Python | Numpy expandtabs() method (original) (raw)
Last Updated : 19 Sep, 2019
With the help of **numpy.char.expandtabs()**
method, we can expand the tab using numpy method in the single statement.
Syntax :
numpy.char.expandtabs()
Return : Return the string array having expanded tabs.
Example #1 :
In this example we can see that by using numpy.char.expandtabs()
method, we are able to get the expanded tabs by using numpy.
import
numpy as np
gfg
=
np.char.expandtabs([
'Geeks\tFor\tGeeks'
],
10
)
print
(gfg)
Output :
[‘Geeks For Geeks’]
Example #2 :
import
numpy as np
gfg
=
np.char.expandtabs([
'G\tF\tG'
,
'Jitender\tKumar'
],
20
)
print
(gfg)
Output :
[‘G F G’ ‘Jitender Kumar’]
Similar Reads
- Python | Numpy.expand_dims() method With the help of Numpy.expand_dims() method, we can get the expanded dimensions of an array by using Numpy.expand_dims() method. Syntax : Numpy.expand_dims() Return : Return the expanded array. Example #1 : In this example we can see that using Numpy.expand_dims() method, we are able to get the expa 1 min read
- expandtabs() method in Python expandtabs() method in Python is used to replace all tab characters (\t) in a string with spaces. This method allows for customizable spacing, as we can specify the number of spaces for each tab. It is especially useful when formatting text for better readability or alignment. Let's understand with 3 min read
- Python | Numpy.dsplit() method With the help of Numpy.dsplit()() method, we can get the splitted dimensions of an array by using Numpy.dsplit()() method. Syntax : Numpy.dsplit(numpy.array(), split_size) Return : Return the array having splitted dimensions. Example #1 : In this example we can see that using Numpy.expand_dims() met 1 min read
- Python | Numpy fromarrays() method With the help of numpy.core.fromarrays() method, we can create the record array by using the list of different arrays by using numpy.core.fromarrays() method. Syntax : numpy.core.fromarrays([li1, li2....], metadata) Return : Return the record of an array. Example #1 : In this example we can see that 1 min read
- Python - Numpy fromrecords() method numpy.fromrecords() method is a powerful tool in the NumPy library that allows you to create structured arrays from a sequence of tuples or other array-like objects. Let's understand the help of an example: [GFGTABS] Python import numpy as np # Define a list of records records = [(1, 'Alice' 2 min read
- Python | numpy.array_split() method With the help of numpy.array_split() method, we can get the splitted array of having different dimensions by using numpy.array_split() method. Syntax : numpy.array_split() Return : Return the splitted array of one dimension. Example #1 : In this example we can see that by using numpy.array_split() m 1 min read
- Numpy MaskedArray.getdata() - Python numpy.ma.getdata() function is used return the data of a masked array as an ndarray. Return the data of arr as an ndarray if arr is a MaskedArray, else return arr as a ndarray or subclass if not. Syntax : numpy.ma.getdata(a, subok=True) Parameters : arr : [array_like] Input MaskedArray, alternativel 2 min read
- numpy.load() in Python numpy.load() function return the input array from a disk file with npy extension(.npy). Syntax : numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII') Parameters: file : : file-like object, string, or pathlib.Path.The file to read. File-like objects must support the 2 min read
- Numpy MaskedArray asanyarray() method | Python numpy.ma.asanyarray() function is used when we want to convert input to a masked array, conserving subclasses. If arr is a subclass of MaskedArray, its class is conserved. No copy is performed if the input is already an ndarray. Syntax : numpy.ma.asanyarray(arr, dtype=None) Parameters : arr : [array 2 min read
- Numpy MaskedArray asarray() method | Python numpy.ma.asarray() function is used when we want to convert input to a masked array of the given data-type. No copy is performed if the input is already a ndarray. If arr is a subclass of MaskedArray, a base class MaskedArray is returned. Syntax : numpy.ma.asarray(arr, dtype=None, order=None) Parame 2 min read