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plotly.express.scatter_3d() function in Python

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:




# 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




# 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:




# 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:


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