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Your assignment is to create a Python program that uses data analytics to address a real-world problem

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Your assignment is to create a Python program that uses data analytics to address a real-world problem. Within reason, you may choose to address any real-world problem that you would like; however, please only choose a real-world problem that is both safe and legal. The goal of the project is for you to showcase the skills that you’ve gained over the course of the semester on an assignment that you find interesting and fulfilling. Your program should read or download some sort of data to perform its analysis. A data file may be stored locally on your computer, or your program can load data from an online API. In either case, you must use real data that pertains to the real-world problem that your project seeks to address. You have several options for obtaining real data. First, the following sites are free repositories that provide data and APIs on a variety of topics: • • • Kaggle (see https://www.kaggle.com/datasets) Google Dataset Search (see https://datasetsearch.research.google.com/) Public API list (see https://github.com/public-apis/public-apis) Second, in light of the recent coronavirus (COVID-19) pandemic, below are a few timely sources of data on that topic: • • • COVID-19 API (see https://covid19api.com/) COVID Tracking Project (see https://covidtracking.com/data) San Diego county coronavirus live map data (see https://drive.google.com/open?id=1Ak2Zxr8RZle4YGPz0YIDdVOQEqkcUbG) Your program must make use of text analytics, machine learning, or both. The exact type of analysis that your program performs is up to you and will depend on the real-world problem that you choose; you may make your own decisions about which tools to use provided that you justify your reasoning. When determining the scope of your project, please ensure that you can complete your project within the last 28 days of the semester. However, your project should be polished and show some level of 2 complexity. For example, a project whose purpose was to calculate the average sentiment for a large dataset of Yelp reviews would not be sufficiently complex. However, a project that allowed the user to compare sentiment values across restaurants over different time periods is more in line with the expectations for this assignment. Your project must involve some sort of visualization. Depending on your dataset, this can take several forms (a line plot, a bar graph, a wordcloud, etc.). Choose visualizations that add realworld value to your project. Design your visualizations to be visually attractive (label your axes if you are making a bar graph, consider stop words if you are making a wordcloud, etc.) You may complete this project either individually or with a partner (that is, a group of two). One partner may submit the final project files on behalf of the group. In this case, please clearly indicate both partners’ names on each file. Both partners will receive the same grade. When submitting your project, please include the following files. • A brief written summary and project description. The document should describe your project concept, including what problem your problem is looking to solve and how your program addresses that problem. Please use two pages as a rough guideline for the expectations for the written document; however, you may write more or less as needed. Please design your report to look professional. For example, use complete sentences and check your spelling. • Your Python program. • (If your program utilizes a data file as opposed to an API, please submit this too! Some considerations to note: • Ensure that you handle potential errors in our code wherever possible. The specific types of errors possible depend on the nature of your project. However, for example, you may handle errors pertaining to connection issues, user-inputted values being poorly formatted or invalid within your real-world problem, etc. • Ensure that your application is crisp, professional, and well-formatted. For example, ensure that you have used spaces appropriately and checked your spelling. • Adding comments in your code is encouraged. You may decide how best to comment your code. At minimum, please use a comment at the start of your code to describe its basic functionality. For any functions in your code, write appropriate docstrings. Question #1 Use the content of this page (https://api.datamuse.com/words?md=s&rel_trg=student (Links to an external site.)) https://api.datamuse.com/words?md=s&rel_trg=student which is in JSON format and write python code that answers the following: 1. How many words have 2 syllables 2. Create a text by using the words which are found on this page. Use a space between every two words. The text will be: enrollment tuition ratio achievement math eligible loans teacher lunch students campus academic graduation accommodation faculty admission undergraduate body fees alumni newspaper enrolled graduate grades scholarship studying attend attending curriculum learning credits 3. Create a wordcloud by using this text. 4. Use part of speech tagging to calculate the number of words in the text according to their tag type as listed below: - words with tag type (“VBG” or “VBP”) - words with tag type (“NN” or “NNS”) - words with other tag types. 5. Create a bar graph for the number of words per each tag type group defined in part 4. Add title and labels’ name. The bar should be displayed as below: 6. Create a pie graph to represent the three groups of part 4. This a screenshot of the same question #Getting the input Corruption pd.read_csv"Corruption.csv Democracy pd.read_excel("democracy.xlsx") pd.read_csv("GDP.csv") Literacy = pd.read_excel("Literacy_Rate.xlsx") = GDP = #average of all is taken as index FileNotFoundError Traceback (most recent call last) in () 7 8 #Getting the input 9 Corruption pd.read_csv ("Corruption.csv") 10 Democracy pd.read_excel("democracy.xlsx") 11 GDP = pd.read_csv ("GDP.csv") -- = = _init_(self, src, **kwds) 4 frames /usr/local/lib/python3.7/dist-packages/pandas/io/parsers.py. in 2008 kwds ["usecols"] = self. usecols 2009 -> 2010 self._reader = parsers. TextReader(src, **kwds) 2011 self.unnamed_cols = self._reader.unnamed_cols 2012 pandas/_libs/parsers.pyx in pandas._libs.parsers. TextReader. _cinit_ pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._setup_parser_source) FileNotFoundError: [Errno 2] No such file or directory: Corruption.csv'