How do you make a dendrogram in python?
Basic Dendrogram¶A dendrogram is a diagram representing a tree. The figure factory called Show Dendrogram plots are commonly used in computational biology to show the clustering of genes or samples, sometimes in the margin of heatmaps. In [1]: import plotly.figure_factory as ff import numpy as np np.random.seed(1) X = np.random.rand(15, 12) # 15 samples, with 12 dimensions each fig = ff.create_dendrogram(X) fig.update_layout(width=800, height=500) fig.show() Set Color Threshold¶In [2]: import plotly.figure_factory as ff import numpy as np X = np.random.rand(15, 10) # 15 samples, with 10 dimensions each fig = ff.create_dendrogram(X, color_threshold=1.5) fig.update_layout(width=800, height=500) fig.show() Set Orientation and Add Labels¶In [3]: import plotly.figure_factory as ff import numpy as np X = np.random.rand(10, 12) names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark', 'Alice', 'Charlie', 'Rob', 'Lisa', 'Lily'] fig = ff.create_dendrogram(X, orientation='left', labels=names) fig.update_layout(width=800, height=800) fig.show() In [4]: import plotly.graph_objects as go import plotly.figure_factory as ff import numpy as np from scipy.spatial.distance import pdist, squareform # get data data = np.genfromtxt("http://files.figshare.com/2133304/ExpRawData_E_TABM_84_A_AFFY_44.tab", names=True,usecols=tuple(range(1,30)),dtype=float, delimiter="\t") data_array = data.view((np.float, len(data.dtype.names))) data_array = data_array.transpose() labels = data.dtype.names # Initialize figure by creating upper dendrogram fig = ff.create_dendrogram(data_array, orientation='bottom', labels=labels) for i in range(len(fig['data'])): fig['data'][i]['yaxis'] = 'y2' # Create Side Dendrogram dendro_side = ff.create_dendrogram(data_array, orientation='right') for i in range(len(dendro_side['data'])): dendro_side['data'][i]['xaxis'] = 'x2' # Add Side Dendrogram Data to Figure for data in dendro_side['data']: fig.add_trace(data) # Create Heatmap dendro_leaves = dendro_side['layout']['yaxis']['ticktext'] dendro_leaves = list(map(int, dendro_leaves)) data_dist = pdist(data_array) heat_data = squareform(data_dist) heat_data = heat_data[dendro_leaves,:] heat_data = heat_data[:,dendro_leaves] heatmap = [ go.Heatmap( x = dendro_leaves, y = dendro_leaves, z = heat_data, colorscale = 'Blues' ) ] heatmap[0]['x'] = fig['layout']['xaxis']['tickvals'] heatmap[0]['y'] = dendro_side['layout']['yaxis']['tickvals'] # Add Heatmap Data to Figure for data in heatmap: fig.add_trace(data) # Edit Layout fig.update_layout({'width':800, 'height':800, 'showlegend':False, 'hovermode': 'closest', }) # Edit xaxis fig.update_layout(xaxis={'domain': [.15, 1], 'mirror': False, 'showgrid': False, 'showline': False, 'zeroline': False, 'ticks':""}) # Edit xaxis2 fig.update_layout(xaxis2={'domain': [0, .15], 'mirror': False, 'showgrid': False, 'showline': False, 'zeroline': False, 'showticklabels': False, 'ticks':""}) # Edit yaxis fig.update_layout(yaxis={'domain': [0, .85], 'mirror': False, 'showgrid': False, 'showline': False, 'zeroline': False, 'showticklabels': False, 'ticks': "" }) # Edit yaxis2 fig.update_layout(yaxis2={'domain':[.825, .975], 'mirror': False, 'showgrid': False, 'showline': False, 'zeroline': False, 'showticklabels': False, 'ticks':""}) # Plot! fig.show() What About Dash?¶Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library. Learn about how to install Dash at https://dash.plot.ly/installation. Everywhere in this page that you see import plotly.graph_objects as go # or plotly.express as px fig = go.Figure() # or any Plotly Express function e.g. px.bar(...) # fig.add_trace( ... ) # fig.update_layout( ... ) import dash import dash_core_components as dcc import dash_html_components as html app = dash.Dash() app.layout = html.Div([ dcc.Graph(figure=fig) ]) app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter How do you plot a dendrogram in Python?Dendrograms in Python. Basic Dendrogram. A dendrogram is a diagram representing a tree. The figure factory called create_dendrogram performs hierarchical clustering on data and represents the resulting tree. ... . Set Color Threshold.. Set Orientation and Add Labels.. Plot a Dendrogram with a Heatmap. See also the Dash Bio demo.. How do you make a dendrogram plot?Specify Number of Nodes in Dendrogram Plot
There are 100 data points in the original data set, X . Create a hierarchical binary cluster tree using linkage . Then, plot the dendrogram for the complete tree (100 leaf nodes) by setting the input argument P equal to 0 . Now, plot the dendrogram with only 25 leaf nodes.
How do I create a hierarchical cluster in Python?Steps to Perform Hierarchical Clustering. Step 1: First, we assign all the points to an individual cluster:. Step 2: Next, we will look at the smallest distance in the proximity matrix and merge the points with the smallest distance. ... . Step 3: We will repeat step 2 until only a single cluster is left.. What is dendrogram with example?The most common example of a dendrogram is the tiered diagram used to display the playoff games and progress of some sporting event, like hockey, basketball or baseball. Each of the teams that makes the playoffs is listed, along with the games they need to win in order to make it to the finals.
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