meetforever/GRPO_CL huggingface dataset:
user: =====Function Descriptions=====
Basic mathematical functions operate element-wise on arrays. They are available both as operator overloads and as functions in the NumPy module.

import numpy

a = numpy.array([1,2,3,4], float)
b = numpy.array([5,6,7,8], float)

print a + b                     #[  6.   8.  10.  12.]
print numpy.add(a, b)           #[  6.   8.  10.  12.]

print a - b                     #[-4. -4. -4. -4.]
print numpy.subtract(a, b)      #[-4. -4. -4. -4.]

print a * b                     #[  5.  12.  21.  32.]
print numpy.multiply(a, b)      #[  5.  12.  21.  32.]

print a / b                     #[ 0.2         0.33333333  0.42857143  0.5       ]
print numpy.divide(a, b)        #[ 0.2         0.33333333  0.42857143  0.5       ]

print a % b                     #[ 1.  2.  3.  4.]
print numpy.mod(a, b)           #[ 1.  2.  3.  4.]

print a**b                      #[  1.00000000e+00   6.40000000e+01   2.18700000e+03   6.55360000e+04]
print numpy.power(a, b)         #[  1.00000000e+00   6.40000000e+01   2.18700000e+03   6.55360000e+04]

=====Problem Statement=====
You are given two integer arrays, A and B of dimensions NXM.
Your task is to perform the following operations:
1. Add (A + B)
2. Subtract (A - B)
3. Multiply (A * B)
4. Integer Division (A / B)
5. Mod (A % B)
6. Power (A ** B)

=====Input Format=====
The first line contains two space separated integers, N and M.
The next N lines contains M space separated integers of array A.
The following N lines contains M space separated integers of array B.

=====Output Format=====
Print the result of each operation in the given order under Task.
user: =====Function Descriptions=====
Concatenate

Two or more arrays can be concatenated together using the concatenate function with a tuple of the arrays to be joined:

import numpy

array_1 = numpy.array([1,2,3])
array_2 = numpy.array([4,5,6])
array_3 = numpy.array([7,8,9])

print numpy.concatenate((array_1, array_2, array_3))    

#Output
[1 2 3 4 5 6 7 8 9]

If an array has more than one dimension, it is possible to specify the axis along which multiple arrays are concatenated. By default, it is along the first dimension.

import numpy

array_1 = numpy.array([[1,2,3],[0,0,0]])
array_2 = numpy.array([[0,0,0],[7,8,9]])

print numpy.concatenate((array_1, array_2), axis = 1)   

#Output
[[1 2 3 0 0 0]
 [0 0 0 7 8 9]]    

=====Problem Statement=====
You are given two integer arrays of size NXP and MXP (N & M are rows, and P is the column). Your task is to concatenate the arrays along axis 0.

=====Input Format=====
The first line contains space separated integers N, M and P .
The next N lines contains the space separated elements of the P columns.
After that, the next M lines contains the space separated elements of the P columns.

=====Output Format=====
Print the concatenated array of size (N + M)XP.
user: =====Function Descriptions=====
itertools.combinations(iterable, r)
This tool returns the r length subsequences of elements from the input iterable.

Combinations are emitted in lexicographic sorted order. So, if the input iterable is sorted, the combination tuples will be produced in sorted order.

Sample Code

>>> from itertools import combinations
>>> 
>>> print list(combinations('12345',2))
[('1', '2'), ('1', '3'), ('1', '4'), ('1', '5'), ('2', '3'), ('2', '4'), ('2', '5'), ('3', '4'), ('3', '5'), ('4', '5')]
>>> 
>>> A = [1,1,3,3,3]
>>> print list(combinations(A,4))
[(1, 1, 3, 3), (1, 1, 3, 3), (1, 1, 3, 3), (1, 3, 3, 3), (1, 3, 3, 3)]

=====Problem Statement=====
You are given a string S.
Your task is to print all possible combinations, up to size k, of the string in lexicographic sorted order.

