Dump a NumPy array into a csv file

tofile is a convenient function to do this:

import numpy as np
a = np.asarray([ [1,2,3], [4,5,6], [7,8,9] ])
a.tofile('foo.csv',sep=',',format='%10.5f')

The man page has some useful notes:

This is a convenience function for quick storage of array data. Information on endianness and precision is lost, so this method is not a good choice for files intended to archive data or transport data between machines with different endianness. Some of these problems can be overcome by outputting the data as text files, at the expense of speed and file size.

Note. This fuction does not produce multi-line csv files, it saves everything to one line.

savetxt may just be sufficient.

If you want to save your numpy array (e.g. your_array = np.array([[1,2],[3,4]])) to one cell, you could convert it first with your_array.tolist().

Then save it the normal way to one cell, with delimiter=';' and the cell in the csv-file will look like this [[1, 2], [2, 4]]

Then you could restore your array like this: your_array = np.array(ast.literal_eval(cell_string))

Writing record arrays as CSV files with headers requires a bit more work.

This example reads a CSV file with the header on the first line, then writes the same file.

import numpy as np

# Write an example CSV file with headers on first line
with open('example.csv', 'w') as fp:
    fp.write('''\
col1,col2,col3
1,100.1,string1
2,222.2,second string
''')

# Read it as a Numpy record array
ar = np.recfromcsv('example.csv')
print(repr(ar))
# rec.array([(1, 100.1, 'string1'), (2, 222.2, 'second string')], 
#           dtype=[('col1', '<i4'), ('col2', '<f8'), ('col3', 'S13')])

# Write as a CSV file with headers on first line
with open('out.csv', 'w') as fp:
    fp.write(','.join(ar.dtype.names) + '\n')
    np.savetxt(fp, ar, '%s', ',')

Note that this example does not consider strings with commas, which would require quotes.

It's easy and fast with pandas

import pandas as pd 
df = pd.DataFrame(np_array)
df.to_csv("file_path.csv")