Page 229 - AI Ver 1.0 Class 10
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Size of an array ARR.size import numpy as np 8
i.e. counts the ARR =
number of np.array([[1,2,3,4],[3,4,5,6]])
elements
print(ARR.size)
Datatype of ARR.dtype import numpy as np int32
elements stored ARR =
in the array
np.array([[1,2,3,4],[3,4,5,6]])
print(ARR.dtype)
Maximum value ARR.max() import numpy as np 45
in the element ARR = np.array([[10,34,45,23,12]])
of the array
print(ARR.max())
Row wise & ARR. import numpy as np Rowwise max : [13
column wise max(axis=1) ARR = 6]
maximum value for row np.array([[11,2,13,4],[3,4,5,6]]) Column wise max :
print(“Rowwise max :”,ARR. [11 4 13 6]
ARR. max(axis=1))
max(axis=0) print(“Column wise max :”,ARR.
for column max(axis=0))
Row wise & ARR. import numpy as np Rowwise min : [2 3]
column wise min(axis=1) ARR = Column wise min :
minimum value for row np.array([[11,2,13,4],[3,4,5,6]]) [3 2 5 4]
print(“Rowwise min :”,ARR.
ARR. min(axis=1))
min(axis=0) print(“Column wise min :”,ARR.
for column min(axis=0))
Sum of all values ARR.sum() import numpy as np Rowwise sum : [30
in the given array ARR = 18]
np.array([[11,2,13,4],[3,4,5,6]]) Column wise sum :
print(“Row Wise sum :”,ARR. [14 6 18 10]
sum(axis=1))
sum is : 48
print(“Column wise sum :”,ARR.
sum(axis=0))
print(“sum is :”,ARR.sum())
Data Science 227