=====Constraints=====
0<k≤len(S)

=====Input Format=====
A single line containing the string S and integer value k separated by a space.

=====Output Format=====
Print the different combinations of string S on separate lines.
user: =====Function Descriptions=====
identity

The identity tool returns an identity array. An identity array is a square matrix with all the main diagonal elements as 1 and the rest as 0. The default type of elements is float.

import numpy
print numpy.identity(3) #3 is for  dimension 3 X 3

#Output
[[ 1.  0.  0.]
 [ 0.  1.  0.]
 [ 0.  0.  1.]]

eye

The eye tool returns a 2-D array with 1's as the diagonal and 0's elsewhere. The diagonal can be main, upper or lower depending on the optional parameter k. A positive k is for the upper diagonal, a negative k is for the lower, and a 0 k (default) is for the main diagonal.

import numpy
print numpy.eye(8, 7, k = 1)    # 8 X 7 Dimensional array with first upper diagonal 1.

#Output
[[ 0.  1.  0.  0.  0.  0.  0.]
 [ 0.  0.  1.  0.  0.  0.  0.]
 [ 0.  0.  0.  1.  0.  0.  0.]
 [ 0.  0.  0.  0.  1.  0.  0.]
 [ 0.  0.  0.  0.  0.  1.  0.]
 [ 0.  0.  0.  0.  0.  0.  1.]
 [ 0.  0.  0.  0.  0.  0.  0.]
 [ 0.  0.  0.  0.  0.  0.  0.]]

print numpy.eye(8, 7, k = -2)   # 8 X 7 Dimensional array with second lower diagonal 1.

=====Problem Statement=====
Your task is to print an array of size NXM with its main diagonal elements as 1's and 0's everywhere else.

=====Input Format=====
A single line containing the space separated values of N and M.
N denotes the rows.
M denotes the columns.

=====Output Format=====
Print the desired NXM array.
user: =====Problem Statement=====
An extra day is added to the calendar almost every four years as February 29, and the day is called a leap day. It corrects the calendar for the fact that our planet takes approximately 365.25 days to orbit the sun. A leap year contains a leap day.

In the Gregorian calendar, three conditions are used to identify leap years:
    The year can be evenly divided by 4, is a leap year, unless:
        The year can be evenly divided by 100, it is NOT a leap year, unless:
            The year is also evenly divisible by 400. Then it is a leap year.

This means that in the Gregorian calendar, the years 2000 and 2400 are leap years, while 1800, 1900, 2100, 2200, 2300 and 2500 are NOT leap years. Source

Task
Given a year, determine whether it is a leap year. If it is a leap year, return the Boolean True, otherwise return False.
Note that the code stub provided reads from STDIN and passes arguments to the is_leap function. It is only necessary to complete the is_leap function.

=====Input Format=====
Read year, the year to test.

=====Constraints=====
1900≤year≤10^5

=====Output Format=====
The function must return a Boolean value (True/False). Output is handled by the provided code stub.

Answer: {"fn_name": "is_leap", "inputs": [[1990]], "outputs": [false]}
user: =====Function Descriptions=====
start() & end()

These expressions return the indices of the start and end of the substring matched by the group.

Code

>>> import re
>>> m = re.search(r'\d+','1234')
>>> m.end()
4
>>> m.start()
0

=====Problem Statement=====
You are given a string S.
Your task is to find the indices of the start and end of string k in S.

=====Input Format=====
The first line contains the string S.
The second line contains the string k.

