Numpy Tutorial in Hindi

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[kishansharma]

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44:56
Function: myar.argsort(axis = 1)
Display: array
([[0, 1, 2],
[0, 1, 2],
[2, 1, 0]], dtype=int64)

Functionality: it will display the indexes of the values from the original array and sort the values

[nnnBigOne]

07:03 Numpy gives efficient storage and ready-made functions for data analysis.

14:06 Using Jupyter Notebook and Numpy

21:09 Learned about creating numpy arrays using python objects

28:12 Creating numpy arrays from Python structures and using intrinsic numpy array creation objects

35:15 Numpy array creation methods and reshaping

42:18 Understanding numpy arrays and axis

49:21 Using arg sort and axis to sort 2D arrays

56:18 NumPy arrays take less space compared to Python arrays.

[rajadityasureshbhai]

44:54
We want an argsort of axis 1, so as we all know that axis one goes from left to right hence when the first whole column will be an axis of when axis 1 is concerned, hence if we try to sort it we will come to know that all the elements are already sorted, so it will yield and answer as [0, 1, 2].

[nandankumar]

45:13 arg.sort() it works by default rows wise and if we give it axis =0 . then it work vertically every column and if we give axis = 0 then it work horizantally

[irfanmohammad]

ar.argsort(axis=1) gives the given 2D array in ascending order for all rows. [ [1, 2, 3] , [4, 5, 6] , [0, 1, 7] ]

[zuberkhan]

ar.argsort(axis = 1)
array ([0, 1, 2]
[0, 1, 2]
[2, 1, 0])
2 = 3
2 = 6
0 = 7
it represents ascending value in every row (horizontally)...

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[pradhyumjaiswal]

ar.argsort(axis=0)
This will give us the index to sort the array column-wise, vertically.

[sakshamkumar]

44:42 --> 'argsort()' may be used to find the index of all the elements of a sorted array of any dimension. for a 2d array, we have to specify the axis whose elements we want to sort

[RaviPal-monc]

44:58 in axis = 0 it tells us where the required elements are w.r.t vertical axis for them to be sorted in ascending order vertically
In axis = 1 it is considered horizontally

[rohanchaudhari]

ar.argsort(axis=1)
# for axis =1 it will sort the array by the column

ar.argsort(axis=0)

# for axis = 0 it will give the index of the maximum element in each row

[kamranhossain]

Argsort(axis=0)..this provide the sorted position of the value of axis 0...like if axis 0 has some numbers like 4, 2, 7..then argsort will provide the following position 1, 0, 2..

[mitalisingh]

Argsort arranges the indices of elements in increasing order of element value. Depending on the axis, it works like...for axis 0 it sorts every column individually and for axis 1 it sorts the rows individually.

[zahoorahmedsayyad]

44:30
As you have given (axis=1) as argument for argsort it will sort elements with respect to in horizontal axis.

[bhattrahul]

I was not knowing that its so easy to handle NumPy and pandas...Kudos to COde Master know that you but still I wanna tell, you are providing occupation to a is so kind....HATTSSS OFFF to this master....We all love you....😍

Do we have notes of pandas and numpy?

[anshdholakia]

44:58, I feel that the argsort(axis=0) when applied to the 2D array, shows the indices sorted with respect to the vertical directions and the axis=1 shows induced sorted wrt the horizontal direction :)

[anish]

The argsort(axis=0) works on columns if we look at the column no1 then the smallest is at index 0, the middlest as at index 1 and the largest is at index 2 so it become 0, 1, 2 and in column 2 : the smallest is at index 2, the middlest is at index 0 and the largest is at index 1 so it become 2, 0, 1..so like this we have to write the index of the smallest number to largest in a column (from smallest to largest )

[akashaggarwal]

ar.argsort(axis=1) will return a matrix of same order with sorter indices on axis one. This will tell us the indices of min to max element of the row
for example;
[
[4, 5, 6],
[8, 22, 1],
[100, 23, 1]
]
will result in
[[0, 1, 2],
[1, 2, 0],
[2, 1, 0]]