convert nan value to zero

Question

I have a 2D numpy array  Some of the values in this array are NaN  I want to perform certain operations using this array  For example consider the array        0    43    67     0    38      100    86    96   100    94       76    79    83    89    56       88    NaN   67    89    81       94    79    67    89    69       88    79    58    72    63       76    79    71    67    56       71    71    NaN   56   100      I am trying to take each row  one at a time  sort it in reversed order to get max 3 values from the row and take their average  The code I tried is     nparr is a 2D numpy array for entry in nparr      sortedentry   sorted entry  reverse True      highest 3 values   sortedentry  3      avg highest 3   float sum highest 3 values     3   This does not work for rows containing NaN  My question is  is there a quick way to convert all NaN values to zero in the 2D numpy array so that I have no problems with sorting and other things I am trying to do

User · Answer

How about nan to num

User · Answer

For your purposes  if all the items are stored as str and you just use sorted as you are using and then check for the first element and replace it with  0    gt  gt  gt  l1     88   NaN   67   89   81    gt  gt  gt  n   sorted l1 reverse True    NaN    89    88    81    67    gt  gt  gt  import math  gt  gt  gt  if math isnan float n 0             n 0     0        gt  gt  gt  n   0    89    88    81    67

User · Answer

You can use lambda function  an example for 1D array    import numpy as np a    np nan  2  3  map lambda v 0 if np isnan v     True else v  a    This will give you the result     0  2  3

User · Answer

A code example for drake s answer to use nan to num    gt  gt  gt  import numpy as np  gt  gt  gt  A   np array   1  2  3    0  3  np NaN     gt  gt  gt  A   np nan to num A   gt  gt  gt  A array    1    2    3             0    3    0

User · Answer

nan is never equal to nan  if z  z z 0   so for a 2D array  for entry in nparr      if entry  entry entry 0

User · Answer

You can use numpy nan to num        numpy nan to num x    Replace nan with zero and inf with finite numbers    Example  see doc      gt  gt  gt  np set printoptions precision 8   gt  gt  gt  x   np array  np inf  -np inf  np nan  -128  128    gt  gt  gt  np nan to num x  array    1 79769313e 308   -1 79769313e 308    0 00000000e 000          -1 28000000e 002    1 28000000e 002

User · Answer

You could use np where to find where you have NaN   import numpy as np  a   np array      0    43    67     0    38                   100    86    96   100    94                    76    79    83    89    56                    88    np nan    67    89    81                    94    79    67    89    69                    88    79    58    72    63                    76    79    71    67    56                    71    71    np nan    56   100     b   np where np isnan a   0  a   In  20   b Out 20    array      0     43     67      0     38             100     86     96    100     94              76     79     83     89     56              88      0     67     89     81              94     79     67     89     69              88     79     58     72     63              76     79     71     67     56              71     71      0     56    100

User · Answer

Where A is your 2D array   import numpy as np A np isnan A     0   The function isnan produces a bool array indicating where the NaN values are   A boolean array can by used to index an array of the same shape   Think of it like a mask

User · Answer

This should work   from numpy import    a   array   1  2  3    0  3  NaN    where are NaNs   isnan a  a where are NaNs    0   In the above case where are NaNs is   In  12   where are NaNs Out 12    array   False  False  False           False  False   True    dtype bool

[python] convert nan value to zero

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