用python解析excel

Question

所以我現在的問題是讀取一個.txt文件並提取特定的數據。然後將這些數據寫入一個excel文件中，現在這些行將成爲列，反之亦然。到目前爲止，我已經能夠讀取文件並創建帶有列的Excel表格，但沒有數據傳輸。下面是它讀取的數據以及寫入excel的內容。

[' O/F=7.1800E+00 PERCENT FUEL= 12.2249 EQUIVALENCE RATIO=5.5559E-01 DENSITY=9.5028E-01'] 
[] 
['     CHAMBER THROAT  EXIT  EXIT'] 
[' PC/P    1.0000 1.7346 1.0083 62.915'] 
[' P', ' PSIA   1500.0 864.8 1487.7 23.84'] 
[' T', ' DEG R   5886  5555  5880  3494'] 
[' H', ' BTU/LB  -446.6 -674.1 -450.1 -1819.9'] 
[' S', ' BTU/(LB)(R) 2.3395 2.3395 2.3395 2.3395'] 
[' DEN (LBM/FT3) 6.50E-01 4.01E-01 6.45E-01 1.81E-02'] 
[' '] 
[' M', ' MOL WT  27.357 27.616 27.361 28.499'] 
[' (DLV/DLP)T  -1.01645 -1.01277 -1.01639 -1.00034'] 
[' (DLV/DLT)P  1.3300 1.2733 1.3292 1.0126'] 
[' CP', 'BTU/(LB)(R) 0.9274 0.8626 0.9265 0.4371'] 
[' CP GAS(SF)  0.4353 0.4326 0.4353 0.4041'] 
[' GAMMA GAS(SF) 1.2001 1.1993 1.2001 1.2084'] 
[' GAMMA (S)  1.1390 1.1395 1.1390 1.1949'] 
[' SON VEL', 'FT/SEC 3490.4 3375.7 3488.6 2698.9'] 
[' MU', 'LBF-S/FT2 2.01E-06 1.93E-06 2.01E-06 1.41E-06'] 
[' K', 'LBF/S-DEGR 3.16E-02 3.01E-02 3.16E-02 2.03E-02'] 
[' PRANDTL NO  0.69205 0.69371 0.69207 0.70189'] 
[' MACH NUMBER  0.0000 1.0000 0.1202 3.0726'] 
[' '] 
[' AE/AT      1.0000 4.9993 9.0000'] 
[' CSTAR', ' FT/SEC    5139  5139  5139'] 
[' CF VAC     1.233    1.757'] 
[' CF       0.657    1.614'] 
[' IVAC', 'LBF-S/LBM   197.00   280.59'] 
[' I', ' LBF-SEC/LBM   104.92   257.74'] 
[' MOL WT(MIX)  27.357 27.616 27.361 28.499'] 

下面是代碼我到目前爲止

import csv 
import sys 
import xlsxwriter 
import pandas as pd 
import argparse 

def parse_args(): 

    parser = argparse.ArgumentParser(description='Read POST run outputs.') 
    parser.add_argument('infile', 
         type=argparse.FileType('r'), 
         help='POST file to be analyzed.') 
    parser.add_argument('outfile', 
         type=argparse.FileType('w'), 
         help='Output xlsx file.') 
    return parser.parse_args() 


def read_post_file(LOX_CH4_GG_5zn.txt, LOX_CH4_GG_5zn.csv): 
    f = open(LOX_CH4_GG_5zn.txt,"r") 
    csv_f = csv.reader(f) 

relevantData = False 
firstDataSet = True 



for row in csv_f: 
    string = str(row) 
    if 'O/F' in string and firstDataSet: 
     relevantData = True 
    elif 'MOLE FRACTIONS' in string: 
     relevantData = False 
     firstDataSet = False 
    if firstDataSet and relevantData: 
     print (string) 

f.close() 

    if __name__ == "__main__": 
    args = parse_args() 
    read_post_file(args.infile.name, args.outfile.name) 



workbook = xlsxwriter.Workbook('Com.xlsx') 
worksheet = workbook.add_worksheet() 

worksheet.set_column('A:A', 20) 

bold = workbook.add_format({'bold': True}) 

worksheet.write('A1', 'O/F', bold) 
worksheet.write('B1', 'PC/P', bold) 
worksheet.write('C1', 'P,PSIA', bold) 
worksheet.write('D1', 'T,DEG(R)', bold) 
worksheet.write('E1', 'H,BTU/LB', bold) 
worksheet.write('F1', 'S,BTU/(LB)(R)', bold) 
worksheet.write('G1', 'DEN,LBM/FT3', bold) 
worksheet.write('H1', 'M,MOL WT', bold) 
worksheet.write('I1', '(DLV/DLP)T', bold) 
worksheet.write('J1', '(DLV/DLP)P', bold) 
worksheet.write('I1', 'CP,BTU/(LB)(R)', bold) 
worksheet.write('K1', 'CP GAS,SF', bold) 
worksheet.write('L1', 'GAMMA GAS,SF', bold) 
worksheet.write('K1', 'GAMMA,S', bold) 
worksheet.write('K1', 'SON VEL,FT/SEC', bold) 
worksheet.write('K1', 'MU,LBF-S/FT2', bold) 
worksheet.write('K1', 'K,LBF/S-DEG(R)', bold) 
worksheet.write('K1', 'PRANDTL NO', bold) 
worksheet.write('K1', 'MACH NUMBER', bold) 
worksheet.write('K1', 'AE/AT', bold) 
worksheet.write('K1', 'CSTAR,FT/SEC', bold) 
worksheet.write('K1', 'CF VAC', bold) 
worksheet.write('K1', 'CF', bold) 
worksheet.write('K1', 'IVAC, LBF-SEC/LBM', bold) 
worksheet.write('K1', 'I,LBF-SEC/LBM', bold) 
worksheet.write('K1', 'MOL WT(MIX)', bold) 

workbook.close() 

任何幫助是極大的讚賞一個這個。

輸入1

輸出內容是被張貼在問題的開始。

Answer 1

這是一個小型工作原型，展示瞭如何使用熊貓來做到這一點。

由於OP沒有提供輸入數據的樣本，我已經生成了一個樣本數據框：8列和20行。 在這個例子中，我將只選擇3列（'A'，'C'，'H'）並轉置它們（將列轉換爲行）。

代碼：

import six 
import numpy as np 
import pandas as pd 

# generate random DataFrame with 8 columns and 20 rows 
sample = pd.DataFrame(np.random.randint(0,100,size=(20, 8)), columns=list('ABCDEFGH')) 

csv_str = six.StringIO() 
sample.to_csv(csv_str, sep=';', index=False) 
print('sample data\n') 
print(csv_str.getvalue()) 

# save sample data into CSV file: 'sample.csv' 
sample.to_csv('sample.csv', sep=';', index=False) 

# create DF from sample data (we want to use only the following columns: 'A' 'C' 'H') 
df = pd.read_csv('sample.csv', sep=';', usecols=['A','C','H']) 
# transpose input DF 
out_df = df.T 
print(out_df) 

# save result DF as excel file 
xlwriter = pd.ExcelWriter('out.xlsx') 
out_df.to_excel(xlwriter, sheet_name='Output', index=True) 
xlwriter.save() 

輸出：

sample data 

A;B;C;D;E;F;G;H 
51;81;17;32;94;81;18;74 
37;95;13;68;83;55;26;23 
5;76;91;11;71;93;17;58 
42;11;86;52;44;39;82;90 
20;85;25;13;58;87;18;68 
49;64;25;15;19;32;49;85 
40;11;91;40;47;73;3;37 
91;67;97;21;71;56;96;86 
88;40;98;15;21;8;17;74 
22;64;28;34;8;14;2;21 
42;34;50;69;48;5;56;23 
67;97;89;70;81;50;8;75 
96;95;81;11;48;63;35;74 
36;50;84;2;99;56;25;69 
35;48;85;84;80;51;26;23 
29;53;50;21;13;40;55;92 
33;63;40;77;47;91;71;73 
69;18;15;80;83;4;23;84 
51;80;72;60;23;56;45;48 
55;4;60;87;28;82;14;63 

    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 \ 
A 51 37 5 42 20 49 40 91 88 22 42 67 96 36 35 29 33 69 51 
C 17 13 91 86 25 25 91 97 98 28 50 89 81 84 85 50 40 15 72 
H 74 23 58 90 68 85 37 86 74 21 23 75 74 69 23 92 73 84 48 

    19 
A 55 
C 60 
H 63 

產生sample CSV file

輸出Excel file

@ Z_Russ89，我會用自己的真實的輸入/輸出數據，如果你將發佈樣本輸入和預期的輸出，但你可以以這個例子爲起點。