Order the answer to: Prompt the user for the country which will be mined. If the user chooses to not provide this…

Custom Essays python programming Order the answer to: Prompt the user for the country which will be mined. If the user chooses to not provide this…

python programming

Order the answer to: Prompt the user for the country which will be mined. If the user chooses to not provide this…

Question 1. Prompt the user for the country which will be mined. If the user chooses to not provide this information, then assume a default search of the United States. Try to make your communication with a user as friendly as possible, that is, the least restrictive to how user should enter countries. E.g. no difference for small/large caps, accept some common abbriviations, like US or USA for United States, or UK for United Kingdom. If an illegal value is entered (e.g. ‘new transavia’ for country), you can ask again or try to fix it – google for the Levenshtein distance. Then ask user to confirm your fix or change it to the right one. If your program fails to fix the illegal value for country name, then do not include it in the data loading routine. You may wish to use a text list of all countries in the world to define valid countries. Note that the We Feel Fine data set does not necessarily cover all of the countries in this list. don’t be overwhelmed with complexity of this part, start with basic prompt and then gradually increase functionality. Suggested features are desirable but not compulsory. 2. Allow the user a maximum of 5 countries to be successfully mined, although they are also allowed to enter less than 5 countries. Load corresponding data files from the folder countries. Successful mining occurs when the feelings for each country have been recorded and returned to your program. 3. For each feeling in the full list of over 5000 feelings and their frequencies determine the number of times each feeling appears in the mined text, for each country. For any counts that are larger than 0, you will need to retain the third column of information which is the hexadecimal equivalent of the colour of the prescribed feeling. 4. For each country, produce a plot of ellipses where each ellipse represents a feeling and have size proportional to the frequency of its occurrence and is coloured based on the full list of feelings referenced above. Ellipse position can be random. The code for this component is provided and explained below, however you will need to make a number of adjustments to it. 5. Run the base query of data file World.txt to determine the first 1500 feelings mined by We Feel Fine from anywhere in the world. We will compare these mined feelings with the chosen countries. There is
Subject python programming
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