PIE
Excel Usage
=PIE(data, title, pie_colormap, explode, legend)
data(list[list], required): Input data (Labels, Values).title(str, optional, default: null): Chart title.pie_colormap(str, optional, default: “viridis”): Color map for slices.explode(float, optional, default: 0): Explode value for slices.legend(str, optional, default: “true”): Show legend.
Returns (object): Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).
Examples
Example 1: Basic pie chart with percentages
Inputs:
| data | |
|---|---|
| A | 30 |
| B | 20 |
| C | 50 |
Excel formula:
=PIE({"A",30;"B",20;"C",50})
Expected output:
"chart"
Example 2: Pie chart with title and legend
Inputs:
| data | title | legend | |
|---|---|---|---|
| Q1 | 25 | Quarterly Sales | true |
| Q2 | 30 | ||
| Q3 | 20 | ||
| Q4 | 25 |
Excel formula:
=PIE({"Q1",25;"Q2",30;"Q3",20;"Q4",25}, "Quarterly Sales", "true")
Expected output:
"chart"
Example 3: Exploded pie chart
Inputs:
| data | explode | |
|---|---|---|
| A | 40 | 0.1 |
| B | 30 | |
| C | 30 |
Excel formula:
=PIE({"A",40;"B",30;"C",30}, 0.1)
Expected output:
"chart"
Example 4: Custom color map
Inputs:
| data | pie_colormap | |
|---|---|---|
| X | 10 | plasma |
| Y | 20 | |
| Z | 30 |
Excel formula:
=PIE({"X",10;"Y",20;"Z",30}, "plasma")
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
import matplotlib.cm as cm
def pie(data, title=None, pie_colormap='viridis', explode=0, legend='true'):
"""
Create a pie chart from data.
See: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.pie.html
This example function is provided as-is without any representation of accuracy.
Args:
data (list[list]): Input data (Labels, Values).
title (str, optional): Chart title. Default is None.
pie_colormap (str, optional): Color map for slices. Valid options: Viridis, Plasma, Inferno, Magma, Cividis. Default is 'viridis'.
explode (float, optional): Explode value for slices. Default is 0.
legend (str, optional): Show legend. Valid options: True, False. Default is 'true'.
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."
if len(data[0]) < 2:
return "Error: Data must have at least 2 columns (Labels, Values)."
# Extract labels and values
labels = [str(row[0]) for row in data]
try:
values = [float(row[1]) for row in data]
except Exception:
return "Error: Values must be numeric."
if any(v < 0 for v in values):
return "Error: Pie chart values must be non-negative."
if sum(values) == 0:
return "Error: Sum of values must be greater than zero."
# Create figure
fig, ax = plt.subplots(figsize=(6, 4))
# Get colors from colormap
cmap = cm.get_cmap(pie_colormap)
colors = [cmap(i / len(values)) for i in range(len(values))]
# Create explode array if specified
explode_array = None
if explode > 0:
explode_array = [explode] * len(values)
# Create pie chart
ax.pie(values, labels=labels, autopct='%1.1f%%', colors=colors, explode=explode_array)
if title:
ax.set_title(title)
if legend == "true":
ax.legend(labels, loc="best")
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)}"