对字符串数据的部分进行热编码。

Question

ACN58946.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macB|antibiotic靶protection|0\sMAEPVLSVKDLDIRFTTPDGNVHAVKKVSFDIAPGECLGVVGESGSGKSQLFMACIGLLAGNGKATGSVTYRGQELLGQPAAKLNAIRGAKITMIFQDPLTSLTPHMRIGDQIVESLRTHSKLSKGEAEKRAIQALELVRIPEAKRRMRQYPHELSGGMRQRVMIAMATACGPDLLIADEPTTALDVTVQAQILDIMRDLRKELGTSIALISHDMGVIASICDRVQVMRYGEFVETGPADDIFYHPQHPYTRMLLEAMPRIDQPVREGRAALKPLAPQEARTTLLEVDNVKVHFPIQMGGVFFGKYKPLRAVDGVSFTLHQGETIGIVGESGCGKSTLARAVLELLPKTTGGVVWMGRDLGALPPAELRRARKDFQIVFQDPLASLDPRMTIGQSIAEPLQSLEPELSKHEVQSRVRAIMEKVGLDPDWINRYPHEFSGGQNQRVGIARAMILKPKLIVCDEAVSALDVSIQAQIVDLILSLQAEFGMSIIFISHDLSVVRQVSHRVMVLYLGRVVELASRDAIYEDARHPYTKALISAVTVPDPRAERLKKRRELPGELPSPLDTRSALMFLKSKRIDDPDAEQYVPKLIEVAPGHFVAEHDPFEVVEMTG\e>ACN58871.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macB|antibiotic efflux|0\sMADYLLEMKNIVKEFGGVRALNGIDIKLKAGECAGLCGENGAGKSTLMKVLSAVYPHGTWDGEILWDGKPLRAQSIRETEAAGIVIIHQELMLVPELSVAENIFLGNEIKLPGGRMDYAAMNRRAEELLAELDIRDVNVVLPVKQYGGGYQQLIEIAKALNKNARLLILDEPSSSLTASEIKVLLRIIHSLKAKGVTCVYISHKLDEVADICDTIVVIRDGQHIATTPMADMNIERIIAQMVGREMNQLYPERSHVPGEVIFEARNVSCYDADNPQRKRVDNISFKLRKGEILGIAGLVGAGRTELVSALFGAYPGPSEAEVWLNGVKLDTRTPLKAIRAGLAMVPEDRKQHGIVPDLGVGHNMTLAVLNDFVRATRIDQQAELATIHKEIKSVKLKTATPFLPITSLSGGNQQKAVLSKMLLTKPKILILDEPTRGVDVGAKFEIYQLMFDLAAQGMSIIMVSSELAEVLGISDRVLVVGEGKLRGDFVNDNLSQETVLAAALDHTQPALH\e>ACN58991.1|FEATURES|NCBI|multidrug|cmeB|antibiotic efflux|0\sMKNDRGEMVPFSAFMTIKKKQGANEINRYNMYNTAAIRGGPATGYSSGEAIKAVQEVAAKNLPNGFDIDWAALSYDETRRGNEAVYIFLIVLAFVYLVLAAQYESFIIPLAVVFSLPAGVFGSFLLIKGMGLANDIYAQVGLVMLVGLLGKNAVLIVEFAVQKQQQGATVFEAAIEGARVRFRPILMTSFAFIAGLIPLVFAHGAGAIGNKTIGSSALGGMFFGTVFGVIVVPGLYYVFGSWAEGRKLIRGEDHDPLTENLVHQMDNFPQSDDK\e>ACN58776.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macA|antibiotic efflux|0\sMGNLPRPTLSPSLSGIRPTMNRETTTRVDSSTPAARLGMRVPSTSRAALVGVAALVVILGGWYGIKRWRAHVASEGQYIFAAIQKGDIEDLVTATGSLQPRDYVDVGAQVSGQLDKILVEVGSDVKEGDLLAEIDADVAAARVDASRAQLRSQQAQLVQQQANLTKAERDLTRQQNLMKEDATTAEQVQNAETTLDTTKAQINALKAQMEQLRASMRVDESNLNYTKILAPMSGTVVSISAKQGQTLNTNQQAPTILRIADLSTMTVQTQVSEADVSKLRSGMQAYFTTLGSAGKRWYGQLKKIEPTPTVTNNVVLYNALFEVPNDNKQLLPQMTAQVFFVAAAAHDVLVVPMSAVSLQRTPPGGIPNAAAAQAAGARGAGAQGAGAQGAQGASAQGAGAQSGQGGQGAAALTPEQIARREARRQQRMQSNGGSATGGAIEGGPPRGGFGASMAARGPRHATVRVQAADGKIEERQITIGVTNRVHAEVLSGLKEGERVVAGTKEPEKAPATAGGQQGAGGQRNNIGGFPGGGLGGGFGR\e

我现在正在研究蛋白质序列。我有这些字符串数据，我想要转换成一个热编码部分。我想要转换的部分在'\s‘之后开始，在'\e’之前结束，然后对整个字符串数据进行转换。由于I有数千个数据集，使用纯Python代码似乎是不可能的，因为完成这个过程需要很长时间。针对这个问题有机器学习库吗？

谢谢你提前提供帮助！

Answer 1

我建议使用斯克勒恩的单热编码器。它应该以最大的效率对数据进行编码。

如果您想在Python中优化其他ML任务，我建议查看丹瑟尔流/喀拉斯、PyTorch 科学知识-学习(SKLearn)和ScyPi。当然，Numpy也是必不可少的。这些工具功能强大，优化程度很高，并且有大量的资源可以帮助您解决问题。它们应该可以帮助您解决几乎所有遇到的ML问题:)

