Of course! The term qpolarchart isn't a standard, built-in Python library. It's highly likely you're referring to pyqtgraph, a powerful and fast graphics library for Python that includes a high-quality PlotWidget with a polar plot mode.

This is a common point of confusion because "Q" in PyQtGraph refers to its underlying Qt framework.

Here’s a complete guide on how to create polar charts using pyqtgraph.

Installation

First, you need to install pyqtgraph. It also requires PyQt5 or PyQt6 for the GUI framework.

pip install pyqtgraph PyQt5

(Use PyQt6 if you prefer that version)

A Simple Polar Chart

The key to making a polar chart in pyqtgraph is to set the aspectRatio of the plot to be equal (making it a circle) and then using the setPolar() method on the ViewBox.

Here is the most basic example:

import pyqtgraph as pg
import numpy as np
# Create a QApplication instance (needed for any Qt application)
app = pg.mkQApp("PyQtGraph Polar Plot Example")
# Create the plot window
win = pg.PlotWidget(title="Simple Polar Chart")
# --- The Magic Step ---
# Set the plot to be polar
win.setPolar(True)
# Generate data for the plot
# theta: angles from 0 to 2*pi
# r: radius values
theta = np.linspace(0, 2*np.pi, 100)
r = np.ones_like(theta)  # A circle with radius 1
# Plot the data
# The 'pen' argument sets the line color and width
win.plot(theta, r, pen='b', clear=True, antialias=True)
# Show the window
win.show()
pg.exec_() # Start the Qt event loop

Running this code will produce a window with a blue circle.

A More Detailed Example (Rose Plot)

Let's create a more interesting plot, like a "rose plot" (a polar plot where the radius is a function of the angle).

import pyqtgraph as pg
import numpy as np
import sys
# Create the application and window
app = pg.mkQApp("PyQtGraph Rose Plot")
win = pg.PlotWidget(title="Rose Plot (r = sin(3*theta))")
win.setPolar(True)
# --- Data Generation ---
theta = np.linspace(0, 2*np.pi, 500)
# A 3-petaled rose: r = sin(3*theta)
r = np.abs(np.sin(3 * theta))
# --- Plotting ---
# We can plot multiple curves on the same plot
# Plot 1: The main rose curve
curve1 = win.plot(theta, r, pen='y', width=3, name="Rose")
# Plot 2: Add a circle for reference (r = 0.5)
r_ref = 0.5 * np.ones_like(theta)
curve2 = win.plot(theta, r_ref, pen='g', style=QtCore.Qt.DashLine, name="Reference")
# --- Customization ---
# Add a legend
win.addLegend()
# Set axis labels (optional, as polar labels are implicit)
win.setLabel('bottom', 'Angle (radians)')
win.setLabel('left', 'Radius')
# Set the range for the radial axis
win.setYRange(0, 1.2) # Show up to radius 1.2
# Show the window and run the app
win.show()
if sys.platform == 'darwin': # For macOS
    pg.exec_()
else:
    pg.exec_()

This code produces a yellow, 3-petaled rose with a green dashed reference circle.

Plotting Data Points (Scatter Plot)

You can also plot individual data points using the PlotDataItem with the symbol argument.

import pyqtgraph as pg
import numpy as np
import sys
app = pg.mkQApp("PyQtGraph Polar Scatter Plot")
win = pg.PlotWidget(title="Polar Scatter Plot")
win.setPolar(True)
# --- Generate random data points ---
num_points = 200
theta_random = np.random.uniform(0, 2*np.pi, num_points)
# Radius is more likely to be near the center
r_random = np.random.rayleigh(0.5, num_points)
# --- Plotting as a scatter plot ---
# Use PlotDataItem for more control over symbols
scatter = pg.ScatterPlotItem(
    theta_random, 
    r_random,
    symbol='o',          # 'o' for circle, 't' for triangle, etc.
    size=8,              # Size of the symbols
    pen=pg.mkPen('w'),   # White outline for symbols
    brush=pg.mkBrush('r') # Red fill for symbols
)
win.addItem(scatter)
# Set axis limits
win.setYRange(0, 2.5)
win.show()
if sys.platform == 'darwin':
    pg.exec_()
else:
    pg.exec_()

This will create a scatter plot with red circular points.

Key Methods and Customization

Here are the most important methods and properties for customizing your polar chart:

Alternative Libraries

While pyqtgraph is excellent for interactive applications and scientific computing, other libraries are popular for static plots and data analysis.

Matplotlib

Matplotlib is the standard for plotting in Python. It has built-in polar plotting capabilities.

import matplotlib.pyplot as plt
import numpy as np
# Create a figure and a polar subplot
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
# Generate data
theta = np.linspace(0, 2*np.pi, 100)
r = 1 + np.sin(theta) # A cardioid
# Plot the data
ax.plot(theta, r)
# Set a title
ax.set_title("A Cardioid with Matplotlib")
# Show the plot
plt.show()

Plotly

Plotly is fantastic for creating interactive, publication-quality graphs that can be embedded in web pages.

import plotly.express as px
import numpy as np
# Generate data
theta = np.linspace(0, 2*np.pi, 100)
r = 1 + np.sin(theta) # A cardioid
# Create a DataFrame
import pandas as pd
df = pd.DataFrame({'theta': theta, 'r': r})
# Create the polar plot using Plotly Express
fig = px.line_polar(df, r='r', theta='theta', line_close=True, title="A Cardioid with Plotly")
fig.show()

Summary: Which one to use?

For your request qpolarchart python, pyqtgraph is almost certainly the library you're looking for.