How to read a txt with pandas and correctly put it in a dataframe to be converted to excel

Question

I just started web scraping. My scraped data has to be transformed into an xlsx file. I changed the text file to look like a csv so that it could subsequently be changed in Excel. txt appears as follows: info about energy levels in Brazil, I generated the following data frame information: dataframe result  FURNAS row is set as an index row in the first line, but I want it to be a regular row.

I've tried using index = None and setting a row of white characters, but all I want is an excel table without any index rows or columns.

Answer 1

It appears that you wish to create an XLSX file without an index using the scraped data. You can try the following actions to do this:

1. Make sure you have the required libraries installed. You will need pandas and openpyxl. If you don't have them installed, you can install them using:

pip install pandas openpyxl

1. Assuming you have your data in a CSV-like txt file, first read the contents into a pandas DataFrame:

import pandas as pd

file_path = "your_file.txt"
df = pd.read_csv(file_path, delimiter=";")

# It's recommended to display the DataFrame to see its current structure
print(df.head())

1. If the FURNAS row is set as the index row, reset the index to make it a regular row:

df.reset_index(inplace=True)

1. Save the DataFrame to an Excel file without an index and header (if you don't want the column names as well):

output_file_path = "output.xlsx"
df.to_excel(output_file_path, index=False, header=None, engine='openpyxl')

1. After running these steps, you should have an XLSX file without any index rows or columns. Be sure to replace your_file.txt with the correct filename and path of your txt file and output.xlsx with the desired output filename and path.