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_3d() function
This function is used to create a 3D scatter plot and can be used with pandas dataframes. Each row of dataframe is represented by a symbol mark in 3D space in a scatter plot.
Syntax: plotly.express.scatter_3d(data_frame=None, x=None, y=None, z=None, color=None, symbol=None, size=None, text=None, hover_name=None, hover_data=None, custom_data=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, error_z=None, error_z_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, size_max=None, color_discrete_sequence=None, color_discrete_map={}, title=None, template=None, width=None, height=None)
Parameters:
data_frame: DataFrame or array-like or dict needs to be passed for column names.
x, y, z: This parameters is either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the x, y and z axis in cartesian 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.
Example 1:
Python3
# Python program to demonstrate 3D scatter # plot import plotly.express as px df = px.data.tips() plot = px.scatter_3d(df, x = 'day', y = 'total_bill', z='sex') plot.show() |
Output:
Example 2: Using color argument
Python3
# Python program to demonstrate scatter # plot import plotly.express as px df = px.data.tips() plot = px.scatter_3d(df, x = 'day', y = 'total_bill', z = 'sex', color = 'time') plot.show() |
Output:
Example 3:
Python3
# Python program to demonstrate scatter # plot import plotly.express as px df = px.data.tips() plot = px.scatter_3d(df, x = 'day', y = 'total_bill', z = 'sex', color = 'time', symbol = 'total_bill') plot.show() |
Output:
