linestyle (str, optional, default: “-”): Line style (e.g., ‘-’, ‘–’).
• marker (str, optional, default: null): Marker style.
• legend (str, optional, default: “false”): Show legend.

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

Examples

Example 1: Basic log-log plot

Inputs:

data
1	1
10	100
100	10000
1000	1000000

Excel formula:

=LOGLOG({1,1;10,100;100,10000;1000,1000000})

Expected output:

"chart"

Example 2: Log-log plot with multiple series

Inputs:

data			legend
1	1	2	true
10	100	50
100	10000	5000

Excel formula:

=LOGLOG({1,1,2;10,100,50;100,10000,5000}, "true")

Expected output:

"chart"

Example 3: Log-log plot with markers and color

Inputs:

data		plot_color	marker
1	2	red	o
10	20
100	200
1000	2000

Excel formula:

=LOGLOG({1,2;10,20;100,200;1000,2000}, "red", "o")

Expected output:

"chart"

Example 4: Log-log plot with labels and title

Inputs:

data		title	xlabel	ylabel
1	1	Log-Log	X (log)	Y (log)
10	10
100	100
1000	1000

Excel formula:

=LOGLOG({1,1;10,10;100,100;1000,1000}, "Log-Log", "X (log)", "Y (log)")

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 loglog(data, title=None, xlabel=None, ylabel=None, plot_color=None, linestyle='-', marker=None, legend='false'):
    """
    Create a log-log plot from data.

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

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

    Args:
        data (list[list]): Input data.
        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.
        plot_color (str, optional): Line color. Valid options: Blue, Green, Red, Cyan, Magenta, Yellow, Black, White. Default is None.
        linestyle (str, optional): Line style (e.g., '-', '--'). Valid options: Solid, Dashed, Dotted, Dash-dot. Default is '-'.
        marker (str, optional): Marker style. Valid options: None, Point, Pixel, Circle, Square, Triangle Down, Triangle Up. Default is None.
        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).
    """
    def to2d(x):
        return [[x]] if not isinstance(x, list) else x

    try:
        data = to2d(data)

        if not isinstance(data, list) or not all(isinstance(row, list) for row in data):
            return "Error: Invalid input - data must be a 2D list"

        # Extract X and Y columns
        if len(data) < 1 or len(data[0]) < 2:
            return "Error: Data must have at least 2 columns"

        # Determine number of series (first column is X, rest are Y series)
        num_series = len(data[0]) - 1

        X = []
        Y_series = [[] for _ in range(num_series)]

        for row in data:
            if len(row) >= 2:
                try:
                    x_val = float(row[0])
                    if x_val > 0:  # Log scale requires positive values
                        X.append(x_val)
                        for i in range(num_series):
                            if i + 1 < len(row):
                                try:
                                    y_val = float(row[i + 1])
                                    if y_val > 0:
                                        Y_series[i].append(y_val)
                                    else:
                                        Y_series[i].append(None)
                                except (TypeError, ValueError):
                                    Y_series[i].append(None)
                            else:
                                Y_series[i].append(None)
                except (TypeError, ValueError):
                    continue

        if len(X) == 0:
            return "Error: No valid positive numeric data found"

        # Create log-log plot
        fig, ax = plt.subplots(figsize=(8, 6))

        # Plot each series
        for i, Y in enumerate(Y_series):
            plot_kwargs = {'linestyle': linestyle}
            if plot_color:
                plot_kwargs['color'] = plot_color
            if marker:
                plot_kwargs['marker'] = marker

            # Filter out None values
            X_filtered = [X[j] for j in range(len(X)) if j < len(Y) and Y[j] is not None]
            Y_filtered = [y for y in Y if y is not None]

            if len(X_filtered) > 0:
                ax.loglog(X_filtered, Y_filtered, label=f"Series {i+1}", **plot_kwargs)

        if title:
            ax.set_title(title)
        if xlabel:
            ax.set_xlabel(xlabel)
        if ylabel:
            ax.set_ylabel(ylabel)

        if legend == "true" and num_series > 1:
            ax.legend()

        ax.grid(True, which="both", ls="-", alpha=0.2)

        if IS_PYODIDE:
            buf = io.BytesIO()
            plt.savefig(buf, format='png', bbox_inches='tight')
            plt.close(fig)
            buf.seek(0)
            img_base64 = base64.b64encode(buf.read()).decode('utf-8')
            return f"data:image/png;base64,{img_base64}"
        else:
            return fig
    except Exception as e:
        return f"Error: {str(e)}"

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