=====Output Format=====
Print the tuple in this format: (start_index, end_index)

If no match is found, print (-1, -1).
user: =====Function Descriptions=====
*This section assumes that you understand the basics discussed in HTML Parser - Part 1

.handle_comment(data)
This method is called when a comment is encountered (e.g. <!--comment-->).
The data argument is the content inside the comment tag:

from HTMLParser import HTMLParser

class MyHTMLParser(HTMLParser):
    def handle_comment(self, data):
          print "Comment  :", data


.handle_data(data)
This method is called to process arbitrary data (e.g. text nodes and the content of <script>...</script> and <style>...</style>).
The data argument is the text content of HTML.

from HTMLParser import HTMLParser

class MyHTMLParser(HTMLParser):
    def handle_data(self, data):
        print "Data     :", data

=====Problem Statement=====
You are given an HTML code snippet of N lines.
Your task is to print the single-line comments, multi-line comments and the data.

Print the result in the following format:

>>> Single-line Comment  
Comment
>>> Data                 
My Data
>>> Multi-line Comment  
Comment_multiline[0]
Comment_multiline[1]
>>> Data
My Data
>>> Single-line Comment:  

Note: Do not print data if data == '\n'. 

=====Input Format=====
The first line contains integer N, the number of lines in the HTML code snippet.
The next N lines contains HTML code.

=====Constraints=====
0<N<100

=====Output Format=====
Print the single-line comments, multi-line comments and the data in order of their occurrence from top to bottom in the snippet.

Format the answers as explained in the problem statement.
user: =====Problem Statement=====
You are given the firstname and lastname of a person on two different lines. Your task is to read them and print the following:

    Hello firstname lastname! You just delved into python.

=====Input Format=====
The first line contains the first name, and the second line contains the last name.

=====Constraints=====
The length of the first and last name ≤ 10.

=====Output Format=====
Print the output as mentioned above.
user: =====Function Descriptions=====
Exceptions
Errors detected during execution are called exceptions.

Examples:
ZeroDivisionError
This error is raised when the second argument of a division or modulo operation is zero.
>>> a = '1'
>>> b = '0'
>>> print int(a) / int(b)
>>> ZeroDivisionError: integer division or modulo by zero

ValueError
This error is raised when a built-in operation or function receives an argument that has the right type but an inappropriate value.
>>> a = '1'
>>> b = '#'
>>> print int(a) / int(b)
>>> ValueError: invalid literal for int() with base 10: '#'

Handling Exceptions
The statements try and except can be used to handle selected exceptions. A try statement may have more than one except clause to specify handlers for different exceptions.

#Code
try:
    print 1/0
except ZeroDivisionError as e:
    print "Error Code:",e
Output

Error Code: integer division or modulo by zero

=====Problem Statement=====
You are given two values a and b.
Perform integer division and print a/b.

=====Input Format=====
The first line contains T, the number of test cases.
The next T lines each contain the space separated values of a and b.

=====Constraints=====
0<T<10

=====Output Format=====
Print the value of a/b.
In the case of ZeroDivisionError or ValueError, print the error code.
user: =====Function Descriptions=====
 min

The tool min returns the minimum value along a given axis.

import numpy

my_array = numpy.array([[2, 5], 
                        [3, 7],
                        [1, 3],
                        [4, 0]])

print numpy.min(my_array, axis = 0)         #Output : [1 0]
print numpy.min(my_array, axis = 1)         #Output : [2 3 1 0]
print numpy.min(my_array, axis = None)      #Output : 0
print numpy.min(my_array)                   #Output : 0

By default, the axis value is None. Therefore, it finds the minimum over all the dimensions of the input array.

max

The tool max returns the maximum value along a given axis.

import numpy

my_array = numpy.array([[2, 5], 
                        [3, 7],
                        [1, 3],
                        [4, 0]])

print numpy.max(my_array, axis = 0)         #Output : [4 7]
print numpy.max(my_array, axis = 1)         #Output : [5 7 3 4]
print numpy.max(my_array, axis = None)      #Output : 7
print numpy.max(my_array)                   #Output : 7

By default, the axis value is None. Therefore, it finds the maximum over all the dimensions of the input array. 

=====Problem Statement=====
You are given a 2-D array with dimensions NXM.
Your task is to perform the min function over axis 1 and then find the max of that.

