Now, you want to apply label encoding on this list for importing and transforming, using LabelEncoder. Imagine, you are given a list of items in a DataFrame as below. Soup=BeautifulSoup(html_doc,’html.parser’) Soup =BeautifulSoup(html_doc,’html.parser’) Hint: You have to extract text in title tag Udacity/deep-learning: Repo for the Deep Learning Nanodegree Foundations program.ģ0) To read the title of the webpage you are using BeautifulSoup.
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Suppose we make a dataframe as df = pd.DataFrame(,ġ6) What is the difference between the two data series given below? Note: Numpy has been imported as np and dataframe is set as df.A) Y = df.values You want to keep the threshold for classification to 5, such that if the class is greater than 5, the output should be 1, else output should be 0.ġ5) Which of the following codes would help you perform this task? The quality column currently has values 1 to 10, but we want to substitute this by a binary classification problem. Suppose you want to join train and test dataset (both are two numpy arrays train_set and test_set) into a resulting array (resulting_set) to do data processing on it simultaneously. If one of them is False, then both the arrays have same space allocated. You surmise that the two arrays must have the same space allocated.Ī) Check memory of both arrays, if they match that means the arrays are same.ī) Do “np.array_equal(e, f)” and if the output is “True” then they both are sameĬ) Print flags of both arrays by e.flags and f.flags check the flag “OWNDATA”. This creates a problem while processing the data.įor example, if you set the first 5 values of e as 0 i.e. When you change the values of the first array, the values for the second array also changes. You get the following output when you print “e” & “f” print e
txt = '''450ġ) Which of the following codes would be appropriate for this task?ĭ) re.search(‘ut, um’, txt)).count() Note: Python regular expression library has been imported as re. To identify how many shots a person is having in the entire game, you are supposed to write a code. What if you could use your technical skills to play this game? Do you remember the game where they played, in which each person drinks a shot whenever someone says “but, um”. You must have seen the show “How I met your mother”.
Here are a few statistics about the distribution. Close to 1,300 people participated in the test with more than 300 people taking this test.īelow are the distribution scores of the people who took the test: This test was conducted as part of DataFest 2017. If you are learning Python for Data Science, this test was created to help you assess your skill in Python.
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Want to know what are the milestones in Data Science Journey and how to achieve them? Check out the complete Data Science Roadmap! Click here to Download. Learning Python is the first step in your Data Science Journey. Not only this, if you want to learn Deep Learning, Python clearly has the most mature ecosystem among all other languages. Most of us use Python as our preferred tool for machine learning. So you can not only transform and manipulate data, but you can also create strong pipelines and machine learning workflows in a single ecosystem.Īt Analytics Vidhya, we love Python. It brings the entire ecosystem of a general programming language.
Python is increasingly becoming popular among data science enthusiasts, and for right reasons.
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