Answer 2

为此您可以使用熊猫。

import pandas as pd
import io
    
data = "ACN58946.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macB|antibiotic target protection|0\sMAEPVLSVKDLDIRFTTPDGNVHAVKKVSFDIAPGECLGVVGESGSGKSQLFMACIGLLAGNGKATGSVTYRGQELLGQPAAKLNAIRGAKITMIFQDPLTSLTPHMRIGDQIVESLRTHSKLSKGEAEKRAIQALELVRIPEAKRRMRQYPHELSGGMRQRVMIAMATACGPDLLIADEPTTALDVTVQAQILDIMRDLRKELGTSIALISHDMGVIASICDRVQVMRYGEFVETGPADDIFYHPQHPYTRMLLEAMPRIDQPVREGRAALKPLAPQEARTTLLEVDNVKVHFPIQMGGVFFGKYKPLRAVDGVSFTLHQGETIGIVGESGCGKSTLARAVLELLPKTTGGVVWMGRDLGALPPAELRRARKDFQIVFQDPLASLDPRMTIGQSIAEPLQSLEPELSKHEVQSRVRAIMEKVGLDPDWINRYPHEFSGGQNQRVGIARAMILKPKLIVCDEAVSALDVSIQAQIVDLILSLQAEFGMSIIFISHDLSVVRQVSHRVMVLYLGRVVELASRDAIYEDARHPYTKALISAVTVPDPRAERLKKRRELPGELPSPLDTRSALMFLKSKRIDDPDAEQYVPKLIEVAPGHFVAEHDPFEVVEMTG\e>ACN58871.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macB|antibiotic efflux|0\sMADYLLEMKNIVKEFGGVRALNGIDIKLKAGECAGLCGENGAGKSTLMKVLSAVYPHGTWDGEILWDGKPLRAQSIRETEAAGIVIIHQELMLVPELSVAENIFLGNEIKLPGGRMDYAAMNRRAEELLAELDIRDVNVVLPVKQYGGGYQQLIEIAKALNKNARLLILDEPSSSLTASEIKVLLRIIHSLKAKGVTCVYISHKLDEVADICDTIVVIRDGQHIATTPMADMNIERIIAQMVGREMNQLYPERSHVPGEVIFEARNVSCYDADNPQRKRVDNISFKLRKGEILGIAGLVGAGRTELVSALFGAYPGPSEAEVWLNGVKLDTRTPLKAIRAGLAMVPEDRKQHGIVPDLGVGHNMTLAVLNDFVRATRIDQQAELATIHKEIKSVKLKTATPFLPITSLSGGNQQKAVLSKMLLTKPKILILDEPTRGVDVGAKFEIYQLMFDLAAQGMSIIMVSSELAEVLGISDRVLVVGEGKLRGDFVNDNLSQETVLAAALDHTQPALH\e>ACN58991.1|FEATURES|NCBI|multidrug|cmeB|antibiotic efflux|0\sMKNDRGEMVPFSAFMTIKKKQGANEINRYNMYNTAAIRGGPATGYSSGEAIKAVQEVAAKNLPNGFDIDWAALSYDETRRGNEAVYIFLIVLAFVYLVLAAQYESFIIPLAVVFSLPAGVFGSFLLIKGMGLANDIYAQVGLVMLVGLLGKNAVLIVEFAVQKQQQGATVFEAAIEGARVRFRPILMTSFAFIAGLIPLVFAHGAGAIGNKTIGSSALGGMFFGTVFGVIVVPGLYYVFGSWAEGRKLIRGEDHDPLTENLVHQMDNFPQSDDK\e>ACN58776.1|FEATURES|NCBI|macrolide-lincosamide-streptogramin|macA|antibiotic efflux|0\sMGNLPRPTLSPSLSGIRPTMNRETTTRVDSSTPAARLGMRVPSTSRAALVGVAALVVILGGWYGIKRWRAHVASEGQYIFAAIQKGDIEDLVTATGSLQPRDYVDVGAQVSGQLDKILVEVGSDVKEGDLLAEIDADVAAARVDASRAQLRSQQAQLVQQQANLTKAERDLTRQQNLMKEDATTAEQVQNAETTLDTTKAQINALKAQMEQLRASMRVDESNLNYTKILAPMSGTVVSISAKQGQTLNTNQQAPTILRIADLSTMTVQTQVSEADVSKLRSGMQAYFTTLGSAGKRWYGQLKKIEPTPTVTNNVVLYNALFEVPNDNKQLLPQMTAQVFFVAAAAHDVLVVPMSAVSLQRTPPGGIPNAAAAQAAGARGAGAQGAGAQGAQGASAQGAGAQSGQGGQGAAALTPEQIARREARRQQRMQSNGGSATGGAIEGGPPRGGFGASMAARGPRHATVRVQAADGKIEERQITIGVTNRVHAEVLSGLKEGERVVAGTKEPEKAPATAGGQQGAGGQRNNIGGFPGGGLGGGFGR\e"
data = data.replace('\e>', '\r')
with io.BytesIO(data.encode('utf8')) as binary_file:
    with io.TextIOWrapper(binary_file, encoding='utf8') as file_obj:
        df = pd.read_table(file_obj, sep="|", header=None, )
df[6] = df[6].str.replace('0\s', '', regex=False)

像这样给你买一张数据文件：

​

之后，您可以使用sklearn.preprocessing.OneHotEncoder或假人编码您的蛋白质序列。我在这里展示了熊猫的版本：

df = pd.get_dummies(data=df, columns=[6])

这是一个例子，如果您的数据在一个变量中可用。如果是文本文件，则不需要io方法，应该用加载txt文件来替换。还要注意，应该用换行符(例如"\r“或"\n”)替换"\e>“来分离样本。