为什么在解析之前循环数据框中的列会导致索引错误，Python 3.6+？

Question

这是在上一篇文章 (regex match not working on simple string with Pyteomics parser) 之后发布的

我从 20,000 个字符串中生成了 >50,000 个字符串的数据框 (pep_df)。但是，我现在要做的是将 str 解析为单个字符并将这些列表返回到字典（pep_dict）中。我不断收到错误消息：

这是数据框的示例：

{'sequence': {0: 'VISYGGCVAQLFIFLALGSTECLLLAVMCFDR',
  1: 'TEQGDSAAYLR',
  2: 'DSLQVSK',
  3: 'GSDALSETSSVSHIEDLEK',
  4: 'QTDPQSSSAK',
  5: 'IFGFQAGLTSLDCSGSYCLPVPVIPSFSTALYGK',
  6: 'YQTEAVEMMDQIVHWVQEDASGLGRPQLQGAPAAEPMAVPMMLLNLVEQLGEADEELAGK',
  7: 'QLEFAAQYPPTFDR',
  8: 'EWPGDLYNNSVIVQAVR',
  9: 'QIWHPNQTCDAAR',
  10: 'YEHAFESSQK',
  11: 'FISQWCGGLPSTSFSFQ',
  12: 'QPSAFIVTQHPLPNTVK',
  13: 'EVASNSELVQSSR',
  14: 'ISHVSGYNYGIPHSCIR',
  15: 'NALQYIHDGSSTR',
  16: 'LDGGSGSTSSSGCHPGGAR',
  17: 'LSLDQALVK',
  18: 'ASAELLR',
  19: 'SDSGPYPLTAR',
  20: 'MGYFLPDDYK',
  21: 'TEIQTLFK',
  22: 'VFQPSVPATK',
  23: 'ETVPSMETGDLCADTAPTPK',
  24: 'GDDCLMK',
  25: 'EGHCLAQDVEEQAR',
  26: 'FEEITGVINPALDK',
  27: 'STSTPTSPGPR',
  28: 'ELPLHGR',
  29: 'YIIIGDMGVGK',
  30: 'TTCCCPSCCVSSCCRPQCCQSVCCQPTCCRPSCCISSCCHPSCCESSCCRPCCCVRPVCGR',
  31: 'VTTFEHQYVSAIK',
  32: 'VVSHPSGVLELHMK',
  33: 'NITFDACLIQMFLIHFFSMMESGILLAMSFDR',
  34: 'YPVPEESQEGTFVGNVAQDFLLDTDSLSAR',
  35: 'HVVMELK',
  36: 'VQWGLVMCFLSYFGTFAVEFR',
  37: 'FEGGAEGR',
  38: 'NLSALSDWYSVYTSAIAFTVYMNAVWHGWAIPLFLFLAILR',
  39: 'TFSYGSSLIQHR',
  40: 'TNTTAVGISKPANIHVK',
  41: 'VPQLGPR',
  42: 'TDDCHPWVLPVVK',
  43: 'LCCAGHDR',
  44: 'QQYLCQPLLDAVLANIR',
  45: 'IYEQLPEVQK',
  46: 'LYLTQAAGLEVPPEEMSLELPETHIEEK',
  47: 'TIEDFESMNTYLQTSPSSVFTSK',
  48: 'AGSVFGEISLLAAGGGNR',
  49: 'QTIIGQPMSVTITTK',
  50: 'ASDQCLK',
  51: 'KPPGELLVSLEELEK',
  52: 'ALSQPSSYSPSCTSSK',
  53: 'LCPYFFANQEFYSLDSQLPIWGVR',
  54: 'QFYEEELINSVVISQLSHIPEDK',
  55: 'IEPMLETLENLSSR',
  56: 'DALQLEMSLVQAR',
  57: 'CHCGEPEHEETPENR',
  58: 'SVSNAATR',
  59: 'GFSQQEVQFEPELFHNTIVCEKPNNHLNK',
  60: 'GAHIMNSTCAAMPK',
  61: 'SDLGPSYGGWQVLDATPQER',
  62: 'NEDACPVGTVSAAPWGSSSILPISWAYIK',
  63: 'VLLEPLRPWACPR',
  64: 'DSMTTENGK',
  65: 'SSSYADPWTPPR',
  66: 'VEDSHQILSQTSHDLNECSWSLNILAINKPQNK',
  67: 'FLASVLPACGDLSFQQDQMTQTFGFR',
  68: 'LHLQQHVSMEFLK',
  69: 'MSNTQAER',
  70: 'SALIVHQR',
  71: 'TPELHLSGK',
  72: 'EAFLSDR',
  73: 'LYILFAAPPEK',
  74: 'EKPFACTECGK',
  75: 'AHCGPAELCEFYSR',
  76: 'STDTSCQMAGLR',
  77: 'GMLEPVQRPDVVLMGAGYR',
  78: 'STLFLIPLFGIHYIIFNFLPDNAGLGIR',
  79: 'NASGHTGDR',
  80: 'NLTVSVHVSPVEGLCLAGGGGLAQQVLVPAGSARPVAFSVVPTAAAAVSLK',
  81: 'DLHFDPSNAVVHVGGVLCVEITMYSQMPVPVHVEQIVVNVHFSIEK',
  82: 'ETGLCADFHPSGAVVAVGLNTGR',
  83: 'LIQPHVQASNNCWEEAISQVDK',
  84: 'HLNSILVLDLR',
  85: 'CQEQAQTTDWR',
  86: 'HGYMIVGDPMGGK',
  87: 'LNVPQVLLPFGR',
  88: 'SASACSTPTHTPQDSLTGVGGDVQEAFAQSSR',
  89: 'MHFFNVPEPDGHIISPLLAGFYMFWTMIILLQVLIPISLYVSIEIVK',
  90: 'LFGPGFANSSWSWVAPEGAGCR',
  91: 'GGSAPGPDPSCWFDPNNICGGGLEPGLVFLGFLLVVGMGLAGAFLAHYVR',
  92: 'AGYEGDGTLCSEMDPCTGLTPGGCSR',
  93: 'FMPLDQWLYFDALDCLPEDGELLPSPEDCALR',
  94: 'VCFNLGR',
  95: 'NLSPTPASPNQGPPPQVPVSPGPPK',
  96: 'SAHALLLPDDPPCHDLGCHPVLTVSWVLGCTLALVVSAFFVLNHLWLWAQACCSHR',
  97: 'QGVLAVIDAYNTSNK',
  98: 'DLEMFAR',
  99: 'GFCMSTLR',
  100: 'YGVIYSTPLPEK'}
}

