我有一个嵌套的Python字典:
d={'CON-2': {'gene-ODF3': [2.0, 44474],'gene-SCGB1C1': [0.184937, 36615], 'gene-TRNAN-GUU-19': [32.0, 443]},'CON-1':{'gene-ODF3': [10.00, 44474], 'gene-SCGB1C1': [0.184937, 36615], 'gene-TRNAN-GUU-19': [30.0, 443], 'gene-LOC103247846': [20.0, 22111]}}
我想在散点图上绘制每个基因的FPKM(第一个值(与其DNA转录物丰度(第二个值(。我尝试了一些不同的东西,比如:
CON_1=pd.DataFrame(d['CON-1'].items(),columns=['FPKM','Fraction-0'])
CON_2=pd.DataFrame(d['CON-2'].items(),columns=['FPKM','Fraction-0'])
df=pd.DataFrame.from_dict({(i,j): d[i][j]
for i in d.keys()
for j in d[i].keys()},
orient='index')
但我无法将这两种价值观区分开来。我想为每个条件(CON-1和CON-2(生成一个单独的数据帧,如下所示:
gene FPKM DNA-abundance
gene-ODF3 2.0 44474
pd.DataFrame(d)['CON-1'].apply(pd.Series)
.rename(columns={0:'FPKM',1:'DNA-abundance'})
# FPKM DNA-abundance
#gene-ODF3 10.000000 44474.0
#gene-SCGB1C1 0.184937 36615.0
#gene-TRNAN-GUU-19 30.000000 443.0
#gene-LOC103247846 20.000000 22111.0
其他情况也是如此。