Plotly library of Python can be very useful for data visualization and understanding the data simply and easily. Plotly graph objects are a high-level interface to plotly which are easy to use.
plotly.express.scatter_polar() function
This function is used to create a polar chart. A polar chart represents data along radial and angular axes.
Syntax: plotly.express.scatter_polar(data_frame=None, r=None, theta=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, title=None, template=None, width=None, height=None)
Parameters:
data_frame: DataFrame or array-like or dict needs to be passed for column names.
r, theta: This parameter is either a name of a column in data_frame, or a pandas Series or array_like object. It is used to position marks along the radial and angular axis in polar coordinates respectively.
color: This parameters assign color to marks.
symbol: This parameter is used to assign symbols to marks. It is either a name of a column in data_frame, or a pandas Series or array_like object.
size: This parameter is used to assign mark sizes. It is either a name of a column in data_frame, or a pandas Series or array_like object.
hover_name: Values from this column or array_like appear in bold in the hover tooltip.
hover_data: This parameter is used to appear in the hover tooltip or tuples with a bool or formatting string as first element, and list-like data to appear in hover as second element Values from these columns appear as extra data in the hover tooltip.
title: The figure title
width: The figure width in pixels.
height: The figure height in pixels.
Example 1:
import plotly.express as px
df = px.data.tips()
plot = px.scatter_polar(df, r = 'day',
theta = 'total_bill')
plot.show() |
Output:
Example 2: Using color argument
import plotly.express as px
df = px.data.tips()
plot = px.scatter_polar(df, r = 'day',
theta = 'total_bill',
color='time')
plot.show() |
Output:
Example 3: Using symbol argument
import plotly.express as px
df = px.data.tips()
plot = px.scatter_polar(df, r = 'day',
theta = 'total_bill',
color = 'time',
symbol = 'tip')
plot.show() |
Output: