In this article, we are going to see different methods to save a NumPy array into a CSV file. CSV file format is the easiest and useful format for storing data
There are different methods by which we can save the NumPy array into a CSV file
Convert a NumPy array into a CSV using Dataframe.to_csv()
This method is used to write a Dataframe into a CSV file. Converting the array into pandas Dataframe and then saving it to CSV format.
Python3
# import necessary librariesimport pandas as pdimport numpy as np# create a dummy arrayarr = np.arange(1,11).reshape(2,5)# display the arrayprint(arr)# convert array into dataframeDF = pd.DataFrame(arr)# save the dataframe as a csv fileDF.to_csv("data1.csv") |
Output:
Convert a NumPy array into a CSV using numpy_array.tofile()
This method is used to write an array into the file. Create an array then save it into a CSV file.
Python3
# import the necessary libraryimport numpy as np# create a dummy arrayarr = np.arange(1,11)# display the arrayprint(arr)# use the tofile() method# and use ',' as a separator# as we have to generate a csv filearr.tofile('data2.csv', sep = ',') |
Output:
Convert a NumPy array into a CSV using numpy.savetext()
This method is used to save an array to a text file. Create an array then save it as a CSV file.
Python3
# import numpy libraryimport numpy# create an arraya = numpy.array([[1, 6, 4], [2, 4, 8], [3, 9, 1]])# save array into csv filenumpy.savetxt("data3.csv", a, delimiter = ",") |
Output:
Convert a NumPy array into a CSV using file handling
A formatter inserts one or more replacement fields and placeholders into a string by using the str.format function and a pair of curly braces (). The value will be inserted into the placeholders and joined to the string that is supplied as input to the format function. The with is used to write in the CSV file.
Python3
# import numpy libraryimport numpy# create an arraya = numpy.array([[1, 6, 4], [2, 4, 8], [3, 9, 1], [11, 23, 43]])# save array into csv filerows = ["{},{},{}".format(i, j, k) for i, j, k in a]text = "\n".join(rows)with open('data3.csv', 'w') as f: f.write(text) |
Output:
