I’m currently working on a script in python. I want to convert an xls file into a txt file but I also want to clean and manage the data. In the xls files, there’s 4 columns which does interest me. Here is a sample of the txt I get from the conversion :
OPEN 0 a_inst0 signal_a OPEN 0 b_inst0 signal_b a_inst0 signal_c OPEN 0 c_inst0 signal_d OPEN 0
To get this result I used this script :
import re # Function to convert def listToStringOpen(s): str1 = "" for ele in s: str1 += ele str1 += "n" return str1 import pandas as pd df = pd.read_excel('my_xls.xlsm', sheet_name='Sheet1', usecols="A:D") with open('my_txt.txt', 'w', encoding ='utf-8', errors='ignore') as outfile: df.to_string(outfile) with open('my_txt.txt', 'r', encoding ='utf-8', errors='ignore') as f: data = f.readlines() DONOTIGNORE2 = 'OPEN' cleaned_lines = [] for line in data: if (DONOTIGNORE2 not in line) : continue cleaned_lines.append(line.rstrip()) with open('result_open.txt', 'w', encoding ='utf-8', errors='ignore') as f: f.write(listToStringOpen(cleaned_lines))
That’s a good beginning but now I’d like to remove the “OPEN 0” of each file but I don’t know how to do it because it could be placed eather in the A:B columns or in the C:D columns. Also the result in the txt is not vertically aligned :( . Do you have any ideas ?
Thanks a lot
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Answer
Please find below the updated code. This is the input I took, added a couple of rows to ensure it works fine..
Few changes:
- read_excel has
header=None
as your data did not have header - While writing to my_txt, I added
index=False, header=False
so that there is no index added to the txt file and no headers. This way your output file will only have data - I used the dataframe to clean the OPEN and ‘0’ when they are in columns A:B or C:D ONLY. Otherwise, leave them alone.
import re # Function to convert def listToStringOpen(s): str1 = "" for ele in s: str1 += ele str1 += "n" return str1 import pandas as pd df = pd.read_excel('my_xls.xlsm', sheet_name='Sheet1', usecols="A:D", header=None) with open('my_txt.txt', 'w', encoding ='utf-8', errors='ignore') as outfile: df.to_string(outfile, index=False, header=False) with open('my_txt.txt', 'r', encoding ='utf-8', errors='ignore') as f: data = f.readlines() df = df.astype(str) cleaned_lines = [] row = 0 for row in range(len(df)): print(df.iloc[row,:][0], df.iloc[row,:][1], df.iloc[row,:][2], df.iloc[row,:][3]) if ((df.iloc[row,:][0].strip() == 'OPEN') and (df.iloc[row,:][1].strip() == "0")) : df.iloc[row,:][0] = "" df.iloc[row,:][1] = "" elif ((df.iloc[row,:][2].strip() == 'OPEN') and (df.iloc[row,:][3].strip() == "0")): df.iloc[row,:][2] = "" df.iloc[row,:][3] = "" with open('result_open.txt', 'w', encoding ='utf-8', errors='ignore') as f: df.to_string(f, index=False, header=False)