Treemap in Plotly

Treemap in plotly.express is convenient to use, high_ranking terminal to plotly, which accomplishes a variety of types of data and produces easy-to-style figures. A treemap provides a stratified view of data and makes it easy to blot the patterns. The tree branches are characterized by rectangles and each of the sub_branches is shown in a smaller rectangle.

Syntax: plotly.express.treemap(data_frame=None, names=None, values=None, parents=None, ids=None, path=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None)

Parameters:

data_frame: This argument needs to be passed for column names (and not keyword names) to be used. Array-like and dict are transformed internally to a pandas DataFrame. 

names: 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 as labels for sectors.

values: 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 set values associated to sectors.

path: Either names of columns in data_frame, or pandas Series, or array_like objects List of columns names or columns of a rectangular dataframe defining the hierarchy of sectors, from root to leaves. 

color: 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 assign color to marks.

Example:

Python3




import plotly.express as px
 
 
fig = px.treemap(
    names = ["A","B", "C", "D", "E"],
    parents = ["", "A", "B", "C", "A"]
)
 
fig.show()


 

 

Output:

 

Treemap using Plotly in Python

Plotly is a Python library that is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot, and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.

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