=====Input Format=====
The first line of input contains the space separated values of N and M.
The next N lines contains M space separated integers.

=====Output Format=====
Compute the min along axis 1 and then print the max of that result.
user: =====Function Descriptions=====
shape

The shape tool gives a tuple of array dimensions and can be used to change the dimensions of an array.

(a). Using shape to get array dimensions

import numpy

my__1D_array = numpy.array([1, 2, 3, 4, 5])
print my_1D_array.shape     #(5,) -> 5 rows and 0 columns

my__2D_array = numpy.array([[1, 2],[3, 4],[6,5]])
print my_2D_array.shape     #(3, 2) -> 3 rows and 2 columns 

(b). Using shape to change array dimensions

import numpy

change_array = numpy.array([1,2,3,4,5,6])
change_array.shape = (3, 2)
print change_array      

#Output
[[1 2]
[3 4]
[5 6]]

reshape

The reshape tool gives a new shape to an array without changing its data. It creates a new array and does not modify the original array itself.

import numpy

my_array = numpy.array([1,2,3,4,5,6])
print numpy.reshape(my_array,(3,2))

#Output
[[1 2]
[3 4]
[5 6]]

=====Problem Statement=====
You are given a space separated list of nine integers. Your task is to convert this list into a 3X3 NumPy array.

=====Input Format=====
A single line of input containing 9 space separated integers.

=====Output Format=====
Print the 3X3 NumPy array.
user: =====Function Descriptions=====
floor
The tool floor returns the floor of the input element-wise.
The floor of x is the largest integer i where i≤x.

import numpy

my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.floor(my_array)         #[ 1.  2.  3.  4.  5.  6.  7.  8.  9.]

ceil
The tool ceil returns the ceiling of the input element-wise.
The ceiling of x is the smallest integer i where i≥x.

import numpy

my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.ceil(my_array)          #[  2.   3.   4.   5.   6.   7.   8.   9.  10.]

rint
The rint tool rounds to the nearest integer of input element-wise.

import numpy

my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.rint(my_array)          #[  1.   2.   3.   4.   6.   7.   8.   9.  10.]

=====Problem Statement=====
You are given a 1-D array, A. Your task is to print the floor, ceil and rint of all the elements of A.

=====Input Format=====
A single line of input containing the space separated elements of array A.

=====Output Format=====
On the first line, print the floor of A.
On the second line, print the ceil of A.
On the third line, print the rint of A.
user: =====Problem Statement=====
Kevin and Stuart want to play the 'The Minion Game'.

Game Rules

Both players are given the same string, S.
Both players have to make substrings using the letters of the string S.
Stuart has to make words starting with consonants.
Kevin has to make words starting with vowels.
The game ends when both players have made all possible substrings.

Scoring
A player gets +1 point for each occurrence of the substring in the string S.

=====Example=====
String S = BANANA
Kevin's vowel beginning word = ANA
Here, ANA occurs twice in BANANA. Hence, Kevin will get 2 Points.

Your task is to determine the winner of the game and their score.

=====Input Format=====
A single line of input containing the string S.
Note: The string S will contain only uppercase letters: [A-Z].

=====Constraints=====
0 < len(S) < 10^6

=====Output Format=====
Print one line: the name of the winner and their score separated by a space.
If the game is a draw, print Draw.

Answer: {"fn_name": "minion_game", "inputs": [["BANANA"]], "outputs": ["Stuart 12"]}
user: =====Problem Statement=====
You are given n words. Some words may repeat. For each word, output its number of occurrences. The output order should correspond with the input order of appearance of the word. See the sample input/output for clarification.

Note: Each input line ends with a "\n" character.

=====Constraints=====
1≤n≤10^5
The sum of the lengths of all the words do not exceed 10^6
All the words are composed of lowercase English letters only.

=====Input Format=====
The first line contains the integer, n.
The next n lines each contain a word.

