Python 将列表的 CSV 部分转换为 Pandas 数据框

Question

我正在提取一个包含许多不同数据的文本文件：序列号、类型和 csv 数据日志：A123>A123>读snSN = 12143A123>读取 cms-sncms-sn = 12143-00000000-0000A123>读取 fw-revfw-rev = 1.3, 1.3A123>读取日志日志 =1855228,1,0,41,-57,26183,25,22,21,22,0,0,0,89,2048,500,0,01855240,1,0,33,0,26319,25,22,22,23,0,0,0,89,2048,500,0,02612010,1,0,41,-82,26122,20,21,21,21,0,0,0,87,2048,500,0,02612142,1,0,49,301,27607,21,22,21,21,0,0,0,81,2048,500,0,0这是我到目前为止的代码：import pandas as pdlines = []                  # Declare an empty list named "lines"with open ('03-22-2019.txt', 'rt') as in_file:  # Open file     for line in in_file:  # For each line of text in in_file, where the data is named "line",        lines.append(line.rstrip('\n'))   # add that line to our list of lines, stripping newlines.    while('' in lines):        lines.remove("")lines = [x for x in lines if 'A123' not in x]  #delete all lines with 'A123'for element in lines:            # For each element in our list,        print(element)              # print it.        split_line = lines[0].split()  # create list with serial number lineSerial_Num = split_line[-1]print(Serial_Num)split_line = lines[1].split()  # go to line with CMS SNCMS_SN = split_line[-1]print(CMS_SN)split_line = lines[2].split()Firm_Rev_1 = split_line[-1]Firm_Rev_2 = split_line[-2]print(Firm_Rev_1)print(Firm_Rev_2)                                  #  Problem section starts here!start_data = lines.index("log =") + 1                   #<<<<<<<<<<data = [x for x in lines[start_data:].split(",")]       #<<<<<<<<<<#dfObj = pd.DataFrame(lines[start_data:-1].split(","))  #<<<<<<<<<<当我尝试将数据的日志部分导入数据帧并将 CSV 值拆分到它们自己的列中时，问题就出现了。我如何以编程方式找到日志数据的开头，并将数据从那里读到最后到 Pandas 数据帧中？

Answer 1

看起来你很接近。

# this will get you a list of lists for each line.

data = [line.split(',') for line in lines[start_data:]]

# This should construct your data frame

dfObj = pd.DataFrame(data=data, columns=[list, of, column, names])