How to replace empty string in python

Question

I have a csv file and I read it into array, the original csv a 5-row, 8-column file with empty elements

       1  2         3        4    5    6   7         8     
Row 1:   '1 1'     '4 4'                  '2 2'   
Row 2:   '3'       '3'                    '3' 
Row 3:   '1 1 1 1' '1 1 1 1'              '2 2 2 2'
Row 4:   '2'       '4'                    '2' 
Row 5:   '4'       '4'                               '4'

I read it into my code:

[[nan '1 1' '4 4' nan nan nan '2 2' nan]
 [nan '3' '3' nan nan nan '3' nan]
 [nan '1 1 1 1' '1 1 1 1' nan nan nan '2 2 2 2' nan]
 [nan '2' '4' nan nan nan '2' nan]
 [nan '4' '4' nan nan nan nan '4']]

So what I want to get is to replace all empty elements into same number of -1 with other elements:

[['-1 -1' '1 1' '4 4' '-1 -1' '-1 -1' '-1 -1' '2 2' '-1 -1']
 ['-1' '3' '3' '-1' '-1' '-1' '3' '-1']
 ['-1 -1 -1 -1' '1 1 1 1' '1 1 1 1' '-1 -1 -1 -1' '-1 -1 -1 -1' '-1 -1 -1 -1' '2 2 2 2' '-1 -1 -1 -1']
 ['-1' '2' '4' '-1' '-1' '-1' '2' '-1']
 ['-1' '4' '4' '-1' '-1' '-1' '-1' '4']]

When I use re.match("\\d",element) , I can not get the result. So could anyone help?

Answer 1

what about :

for line in csvdata:
    multiplicity = max([len(datum.split(" ")) if isinstance(datum, str) else 0 for datum in line])
    for datum in line:
        if(not isinstance(datum, str)):
            datum = " ".join(["-1"]*multiplicity)

It looks awful to me, but it should works.

Answer 2

try this:

xs=[["nan '1 1' '4 4' nan nan nan '2 2' nan"],
    ["nan '3' '3' nan nan nan '3' nan"],
    ["nan '1 1 1 1' '1 1 1 1' nan nan nan '2 2 2 2' nan"],
    ["nan '2' '4' nan nan nan '2' nan"],
    ["nan '4' '4' nan nan nan nan '4'"]]

for x in xs:
   s = len(x[0].replace('nan','').replace(' ','').split("''")[0])-1
   r = ' '.join('v'*s).replace('v', '-1')
   r = "'%s'" % r
   x[0] = x[0].replace('nan', r)

Answer 3

I believe you should make clear in your question you are using a library (numPy). Most of the solutions will work for Python, but as you are already using numpy, this is a better solution I believe

x = np.asarray(pd.read_csv("data/org8.csv"))
x[np.isnan(x)] = -1