这是不起作用的自定义函数：

def ButcherShop(df, target, rule, min_length=7,exception=None,max_legnth=100, pH=2.0):
    raw = df[target]
    string_catcher=re.compile(r'^([A-Z]+)$')
    unique_peptides = set()
    for peptide in raw:
        new_peptides = parser.cleave(peptide, rule=rule,min_length=min_length,exception=exception)
        unique_peptides.update(new_peptides)
    print(f'Done,{len(unique_peptides)} sequences of >= 7 amino acids!')
    pep_dic = [{'sequence': i} for i in unique_peptides]
    pep_df = pd.DataFrame.from_dict(pep_dic)
    for i, row in pep_df.iterrows():
        unique_id = i
        peptides = row['sequence']
        pep_dic['parsed_sequence'] = re.findall(string_catcher,peptides)
        pep_dic['xlength'] = len(peptides)
        pep_dic['charge'] = int(round(electrochem.charge(peptides, pH=pH)))
        pep_dic['mass']=int(round(Peptide_mass(peptides)))
    pep_dic = [peptide for peptide in pep_dic if peptide['length'] <= int(max_length)]
    return unique_peptides,pep_dic, pep_df

如果我能在这方面得到任何帮助，我将不胜感激。

更新的解决方案：

def ButcherShop(df, target, rule, min_length=7,exception=None,max_length=100, pH=2.0):
    raw = df[target]
    string_catcher=re.compile(r'^([A-Z]+)$')
    unique_peptides = set()
    for peptide in raw:
        new_peptides = parser.cleave(peptide, rule=rule,min_length=min_length,exception=exception)
        unique_peptides.update(new_peptides)
    print(f'Done,{len(unique_peptides)} sequences of >= 7 amino acids!')
    pep_dic = [{'sequence': i} for i in unique_peptides]
    for row in pep_dic:
        peptides = row['sequence']
        row['parsed_sequence'] = re.findall(string_catcher,peptides)
        row['length'] = len(peptides)
        row['charge'] = int(round(electrochem.charge(peptides, pH=pH)))
        row['mass']=int(round(Peptide_Mass(peptides)))
    pep_dic = [peptide for peptide in pep_dic if peptide['length'] <= int(max_length)]
    pep_df = pd.DataFrame.from_dict(pep_dic)
    return unique_peptides,pep_dic, pep_df

Answer 1

pep_dic 是字典列表，而不是单个字典。您需要遍历它，而不是遍历数据框。

此外，您正在分配字典的 xlength 键，但在最后过滤时检查 length。其中一个需要更改以保持一致。

for row in pep_dic:
    peptides = row['sequence']
    row['parsed_sequence'] = re.findall(string_catcher,peptides)
    row['length'] = len(peptides)
    row['charge'] = int(round(electrochem.charge(peptides, pH=pH)))
    row['mass']=int(round(Peptide_mass(peptides)))

pep_dic = [peptide for peptide in pep_dic if peptide['length'] <= int(max_length)]