USDA Nutrients UMAP-HeatmapCitiBike Clustergrammer-GL and Deck.glClustergrammer-GL Visium ExampleCOVID-19 Transcriptional Signature Tenoever Data: A5492,700 PBMC scRNA-seq Clustergrammer-GL and Enrichr NotebookNBA Shot Chart Clustergrammer-GLNBA Player Stats UMAP-HeatmapClustergrammer-GL
Clustergrammer2 Pyodide
// choose your dataset
//////////////////////////////
// csv_string = FileAttachment("10K_random.csv").text()
// csv_string = FileAttachment("1M_random.csv").text()
csv_string = FileAttachment("ccle_data_observable.csv").text()
// csv_string = FileAttachment("rc_two_cat_clean.csv").text()
run_clustergrammer = {
py`
import micropip
micropip.install(['clustergrammer2_core==0.3.0'])
`
var run_clustergrammer = py`
import micropip
import pandas as pd
import scipy
import sklearn
import statsmodels
import matplotlib
import json
from io import StringIO
from clustergrammer2_core import net
def run_clustergrammer(csv_string):
df = pd.read_csv(StringIO(csv_string), sep=",", index_col=0)
net.load_df(df)
# Z-Score Data
#########################
net.normalize(axis='row', norm_type='zscore')
net.cluster()
return json.dumps(net.viz)
run_clustergrammer
`
return run_clustergrammer
}
network = JSON.parse(run_clustergrammer(csv_string))
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
