I have 109 csv files that I want to import using a function or a for-loop. So far I have imported the files manually using the following function:
import numpy as np
plain_table1 = np.genfromtxt('File-path\File-name1.csv', delimiter=',')
...
plain_table109 = np.genfromtxt('File-path\File-name109.csv', delimiter=',')
Is there a simpler way to import all the data files without having to type all of them in manually?
Using a dictionary comprehension, you can construct a dictionary to store your data, using numeric keys to identify arrays:
import numpy as np
d = {i: np.genfromtxt(f'File-path\File-name{i}.csv', delimiter=',') \
for i in range(1, 110)}
Then access, for example, the array in File-name100.csv via d[100].
In its simplest form, use a for loop and a range (assuming that your file names are really numbered 1 through 109). Inside the loop, you could append to a list:
import numpy as np
first = 1
last = 109
plain_tables = []
for i in range(first, last + 1):
plain_tables.append(np.genfromtxt('File-path\File-name%s.csv' % i, delimiter=',')
Note the %s in the string. That's a placeholder. Together with the % operator this can be used to get a variable into a string.
Other features exist in Python to do the same, like list comprehensions:
plain_tables = [np.genfromtxt('File-path\File-name%s.csv' % i, delimiter=',')
for i in range(first, last + 1)]
This should do the work for any number of files as long as all are '.CSV'
import numpy as np
from os import listdir, path
plain_table = {file: np.genfromtxt(path.join(File-path,file), delimiter=',') for file in listdir(FolderPath)}
print(len(plain_table))
var1, var2, var3, ... varN- you probably should use lists (or higher dimensional arrays) instead.