## how to replace a character in an array using numpy?

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I have an array that consists of numeric values that are on a string form along with the '?' character which represents missing values. How can I make to replace those chars with an outlier value like -999999?

I know there is a way with Panda´s, but how to do that only using numpy? Tried to find those values with something like:

x=X[X=='?']

to use numpy replace, but no luck at all. Any help?

Thanks

It's quite similar to the Pandas method:

X[X == '?'] = '-999999'

at which point, if you desire, you could convert the values to integers using

X = X.astype(int)

For example:

import numpy as np X = np.array(['1', '2', '3', '?', '5'], dtype=object) X[X == '?'] = '-999999' X = X.astype(int) print(X) # array([ 1, 2, 3, -999999, 5])

**how to replace a character in an array using numpy?,** It's quite similar to the Pandas method: X[X == '?'] = '-999999'. at which point, if you desire, you could convert the values to integers using numpy.char.replace() This function returns a new copy of the input string in which all occurrences of the sequence of characters is replaced by another given sequence.

One way to do it would be using numpy.place :

np.place(X,X=="?",-999999)

**numpy.char.replace,** For each element in a, return a copy of the string with all occurrences of substring old replaced by new. Calls str.replace element-wise. Parameters. aarray-like of numpy.core.defchararray.replace() function. For each element in a given array numpy.core.defchararray.replace() function returns a copy of the string with all occurrences of substring old replaced by new. Calls str.replace element-wise.

You can also use `np.where`

:

print(np.where(X == '?', '-999999', X).astype(int))

**char.replace - Numpy and Scipy,** numpy.char.replace() - This function returns a new copy of the input string in which all occurrences of the sequence of characters is replaced by another given Write a NumPy program to replace all elements of NumPy array that are greater than specified array. Resetting will undo all of your current changes. pro tip You can save a copy for yourself with the Copy or Remix button. Recaptcha requires verification. pro tip You can save a copy for yourself with the Copy or Remix button. Publish Your Trinket!

**numpy.char.replace(),** numpy.chararray.replace¶. chararray. replace (old, new, count=None)[source]¶. For each element in self, return a copy of the string with all occurrences of Alternatively you can use map(): You can use the numpy.core.defchararray.replace function, which performs the for operation using numpy instead: Now all you need is np.char.replace. Something along these lines will work if your strings are of fixed length, and your array is of type string, and not of type object.

**numpy.chararray.replace,** Python code example 'Replace values in an array' for the package numpy, powered by Kite. Given numpy array, the task is to replace negative value with zero in numpy array. Let’s see a few examples of this problem. Method #4: Comparing the given array with an array of zeros and write in the maximum value from the two arrays as the output. Check out this Author's contributed articles. If you like GeeksforGeeks and would like to

**numpy - Replace values in an array - Python code example,** Versus a regular NumPy array of type str or unicode , this class adds the following remove whitespace from the end when comparing values; vectorized string chararrays should be created using numpy.char.array or numpy.char.asarray Generally speaking, though, I'd avoid using numpy arrays to store strings in most cases. There are cases where it's useful, but you're usually better off sticking to data structures that allow variable-length strings for, well, holding strings.