I have this pandas df with 2 columns
target drugs 0 ACE2 gene [angiotensin II,rosiglitazone,irbesartan,valsar] 1 Elastases [heparin,prednisolone,montelukast,formoterol] 2 MAPK14 protein [oxaprozin,nilotinib,imatinib,tocilizumab] 3 TMPRSS2 gene [enzalutamide,camostat] 4 Toll-like receptors [rituximab,atorvastatin,artesunate,tazarotene] 5 Ubiquitin [sunitinib,lapatinib,atorvastatin,edaravone] 6 ezrin [erlotinib,crizotinib,sorafenib,everolimus]
and I want to create a plot that clusters the drugs into their target, so there will be 7 clusters (7 targets) , I am not sure how to do it..
This is the df:
import pandas as pd data = {'target': ['ACE2 gene', 'Elastases', 'MAPK14 protein, human', 'TMPRSS2 gene', 'Toll-like receptors', 'Ubiquitin' , 'ezrin'],'drugs': [['angiotensin II','rosiglitazone','irbesartan'], ['heparin','prednisolone','montelukast','formoterol'] , ['oxaprozin','nilotinib','imatinib','tocilizumab'] , ['enzalutamide','camostat'] , ['rituximab','atorvastatin','artesunate','tazarotene'] , ['sunitinib','lapatinib','atorvastatin','edaravone'], ['erlotinib','crizotinib','sorafenib','everolimus']] } df = pd.DataFrame(data)
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Answer
You can plot scatterplot
with seaborn
like below: (Because you say in the comments of other answer, You have problem with answer, I send another answer with another approach.)
import matplotlib.pyplot as plt import pandas as pd from itertools import chain import seaborn as sns df = pd.DataFrame(data = {'target': ['ACE2 gene', 'Elastases', 'MAPK14 protein, human', 'TMPRSS2 gene', 'Toll-like receptors', 'Ubiquitin' , 'ezrin'], 'drugs': [['angiotensin II','rosiglitazone','irbesartan'], ['heparin','prednisolone','montelukast','formoterol'] , ['oxaprozin','nilotinib','imatinib','tocilizumab'] , ['enzalutamide','camostat'] , ['rituximab','atorvastatin','artesunate','tazarotene'] , ['sunitinib','lapatinib','atorvastatin','edaravone'], ['erlotinib','crizotinib','sorafenib','everolimus']]}) df['times'] = df['drugs'].apply(lambda x : len(x)) df = df.loc[df.index.repeat(df['times'])].reset_index(drop=True) df['drug'] = df.groupby('target')['drugs'].transform(lambda x: list(y[idx] for idx, y in enumerate(x))) df = df.drop(['drugs','times'], axis=1) df['unq_id'] = df.index+1 fig, axe = plt.subplots(figsize=(20,10)) axe.axis('off') sns.scatterplot(data=df, x="unq_id", y="target", hue="target", ax= axe, s=1000) for _, point in df.iterrows(): axe.text(point['unq_id']-0.2, point['target'], point['drug'], rotation=45, size=18) plt.setp(axe.get_legend().get_texts(), fontsize='22') # for legend text plt.setp(axe.get_legend().get_title(), fontsize='32') # for legend title plt.show()
Output: