{"id":780,"date":"2023-03-29T22:50:08","date_gmt":"2023-03-29T14:50:08","guid":{"rendered":"https:\/\/kuo.us.to\/wordpress\/?p=780"},"modified":"2023-03-29T22:50:10","modified_gmt":"2023-03-29T14:50:10","slug":"python%e5%ad%b8%e7%bf%92%e7%ad%86%e8%a8%98-pandas-%e6%89%b9%e6%ac%a1%e8%ae%80%e5%8f%96txt%e6%aa%94%e6%a1%88%ef%bc%8c%e6%8c%87%e5%ae%9a%e7%89%b9%e5%ae%9a%e8%b3%87%e6%96%99%ef%bc%8c%e6%89%b9%e6%ac%a1","status":"publish","type":"post","link":"https:\/\/kuo.us.to\/wordpress\/python%e5%ad%b8%e7%bf%92%e7%ad%86%e8%a8%98\/780\/","title":{"rendered":"Python\u5b78\u7fd2\u7b46\u8a18: Pandas \u6279\u6b21\u8b80\u53d6txt\u6a94\u6848\uff0c\u6307\u5b9a\u7279\u5b9a\u8cc7\u6599\uff0c\u6279\u6b21\u532f\u51faExcel\u6a94\u6848"},"content":{"rendered":"\n

\u672c\u6587\u4f86\u81ea\u65bcithelp\u7db2\u53cb\u4e4b\u767c\u554f\uff0c\u7db2\u5740\u5982\u4e0b\uff1a
https:\/\/ithelp.ithome.com.tw\/questions\/10212370<\/a><\/p>\n\n\n\n

\u56e0\u4e0a\u9762\u554f\u7b54\u8cc7\u6599\u6709\u9ede\u591a\uff0c\u7db2\u53cb\u53c8\u6709\u5f8c\u7e8c\u63d0\u554f\uff0c\u5beb\u6210\u6587\u7ae0\u6bd4\u8f03\u5bb9\u6613\u7de8\u8f2f\u3002<\/p>\n\n\n\n

\u539f\u5148\u554f\u984c\u53ca\u63d0\u554f\u5206\u985e\u62102\u984c\uff1a<\/h2>\n\n\n\n

\u7b2c1\u984c<\/h2>\n\n\n\n

test.txt\u8cc7\u6599\u6a94\u5167\u5bb9\u5982\u4e0b\uff1a<\/p>\n\n\n

\n3 i\n2 10-\n2 ,,\n1 \/ 1 cia\n0 \\ 0 0 By Pte\n\u4eba 4 6 8 \u201cPost\n-1 \/ \u201cI 5-\n2\n2 \/ TO\n-3\n4g \/ \u4eba ]\nVolume shift [ml] 15-\n\n####Flow-Volume-Curve####\n\nPred Pre %... Post %... Chg...\nsr eff 0.96 1.13 118 0.15 89 -25\nR tot 0.30 0.48 161 1.44 146 -10\nR eff 0.30 0.42 139 0.38 127 -9\nFrcpl 2.51 1.16 74 1.79 71 -4\nVT 0.59 1.71 290 0.90 154 -47\nIc 1.91 2.44 128 2.38 125 -3\nERV 1.05 0.36 35 0.53 50 45\nRV 1.46 1.50 102 1.26 16 -16\nTLC 4.44 4.31 97 4.16 94 -3\nRV%TLC 32.90 34.78 106 30.30 92 -13\nVC IN 2.96 1.02 68 1.38 47 -32\nFVC 2.91 2.81 96 2.90 100 3\nFEV 1 2.10 2.29 92 2.38 95 4\nFEV1%F 81.65 82.08 1\nPEF 6.18 6.64 107 5.43 88 -18\nMEF 75 5.57 5.79 104 4.98 89 -14\nMEF 50 3.93 2.68 68 3.10 79 16\nMEF 25 1.71 0.88 52 1.03 60 17\nMMEF 3.46 2.24 65 2.50 72 11\nFIF 50 4.18 3.94 -6\nSubstance ventolin\n<\/pre><\/div>\n\n\n
\u76ee\u6a19\uff1a\u8b80\u53d6\u300cPred Pre %\u2026 Post %\u2026 Chg\u2026\u300d\u8207\u300cSubstance ventolin\u300d\u4e4b\u9593\u7684\u5167\u5bb9\uff0c\u6574\u7406\u6210\u4ee5\u4e0b\u683c\u5f0f\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
code1\uff1a<\/p>\n\n\n
\n# \u5148\u627e\u51fa\u8b80\u53d6\u6a94\u6848\u7684\u8d77\u59cb\u548c\u7d50\u675f\u884c\nimport pandas as pd\nimport re\n\nfile = 'test.txt'\n\n# \u8a2d\u5b9a\u7a7a\u7684\u7d22\u5f15\nindexes = []\nwith open(file) as f:        \n    lines = f.readlines()\n    for i, line in enumerate(lines):\n        # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u8d77\u59cb\u4f4d\u7f6e\n        if line.startswith('Pred Pre %... Post %... Chg...'):\n            # \u627e\u5230\u8d77\u59cb\u4f4d\u7f6e\u5f8c\uff0c\u4e0b\u4e00\u884c\u624d\u958b\u59cb\u8b80\u53d6\n            s = i+1\n        # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u7d50\u675f\u4f4d\u7f6e\n        elif line.startswith('Substance ventolin'):\n            e = i\n            indexes.append((s, e))  \n        else:\n            pass\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u82f1\u6587\u540d\u5b57\nresult_name = []\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u6578\u64da\nresult_data = []\n\n# \u8b80\u53d6\u8d77\u59cb\u548c\u7d50\u675f\u4f4d\u7f6e\u4e2d\u9593\u7684\u8cc7\u6599\nfor line in lines[s:e]:\n    \n    # \u9019\u908a\u662f\u7528ccutmis\u524d\u8f29\u7684Regex\u4f86\u5c0b\u627e\u8207\u5207\u5272\u8cc7\u6599\uff1a\n    temp = re.findall('(^[A-Za-z%]+.*[A-Za-z%].)(.*)$', line)\n    \n    # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u82f1\u6587\u540d\u5b58\u5230result_name\n    result_name.append(temp[0][0])\n    \n    # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u6578\u64da\u5b58\u5230result_name\n    result_data.append(temp[0][1].split(' '))\n\n\ndf_name = pd.DataFrame(result_name)\ndf_data = pd.DataFrame(result_data)\n\n# \u5c07\u4ee5\u4e0a\u76842\u500bdataframe \u4e32\u63a5\ndf = pd.concat([df_name, df_data], axis=1)\n\n# \u5c07\u6b04\u540d\u4fee\u6b63\u70ba\u300ccol_1......, col_x\u300d\ndf.columns=['col_' + str(x) for x in range(1, len(df.columns)+1)]\n\ndf\n<\/pre><\/div>\n\n\n
\u7d50\u679c\u5982\u4e0b\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u7b2c2\u984c<\/h2>\n\n\n\n
\u5047\u8a2d\u67093\u500btext\u6a94\u6848\uff0c\u8cc7\u6599\u5206\u5225\u5982\u4e0b\uff1a<\/p>\n\n\n\n
test1.txt\uff1a<\/p>\n\n\n
\n3 i\n2 10-\n2 ,,\n1 \/ 1 cia\n0 \\ 0 0 By Pte\n\u4eba 4 6 8 \u201cPost\n-1 \/ \u201cI 5-\n2\n2 \/ TO\n-3\n4g \/ \u4eba ]\nVolume shift [ml] 15-\n\n####Flow-Volume-Curve####\n\nPred Pre %... Post %... Chg...\nsr eff 0.96 1.13 118 0.15 89 -25\nR tot 0.30 0.48 161 1.44 146 -10\nR eff 0.30 0.42 139 0.38 127 -9\nFrcpl 2.51 1.16 74 1.79 71 -4\nVT 0.59 1.71 290 0.90 154 -47\nSubstance ventolin\n<\/pre><\/div>\n\n\n
test2.txt\uff1a<\/p>\n\n\n
\n3 i\n2 10-\n2 ,,\n1 \/ 1 cia\n0 \\ 0 0 By Pte\n\u4eba 4 6 8 \u201cPost\n-1 \/ \u201cI 5-\n2\n2 \/ TO\n-3\n4g \/ \u4eba ]\nVolume shift [ml] 15-\n\n####Flow-Volume-Curve####\n\nPred Pre %... Post %... Chg...\nIc 1.91 2.44 128 2.38 125 -3\nERV 1.05 0.36 35 0.53 50 45\nRV 1.46 1.50 102 1.26 16 -16\nTLC 4.44 4.31 97 4.16 94 -3\nRV%TLC 32.90 34.78 106 30.30 92 -13\nVC IN 2.96 1.02 68 1.38 47 -32\nFVC 2.91 2.81 96 2.90 100 3\nSubstance ventolin\n<\/pre><\/div>\n\n\n
test3.txt\uff1a<\/p>\n\n\n
\n3 i\n2 10-\n2 ,,\n1 \/ 1 cia\n0 \\ 0 0 By Pte\n\u4eba 4 6 8 \u201cPost\n-1 \/ \u201cI 5-\n2\n2 \/ TO\n-3\n4g \/ \u4eba ]\nVolume shift [ml] 15-\n\n####Flow-Volume-Curve####\n\nPred Pre %... Post %... Chg...\nFEV 1 2.10 2.29 92 2.38 95 4\nFEV1%F 81.65 82.08 1\nPEF 6.18 6.64 107 5.43 88 -18\nMEF 75 5.57 5.79 104 4.98 89 -14\nMEF 50 3.93 2.68 68 3.10 79 16\nMEF 25 1.71 0.88 52 1.03 60 17\nMMEF 3.46 2.24 65 2.50 72 11\nFIF 50 4.18 3.94 -6\nSubstance ventolin\n<\/pre><\/div>\n\n\n
\u76ee\u6a192-1\uff1a\u6279\u6b21\u8b80\u53d6text\u6a94\u6848\uff0c\u8655\u7406\u5b8c\u5f8c\uff0c\u8f38\u51fa\u6210\u4e00\u500btest.xlsx\u6a94\u6848\uff0c\u5206\u6210\u300ctest1, test2, test3\u300d\u4e09\u500b\u5de5\u4f5c\u8868\u3002
\u76ee\u6a192-2\uff1a\u6279\u6b21\u8b80\u53d6text\u6a94\u6848\uff0c\u8655\u7406\u5b8c\u5f8c\u7d50\u5408\u6240\u6709\u8cc7\u6599\uff0c\u8f38\u51fa\u6210\u4e00\u500btest.xlsx\u6a94\u6848\u3002<\/p>\n\n\n\n
code 2-0\uff1a<\/p>\n\n\n
\nimport glob\nimport re\nimport pandas as pd\n\n# \u5047\u8a2d\u6240\u6709\u7684text\u6a94\u6848\u653e\u572820230329_test\u7684\u76ee\u9304\u4e0b\nfiles = glob.glob('.\/20230329_test\/*.txt')\n\n# \u5148\u5370\u51fa\u6240\u6709\u7684\u6a94\u6848\nfiles\n<\/pre><\/div>\n\n\n
\u7d50\u679c\u5982\u4e0b\uff1a
[‘.\/20230329_test\\test1.txt’,
‘.\/20230329_test\\test2.txt’,
‘.\/20230329_test\\test3.txt’]<\/p>\n\n\n\n
code 2-1\uff1a<\/p>\n\n\n
\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8ff4\u5708\u7684\u6240\u6709dataframe\ndf_list = []\n\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58dataframe\u7684\u5de5\u4f5c\u8868\u540d\u7a31\nsheet_list = []\n\n# \u8ff4\u5708\u8b80\u53d6\u6240\u6709\u8981\u8655\u7406\u7684\u6a94\u6848\nfor file in files:\n    \n    # \u5c07txt\u7684\u6a94\u6848\u540d\u7a31\u4e0d\u542b\u526f\u6a94\u540d\u5b58\u5165sheet_name\n    sheet_list.append(file[-9:-4])\n    \n    # \u5148\u627e\u51fa\u8b80\u53d6\u6a94\u6848\u7684\u8d77\u59cb\u548c\u7d50\u675f\u884c\n    with open(file) as f:  \n        s, e = None, None\n        lines = f.readlines()\n        for i, line in enumerate(lines):\n    \n            # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u8d77\u59cb\u4f4d\u7f6e\n            if line.startswith('Pred Pre %... Post %... Chg...'):\n            \n                # \u627e\u5230\u8d77\u59cb\u4f4d\u7f6e\u5f8c\uff0c\u4e0b\u4e00\u884c\u624d\u958b\u59cb\u8b80\u53d6\n                s = i+1\n            \n            # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u7d50\u675f\u4f4d\u7f6e\n            elif line.startswith('Substance ventolin'):\n                e = i\n                  \n            else:\n                pass\n    \n    # \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u82f1\u6587\u540d\u5b57\n    result_name = []\n    \n    # \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u6578\u64da\n    result_data = []\n    \n    # \u8b80\u53d6\u8d77\u59cb\u548c\u7d50\u675f\u4f4d\u7f6e\u4e2d\u9593\u7684\u8cc7\u6599\n    for line in lines[s:e]:\n        \n        # \u9019\u908a\u662f\u7528ccutmis\u524d\u8f29\u7684Regex\u4f86\u5c0b\u627e\u8207\u5207\u5272\u8cc7\u6599\uff1a\n        temp = re.findall('(^[A-Za-z%]+.*[A-Za-z%].)(.*)$', line)\n        \n        # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u82f1\u6587\u540d\u5b58\u5230result_name\n        result_name.append(temp[0][0])\n        \n        # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u6578\u64da\u5b58\u5230result_name\n        result_data.append(temp[0][1].split(' '))\n    \n    \n    df_name = pd.DataFrame(result_name)\n    df_data = pd.DataFrame(result_data)\n    \n    # \u5c07\u4ee5\u4e0a\u76842\u500bdataframe \u4e32\u63a5\n    df = pd.concat([df_name, df_data], axis=1)\n    \n    # \u5c07\u6b04\u540d\u4fee\u6b63\u70ba\u300ccol_1......, col_x\u300d\n    df.columns=['col_' + str(x) for x in range(1, len(df.columns)+1)]\n    \n    # \u5c07dataframe\u5b58\u5165df_list\n    df_list.append(df)\n\n# \u5c07\u4e0a\u9762\u8655\u7406\u5b8c\u7684\u8cc7\u6599\u5206\u62103\u500b\u5de5\u4f5c\u8868\uff0c\u5b58\u5165\u539f\u5148\u8cc7\u6599\u5b58\u4e2d\u7684test.xlsx\nw = pd.ExcelWriter('.\/20230329_test\/test.xlsx')\nfor a, b in zip(sheet_list, df_list):\n    b.to_excel(w, sheet_name=f'{a}', index=False)\nw.close()\n<\/pre><\/div>\n\n\n
\u7d50\u679c\u5982\u4e0b\uff1a
test1\u5de5\u4f5c\u8868<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u6ce8\u610ftest3\u5de5\u4f5c\u8868\u662fcol_1-col_8<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
code 2-2\uff1a<\/p>\n\n\n
\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8ff4\u5708\u7684\u6240\u6709dataframe\ndf_list = []\n\n# \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58dataframe\u7684\u5de5\u4f5c\u8868\u540d\u7a31\uff0c\u9019\u500b\u7528\u4e0d\u5230\u4e86!!\n#sheet_list = []\n\n# \u8ff4\u5708\u8b80\u53d6\u6240\u6709\u8981\u8655\u7406\u7684\u6a94\u6848\nfor file in files:\n    \n    # \u5c07txt\u7684\u6a94\u6848\u540d\u7a31\u4e0d\u542b\u526f\u6a94\u540d\u5b58\u5165sheet_name\uff0c\u9019\u500b\u7528\u4e0d\u5230\u4e86!!