=====Output Format=====
Output 2 lines.
On the first line, output the number of distinct words from the input.
On the second line, output the number of occurrences for each distinct word according to their appearance in the input.
user: =====Function Descriptions=====
Polar coordinates are an alternative way of representing Cartesian coordinates or Complex Numbers.
A complex number z
z = x + yj
is completely determined by its real part y. Here, j is the imaginary unit.

A polar coordinate (r, φ) is completely determined by modulus r and phase angle φ.
If we convert complex number z to its polar coordinate, we find:
r: Distance from z to origin, i.e., sqrt(x^2 + y^2)
φ: Counter clockwise angle measured from the positive -axis to the line segment that joins z to the origin.

Python's cmath module provides access to the mathematical functions for complex numbers.
cmath.phase
This tool returns the phase of complex number z (also known as the argument of z).
>>> phase(complex(-1.0, 0.0))
3.1415926535897931

abs
This tool returns the modulus (absolute value) of complex number z.
>>> abs(complex(-1.0, 0.0))
1.0

=====Problem Statement=====
You are given a complex z. Your task is to convert it to polar coordinates.

=====Input Format=====
A single line containing the complex number z. Note: complex() function can be used in python to convert the input as a complex number.

=====Constraints=====
Given number is a valid complex number

=====Output Format=====
Output two lines:
The first line should contain the value of r.
The second line should contain the value of φ.
user: =====Function Descriptions=====
A set is an unordered collection of elements without duplicate entries.
When printed, iterated or converted into a sequence, its elements will appear in an arbitrary order.

=====Example=====
>>> print set()
set([])

>>> print set('HackerRank')
set(['a', 'c', 'e', 'H', 'k', 'n', 'r', 'R'])

>>> print set([1,2,1,2,3,4,5,6,0,9,12,22,3])
set([0, 1, 2, 3, 4, 5, 6, 9, 12, 22])

>>> print set((1,2,3,4,5,5))
set([1, 2, 3, 4, 5])

>>> print set(set(['H','a','c','k','e','r','r','a','n','k']))
set(['a', 'c', 'r', 'e', 'H', 'k', 'n'])

>>> print set({'Hacker' : 'DOSHI', 'Rank' : 616 })
set(['Hacker', 'Rank'])

>>> print set(enumerate(['H','a','c','k','e','r','r','a','n','k']))
set([(6, 'r'), (7, 'a'), (3, 'k'), (4, 'e'), (5, 'r'), (9, 'k'), (2, 'c'), (0, 'H'), (1, 'a'), (8, 'n')])

Basically, sets are used for membership testing and eliminating duplicate entries.

=====Problem Statement=====
Now, let's use our knowledge of sets and help Mickey.

Ms. Gabriel Williams is a botany professor at District College. One day, she asked her student Mickey to compute the average of all the plants with distinct heights in her greenhouse.

Formula used: 
Average = Sum of Distinct Heights / Total Number of Distinct Heights

=====Input Format=====
The first line contains the integer, N, the total number of plants.
The second line contains the N space separated heights of the plants.

=====Constraints=====
0<N≤100

=====Output Format=====
Output the average height value on a single line.
user: =====Problem Statement=====
Given an integer, n, print the following values for each integer i from 1 to n:
1. Decimal
2. Octal
3. Hexadecimal (capitalized)
4. Binary

The four values must be printed on a single line in the order specified above for each i from 1 to n. Each value should be space-padded to match the width of the binary value of n.

=====Input Format=====
A single integer denoting n.

=====Constraints=====
1 ≤ n ≤ 99

=====Output Format=====
Print n lines wehere each line i (in the range 1 ≤ i ≤ n) contains the respective decimal, octal, capitalized hexadecimal, and binary values of i. Each printed value must be formatted to the width of the binary value of n.
user: =====Problem Statement=====
You are given a set A and n other sets.
Your job is to find whether set A is a strict superset of each of the N sets.
Print True, if A is a strict superset of each of the N sets. Otherwise, print False.
A strict superset has at least one element that does not exist in its subset.

