python read file
# Basic syntax: with open('/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() # Basic syntax for a delimited file with multiple fields: import csv with open('/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()