Python Numpy Data Analysis Exercises

1. Write a Python Numpy program to generate 3x3 matrix and display the maximum and minimum of y axis .

The output is:

Expected Answer:
3x3 matrix:
[[0 1 2]
[3 4 5]
[6 7 8]]

Maximum value along the y axis: [2 5 8]
Minimum value along the y axis: [0 3 6]

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2. Write a Python Numpy program to generate 3x3 array and display the maximum and minimum of value in the 3x3 array.

The output is:

Expected Answer:
3x3 array:
[[0 1 2]
[3 4 5]
[6 7 8]]

Maximum value of the array:
8
Minimum value of the array:
0

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3. Write a Python Numpy program to generate 3x3 array and calculate to find out the difference between maximum and minimum value in x axis.

The output is:

Expected Answer:
3x3 array:
[[0 1 2]
[3 4 5]
[6 7 8]]

Difference between the maximum and the minimum values of the 3x3 array:
[2 2 2]

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4. Write a Python Numpy program to generate 4x3 array and find out the median of the array.

The output is:

Expected Answer:
Initial 3x4 array:
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]]

Median of 3x4 array: 5.5

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5. Write a Python Numpy program to calculate the 65th percentile for all elements in the 3x4 array along the first axis (x-axis).

The output is:

Expected Answer:
Initial 3x4 array:
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]]

65th percentile for all elements of the 3x4 array along the first axis:
[5.2 6.2 7.2 8.2]

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6. Write a Python Numpy program to calculate weight average of the given array in the following output.

The output is:

Expected Answer:
Initial array: [1 2 3 4 5]
Weights:    [2 3 4 5 6]

Weighted average of the array: 3.5

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7. Write a Python Numpy program to calculate the mean, standard deviation and variance of the given array in the following output.

The output is:

Expected Answer:
Initial array: [1 2 3 4 5]
Mean: 3.0
Standard deviation: 1.707825127659933
Variance: 2.9166666666666665

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8. Write a Python Numpy program to calculate cross-correlation of the two given array in the following output.

The output is:

Expected Answer:
Initial array1:
[1 2 3 4]

Initial array2:
[6 7 8 9]

Cross-correlation of the arrays:
[[1.66666667 1.66666667]
[1.66666667 1.66666667]]

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More Exercises:

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Python Library Exercises
Python Sets Exercises
Python Array Exercises
Python Condition Statement Exercises
Python Lambda Exercises
Python Function Exercises
Python File Input Output Exercises
Python Tkinter Exercises


More Numpy Exercises:

Numpy String Exercises
Numpy Integer Exercises
Numpy Array Exercises
Numpy Data Analysis Exercises
Numpy Data Sorting Exercises


More Pandas Exercises:

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