=====Example=====
Set([1,3,4]) is a strict superset of set([1,3]).
Set([1,3,4]) is not a strict superset of set([1,3,4]).
Set([1,3,4]) is not a strict superset of set(1,3,5).

=====Input Format=====
The first line contains the space separated elements of set A.
The second line contains integer n, the number of other sets.
The next n lines contains the space separated elements of the other sets.

=====Constraints=====
0 < len(set(A)) < 501
0<N<21
0 < len(otherSets) < 101

=====Output Format=====
Print True if set A is a strict superset of all other N sets. Otherwise, print False.
user: =====Problem Statement=====
You are given a positive integer N. Print a numerical triangle of height N - 1 like the one below:
1
22
333
4444
55555
......

Can you do it using only arithmetic operations, a single for loop and print statement?

Use no more than two lines. The first line (the for statement) is already written for you. You have to complete the print statement.

Note: Using anything related to strings will give a score of 0.

=====Input Format=====
A single line containing integer, N.

=====Constraints=====
1≤N≤9

=====Output Format=====
Print N - 1 lines as explained above.
user: =====Function Descriptions=====
sum

The sum tool returns the sum of array elements over a given axis.

import numpy

my_array = numpy.array([ [1, 2], [3, 4] ])

print numpy.sum(my_array, axis = 0)         #Output : [4 6]
print numpy.sum(my_array, axis = 1)         #Output : [3 7]
print numpy.sum(my_array, axis = None)      #Output : 10
print numpy.sum(my_array)                   #Output : 10

By default, the axis value is None. Therefore, it performs a sum over all the dimensions of the input array.

prod

The prod tool returns the product of array elements over a given axis.

import numpy

my_array = numpy.array([ [1, 2], [3, 4] ])

print numpy.prod(my_array, axis = 0)            #Output : [3 8]
print numpy.prod(my_array, axis = 1)            #Output : [ 2 12]
print numpy.prod(my_array, axis = None)         #Output : 24
print numpy.prod(my_array)                      #Output : 24

By default, the axis value is None. Therefore, it performs the product over all the dimensions of the input array.

=====Problem Statement=====
ou are given a 2-D array with dimensions NXM.
Your task is to perform the sum tool over axis 0 and then find the product of that result.

=====Output Format=====
Compute the sum along axis 0. Then, print the product of that sum.
user: =====Function Descriptions=====
One of the built-in functions of Python is divmod, which takes two arguments a and b and returns a tuple containing the quotient of first and then the remainder.

=====Problem Statement=====
For example:
>>> print divmod(177,10)
(17, 7)

Here, the integer division is 177/10 => 17 and the modulo operator is 177%10 => 7.

Task
Read in two integers, a and b, and print three lines.
The first line is the integer division a//b (While using Python2 remember to import division from __future__).
The second line is the result of the modulo operator: a%b.
The third line prints the divmod of a and b.

=====Input Format=====
The first line contains the first integer, a, and the second line contains the second integer, b.

=====Output Format=====
Print the result as described above.
user: =====Function Descriptions=====
Transpose

We can generate the transposition of an array using the tool numpy.transpose.
It will not affect the original array, but it will create a new array.

import numpy

my_array = numpy.array([[1,2,3],
                        [4,5,6]])
print numpy.transpose(my_array)

#Output
[[1 4]
 [2 5]
 [3 6]]

Flatten

The tool flatten creates a copy of the input array flattened to one dimension.

import numpy

my_array = numpy.array([[1,2,3],
                        [4,5,6]])
print my_array.flatten()

#Output
[1 2 3 4 5 6]

=====Problem Statement=====
You are given a NXM integer array matrix with space separated elements (N = rows and M = columns).
Your task is to print the transpose and flatten results.

=====Input Format=====
The first line contains the space separated values of N and M.
The next N lines contains the space separated elements of M columns.

=====Output Format=====
First, print the transpose array and then print the flatten.