python import data

1# Basic syntax:
2with open('/path/to/filename.extension', 'open_mode') as filename:
3  file_data = filename.readlines()	# Or filename.read() 
4# Where:
5#	- open imports the file as a file object which then needs to be read
6#		with one of the read options
7#	- readlines() imports each line of the file as an element in a list
8#	- read() imports the file contents as one long new-line-separated 
9#		string
10#	- open_mode can be one of:
11#		- "r" = Read which opens a file for reading (error if the file 
12#			doesn't exist)
13#		- "a" = Append which opens a file for appending (creates the 
14#			file if it doesn't exist)
15#		- "w" = Write which opens a file for writing (creates the file 
16#			if it doesn't exist)
17#		- "x" = Create which creates the specified file (returns an error
18#			if the file exists)
19# Note, "with open() as" is recommended because the file is closed 
20#	automatically so you don't have to remember to use file.close()
21# Note, if you're getting unwanted newline characters with this approach,
22#	you can run: file_data = filename.read().splitlines() instead
23
24# Basic syntax for a delimited file with multiple fields:
25import csv
26with open('/path/to/filename.extension', 'open_mode') as filename:
27	file_data = csv.reader(filename, delimiter='delimiter')
28    data_as_list = list(file_data)
29# Where:
30#	- csv.reader can be used for files that use any delimiter, not just
31#		commas, e.g.: '\t', '|', ';', etc. (It's a bit of a misnomer)
32#	- csv.reader() returns a csv.reader object which can be iterated 
33#		over, directly converted to a list, and etc. 
34
35# Importing data using Numpy:
36import numpy as np
37data = np.loadtxt('/path/to/filename.extension',
38				delimiter=',', 	# String used to separate values
39				skiprows=2, 	# Number of rows to skip
40				usecols=[0,2], 	# Specify which columns to read
41				dtype=str) 		# The type of the resulting array
42
43# Importing data using Pandas:
44import pandas as pd
45data = pd.read_csv('/path/to/filename.extension',
46				nrows=5, 		# Number of rows of file to read
47				header=None, 	# Row number to use as column names 
48	            sep='\t', 		# Delimiter to use 
49	            comment='#', 	# Character to split comments
50				na_values=[""])	# String to recognize as NA/NaN
51
52# Note, pandas can also import excel files with pd.read_excel()

1import pandas as pd
2
3df = pd.read_excel (r'C:\Users\Ron\Desktop\Product List.xlsx') #place "r" before the path string to address special character, such as '\'. Don't forget to put the file name at the end of the path + '.xlsx'
4print (df)
5

1you should be in the same dir as .py file 
2
3df = pd.read_csv('your_file_name.csv')