\n    #sheet_list.append(file[-9:-4])\n    \n    # \u5148\u627e\u51fa\u8b80\u53d6\u6a94\u6848\u7684\u8d77\u59cb\u548c\u7d50\u675f\u884c\n    with open(file) as f:  \n        s, e = None, None\n        lines = f.readlines()\n        for i, line in enumerate(lines):\n    \n            # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u8d77\u59cb\u4f4d\u7f6e\n            if line.startswith('Pred Pre %... Post %... Chg...'):\n            \n                # \u627e\u5230\u8d77\u59cb\u4f4d\u7f6e\u5f8c\uff0c\u4e0b\u4e00\u884c\u624d\u958b\u59cb\u8b80\u53d6\n                s = i+1\n            \n            # \u641c\u5c0b\u6a94\u6848\u8981\u8b80\u53d6\u7684\u7d50\u675f\u4f4d\u7f6e\n            elif line.startswith('Substance ventolin'):\n                e = i\n                  \n            else:\n                pass\n    \n    # \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u82f1\u6587\u540d\u5b57\n    result_name = []\n    \n    # \u8a2d\u5b9a\u7a7a\u7684list\u5132\u5b58\u8981\u6574\u7406\u7684\u6578\u64da\n    result_data = []\n    \n    # \u8b80\u53d6\u8d77\u59cb\u548c\u7d50\u675f\u4f4d\u7f6e\u4e2d\u9593\u7684\u8cc7\u6599\n    for line in lines[s:e]:\n        \n        # \u9019\u908a\u662f\u7528ccutmis\u524d\u8f29\u7684Regex\u4f86\u5c0b\u627e\u8207\u5207\u5272\u8cc7\u6599\uff1a\n        temp = re.findall('(^[A-Za-z%]+.*[A-Za-z%].)(.*)$', line)\n        \n        # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u82f1\u6587\u540d\u5b58\u5230result_name\n        result_name.append(temp[0][0])\n        \n        # \u539f\u59cb\u8cc7\u6599\u4e2d\u7684\u6578\u64da\u5b58\u5230result_name\n        result_data.append(temp[0][1].split(' '))\n    \n    \n    df_name = pd.DataFrame(result_name)\n    df_data = pd.DataFrame(result_data)\n    \n    # \u5c07\u4ee5\u4e0a\u76842\u500bdataframe \u4e32\u63a5\n    df = pd.concat([df_name, df_data], axis=1)\n    \n    # \u5c07\u6b04\u540d\u4fee\u6b63\u70ba\u300ccol_1......, col_x\u300d\n    df.columns=['col_' + str(x) for x in range(1, len(df.columns)+1)]\n    \n    # \u5c07dataframe\u5b58\u5165df_list\n    df_list.append(df)\n\n# \u5c073\u500b\u6a94\u6848\u4e32\u63a5\ndf_all = pd.concat(df_list, axis=0).reset_index(drop=True)\n\n# \u4e32\u63a5\u5f8c\u7684\u6a94\u6848\u5b58\u5165\u539f\u5148\u8cc7\u6599\u5b58\u4e2d\u7684test.xlsx\ndf_all.to_excel('.\/20230329_test\/test.xlsx', index=False)\n\n<\/pre><\/div>\n\n\n
\u7d50\u679c\u5982\u4e0b\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"
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