将matplotlib图像插入到pandas数据帧中

Question

目的:我正在使用rdkit来根据我的分子颜色进行着色rdkit.Chem.Draw.SimilarityMaps.现在,我想使用matplotlib图像SimilarityMaps函数在pandas数据帧中引入它们,并以html文件的形式导出该表.

代码:我尝试使用以下代码执行此操作

import pandas as pd
from rdkit import Chem
from rdkit.Chem import Draw
from rdkit.Chem.Draw import SimilarityMaps
from rdkit.Chem.Draw import IPythonConsole #Needed to show molecules
from rdkit.Chem.Draw.MolDrawing import MolDrawing, DrawingOptions

df = pd.DataFrame({'smiles':['Nc1nc(NC2CC2)c3ncn([C@@H]4C[C@H](CO)C=C4)c3n1','CCCC(=O)Nc1ccc(OCC(O)CNC(C)C)c(c1)C(C)=O','CCN(CC)CCNC(=O)C1=CC=C(C=C1)NC(=O)C','CC(=O)NC1=CC=C(C=C1)O','CC(=O)Nc1sc(nn1)[S](N)(=O)=O']})

def getSim(smi):
    mol = Chem.MolFromSmiles(smi)
    refmol = Chem.MolFromSmiles('c1ccccc1')
    fp = SimilarityMaps.GetMorganFingerprint(mol, fpType='bv')
    fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(refmol, mol, SimilarityMaps.GetMorganFingerprint)
    return fig

df['map'] = df['smiles'].map(getSim)
df.to_html('/.../test.html')

当我打开文件时test.html,map列包含信息"Figure(200x200)".我检查我的数据帧映射列是否包含对象:它在python中没有问题,但在html文件中没有.

问题:我不确定如何获取带有图像的数据框,我希望得到社区的帮助来澄清这个主题.

提前致谢

Answer 1

你看到的Figure (200x200)是__repr__matplotlib图类的字符串.它是该python对象的文本表示(与您在执行时看到的相同print(fig)).

你想要的是在表格中有一个实际的图像.一个简单的选择是将matplotlib图保存为png图像,创建一个html标签,<img src="some.png" />从而显示该表.

import pandas as pd
import numpy as np;np.random.seed(1)
import matplotlib.pyplot as plt
import matplotlib.colors

df = pd.DataFrame({"info" : np.random.randint(0,10,10), 
                   "status" : np.random.randint(0,3,10)})

cmap = matplotlib.colors.ListedColormap(["crimson","orange","limegreen"])

def createFigure(i):
    fig, ax = plt.subplots(figsize=(.4,.4))
    fig.subplots_adjust(0,0,1,1)
    ax.axis("off")
    ax.axis([0,1,0,1])
    c = plt.Circle((.5,.5), .4, color=cmap(i))
    ax.add_patch(c)
    ax.text(.5,.5, str(i), ha="center", va="center")
    return fig

def mapping(i):
    fig = createFigure(i)
    fname = "data/map_{}.png".format(i)
    fig.savefig(fname)
    imgstr = '<img src="{}" /> '.format(fname)
    return imgstr


df['image'] = df['status'].map(mapping)
df.to_html('test.html', escape=False)

这样做的缺点是您在磁盘上的某处保存了大量图像.如果不需要,可以将编码为base64的图像存储在html文件中<img src="data:image/png;base64,iVBORw0KGgoAAAAN..." />.

import pandas as pd
import numpy as np;np.random.seed(1)
import matplotlib.pyplot as plt
import matplotlib.colors
from io import BytesIO
import base64

df = pd.DataFrame({"info" : np.random.randint(0,10,10), 
                   "status" : np.random.randint(0,3,10)})

cmap = matplotlib.colors.ListedColormap(["crimson","orange","limegreen"])

def createFigure(i):
    fig, ax = plt.subplots(figsize=(.4,.4))
    fig.subplots_adjust(0,0,1,1)
    ax.axis("off")
    ax.axis([0,1,0,1])
    c = plt.Circle((.5,.5), .4, color=cmap(i))
    ax.add_patch(c)
    ax.text(.5,.5, str(i), ha="center", va="center")
    return fig

def fig2inlinehtml(fig,i):
    figfile = BytesIO()
    fig.savefig(figfile, format='png')
    figfile.seek(0) 
    figdata_png = base64.b64encode(figfile.getvalue())
    imgstr = '<img src="data:image/png;base64,{}" />'.format(figdata_png)
    return imgstr

def mapping(i):
    fig = createFigure(i)
    return fig2inlinehtml(fig,i)


with pd.option_context('display.max_colwidth', -1):
    df.to_html('test.html', escape=False, formatters=dict(status=mapping))

输出看起来相同,但没有图像保存到磁盘.

这在Jupyter笔记本中也很有效,只需要很小的修改,

from IPython.display import HTML
# ...
pd.set_option('display.max_colwidth', -1)
HTML(df.to_html(escape=False, formatters=dict(status=mapping)))