importar datos desde un archivo de texto ejemplo de código python

Si hallas algún error con tu código o proyecto, recuerda probar siempre en un ambiente de testing antes aplicar el código al proyecto final.

Ejemplo: datos de importación de python

# Basic syntax:withopen('/path/to/filename.extension','open_mode')as filename:
  file_data = filename.readlines()# Or filename.read() # Where:#	- open imports the file as a file object which then needs to be read#		with one of the read options#	- readlines() imports each line of the file as an element in a list#	- read() imports the file contents as one long new-line-separated #		string#	- open_mode can be one of:#		- "r" = Read which opens a file for reading (error if the file #			doesn't exist)#		- "a" = Append which opens a file for appending (creates the #			file if it doesn't exist)#		- "w" = Write which opens a file for writing (creates the file #			if it doesn't exist)#		- "x" = Create which creates the specified file (returns an error#			if the file exists)# Note, "with open() as" is recommended because the file is closed #	automatically so you don't have to remember to use file.close()# Note, if you're getting unwanted newline characters with this approach,#	you can run: file_data = filename.read().splitlines() instead# Basic syntax for a delimited file with multiple fields:import csv
withopen('/path/to/filename.extension','open_mode')as filename:
	file_data = csv.reader(filename, delimiter='delimiter')
    data_as_list =list(file_data)# Where:#	- csv.reader can be used for files that use any delimiter, not just#		commas, e.g.: 't', '|', ';', etc. (It's a bit of a misnomer)#	- csv.reader() returns a csv.reader object which can be iterated #		over, directly converted to a list, and etc. # Importing data using Numpy:import numpy as np
data = np.loadtxt('/path/to/filename.extension',
				delimiter=',',# String used to separate values
				skiprows=2,# Number of rows to skip
				usecols=[0,2],# Specify which columns to read
				dtype=str)# The type of the resulting array# Importing data using Pandas:import pandas as pd
data = pd.read_csv('/path/to/filename.extension',
				nrows=5,# Number of rows of file to read
				header=None,# Row number to use as column names 
	            sep='t',# Delimiter to use 
	            comment='#',# Character to split comments
				na_values=[""])# String to recognize as NA/NaN# Note, pandas can also import excel files with pd.read_excel()

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