[ad_1] I am not completly sure if this is what you are looking for, but generators have a method called ‘send’ which enables you to pass data to the generator. You might want to read this example. Pay attention to the functions ‘consume’ and ‘produce’. [ad_2] solved How can I pass a variable from one … Read more
[ad_1] Use a dictionary: >>> x=[‘a’, ‘b’, ‘c’, ‘d’] >>> di={k:[] for k in x} 1 [ad_2] solved How to make several list which have a name already decided variable [closed]
[ad_1] Some parts of your question are unclear. It might help to give the context of what you’re trying to achieve, rather than what are the specific steps you’re taking. 1) + 3) In a Normal distribution – fitting the distribution, and estimating the mean and standard deviation – are basically the same thing. The … Read more
[ad_1] Here is an efficient solution. For each element in the second list, get the next element of the first one until you have a match. If you reach the end of the first list before you matched all, this is False else True def check(a, b): i = iter(a) return all(e in i for … Read more
[ad_1] Recursion works by breaking down each problem to a “smaller” version of the same problem. In this case, you can insert this code: elif n < 0: return False elif is_buyable(n – 20) or is_buyable(n – 9) or is_buyable(n – 6): return True 4 [ad_2] solved Python Recursion Puzzle: Buying n McNuggets at McDonalds … Read more
[ad_1] There are several ways to transform this variable. In the picture I see, that there are not only bins, but also value ’55+’, it needs to be considered. 1) One liner: df[‘age’].apply(lambda x: np.mean([int(x.split(‘-‘)[0]), int(x.split(‘-‘)[1])]) if ‘+’ not in x else x[:-1]) It checks whether the value contains ‘+’ (like 55+), if yes than … Read more
[ad_1] Anaconda is only capable of detecting and managing packages within its own environment. It cannot and will not detect and use an existing CUDA installation when installing packages with a CUDA dependency. Note however that the cudatoolkit package which conda will install is not a complete CUDA toolkit distribution. It only contains the necessary … Read more
[ad_1] You may use below list comprehension using map with eval(…) as: import ast Users = [‘Protein(“SAHDSJDSFJH”), {“id”: “s1”}’, ‘Protein(“ACGTWZJSFNM”), {“id”: “s2”}’, ‘Protein(“ABHZZEQTAAB”), {“id”: “s3”}’] new_list = [y for x in map(eval, Users) for y in x] where new_list will hold the value: [Protein(“SAHDSJDSFJH”), {‘id’: ‘s1’}, Protein(“ACGTWZJSFNM”), {‘id’: ‘s2’}, Protein(“ABHZZEQTAAB”), {‘id’: ‘s3’}] PS: Note that … Read more
[ad_1] You can do the test for whether it’s home or away in the query itself. cursor.execute(“”” SELECT CASE WHEN robot_on_her_island = ? THEN ‘Last_War_on_her_island’ ELSE ‘Last_War_on_island_away’ END AS which_island, points_war_home, points_war_away FROM war WHERE ? IN (robot_on_her_island, robot_on_island_away) LIMIT 1″””, (select_robot_on_her_island, select_robot_on_her_island)) row = cursor.fetchone() if row: which_island, points_home, points_away = row if which_island … Read more
[ad_1] As you are working with float data type, the following list builder code (as previously pointed in the comments) should work. row = [float(i) for i in row] [ad_2] solved How to remove ‘ ‘ in a python list
[ad_1] Good question… This is really hard to answer but I attempted a solution(what engineers try to do) that might work based on analyzing the pattern example you gave: import string import random def generate_similar(string): # Generates similar name by substituting vowels similar_word = [] for char in string: if char.lower() in ‘aeiou’: similar_word.append(random.choice(string.letters).lowercase()) else: … Read more
[ad_1] I think your only problem is that you have to reformat you result before saving it to the file, i.e. something like: result.map(lambda x:x[0]+’,’+str(x[1])).saveAsTextFile(“hdfs://localhost:9000/Test1”) 6 [ad_2] solved Removing Characters from python Output
[ad_1] You just copied the code from the itertools.permutations() documentation. That explicitly states that it is roughly equivalent, because it is only there to help you understand what itertools.permutations() does. The code is not intended to be used in production settings. Use itertools.permutations() itself. The itertools module is designed for maximum efficiency already. The module … Read more
[ad_1] np.arrays are much faster when using vectorized functions or to say it another way, specifically when you are not iterating over the elements. Here is an example. We will add 1 to each number in the ordered list you created. The setup is similar except I use lists instead of ranges so I can … Read more
[ad_1] As your individual response come through, you can create a list of the values using extend (vs append). Then create your final dictionary. Here’s a mockup of one way to implement -collect all the response, then iterate over the list. Otherwise you can parse each response as they come in. response1 = { “@odata.context”: … Read more