Objective: Practice fetching data and utilizing it in R to gather basic numerical information about it while also displaying graphs in ggplot.
The dataset: ramen.csv. The Ramen Rater is a product review website for the hardcore ramen enthusiast (or "ramenphile"), with over 2500 reviews to date. This dataset is an export of "The Big List" (of reviews), converted to a CSV format. The data set we are using is part of this dataset (Kaggle Intro). Each record in the dataset is a single ramen product review. Review numbers are contiguous: more recently reviewed ramen varieties have higher numbers. Brand, Variety (the product name), Country, and Style (Cup? Bowl? Tray?) are pretty self-explanatory. Stars indicate the ramen quality, as assessed by the reviewer, on a 5-point scale; this is the most important column in the dataset.
Case Study Questions:
1. Explore the data with group_by and summarise(grouped_data_name, count = n()) and other functions and answer: How many countries are reviewed in this data? How many brands from each country? (Hint: nlevels(as. f actor(Variable_name)) gives the number of levels in that factor, nlevels() only works on factor type of variables).
2. How many observations have "Top Ten" rating? What brands are they? (For the ones without "top ten" rating, the data is missing as "NA")
3. From above, which brand received the most "Top Ten" awards? Have any of you has this brand before?
4. How many brands have average star rating =5? (Hint: mean() only works on numeric variables)
5. Which country makes the best ramen? How did you define “best”? Why?
6. To explore the proportions of different ramen styles in each country:
(6a) Define a data frame "data_style" with observations have style "Bowl", "Cup", "Pack" or "Tray".
(6b) Use the new data frame "data_style" in ggpplot(), choose the right arguments for "geom_bar()" then add "facet_wrap()", to reproduce the above plot.
(6c) Based on the plot, what seems to be the most popular style?
What I Did: I infered what R outputs would give the answer of the questions and then worked on coding that would me lead me to that exact desired output.
Outcomes: I learned more about manipulation and filtering of dataframes through the tidyverse library. Gained experience in data visualization through the ggplot library.
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Objective: Practice fetching data and utilizing it in R to gather basic numerical information about it.
The dataset: bay_area_boba_spots.csv recorded 603 boba spots across the bay area. The variables include the Yelp id of the boba shop, name of the boba shop, Yelp rating of the boba shop, on a scale of 1-5, Address of the boba shop, City the boba shop is located in, Latitude and the Longitude of the boba shop.
Case Study Questions:
1. Define a variable "Group members" to show all your group member’s names.
2. How many different boba brands are in the data? Can you define a variable to give me two brands you or your teammates have been to among those? Can you define a variable to give me your rating for these two brands?
3. What are the Yelp ratings of the two brands you chose? Use a logic operation to compare the Yelp rating and your rating to see which one is higher. If there are more than one rating for the same brand, use the average of the ratings.
4. How many boba stores have ratings greater or equal to 4.5?
5. How many boba stores have ratings greater or equal to 4.5 are from Fremont?
6. How many boba stores have ratings equal to 5? Can you give me the names of the stores?
7. I want to go to "Happy Lemon Berkeley" (the name) in Berkeley, can you find the address?
8. Find the lowest Yelp rating, and tell me which store(s) are they.
What I Did: I infered what R outputs would give the answer of the questions and then worked on coding that would me lead me to that exact desired output.
Outcomes: I learned about how R is used to extract data from files and make a basic numerical study on it.
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Objective: Practice using loops and scanner system in Java.
What I Did: I coded a program that allows a user to play Mastermind with the computer. The goal of the game is to try to guess the secret 4-letter word in 7 tries. Clues that are given are: 1) An 'O' means the user guessed the correct letter in the correct position and 2) An 'X' means the user guessed the correct letter but in the wrong position.
Outcomes: I learned about interactive programing in Java. Gained better understanding of the complex use of for and while loops.
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Objective: Practice using files and classes in Python. Learn about sorting algorithms
What I Did: I coded a program that reads a file I manually created containing comma-separated data about several pet animals, with each line containing data about one pet. Once read by my program, the data is stored in different object classes depending on the type of animal. In order to do this, I had to code a different python file with all the animal object-type in it, essentially naming the object file pets.py. I then imported that file into my main program that'll read the .txt file with all the pets I listed with their data. After a data-object is created, it is added to one big pets list menu and all operations are performed on that menu. The menu consisted of: 1. Show pet names (displays only the names of all the pets) 2. Search for pet (asks the user for the name of a pet. If the pet is in the list, it'll print all the details for that pet and the index in the list where it was found. If the pet is not in the list, a message will display telling the user that the pet is not in the list) 3. Show list (displays the entire pet list) 4. Show pets of a certain type (asks the user what kind of pet (dog/cat/fish/bird/…) to display, then displays a list of only pets of that type) 5. Exit the program. I also implimented user input validation for the menu.
Outcomes: I learned about object-oriented programing. Gained experiencing in creating sorting algorithms. Upgraded my skills in coding interactive programs.
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Objective: Learn to use Flask. Familiarize myself with importing external modules. Gain experience using an API to get information. Learn to build an interactive Web-app.
What I Did: built a Web app in python that displays daily stock prices obtained through an Application Program Interface (API) from an online service that provides free stockmarket information. I first coded a Search page for the user to look up stock information by typing in the company's stock symbol. If the stock symbol exists, the program will run to show the stock information onto the screen. To do so, I conducted some data manipulation to extract the stock's opening price, high price, low price, and current price, and displayed them through a website page in html. I also displayed the extracted data into a text document from a file output. If the user has inputed a stock symbol that doesn't exist, then the program would display a page telling the user the stock was not found and to go back to the initial Search page and try again, with a Back link.
Outcomes: I learned about and how to use API keys to read and obtain data. I also learned to do data splitting into strings and various techniques of data manipulation. I learned how to code HTML in python.
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Objective: Practice creating and using dictionaries, processing strings, reading files, and handling user input.
What I Did: I coded a program that reads GettysburgAddress.txt file and counts all the words. As the program reads the file, it'll create a dictionary where the words are keys and the number of times each word is in the file is the value. I also converted all the words to lower case to not create different keys with the same word. After all the words from the file have been added to the dictionary with their respective counts, the program will ask the user to enter a word. If the word the user enters is in the dictionary, the screen will display the number of times the word was found in the file. If the word is not in the dictionary, the program will tell the user “That word isn’t in the file” and ask for another word. If the user enters nothing (i.e., an empty string), then it'll tell the user “Goodbye!” and exit the program.
Outcomes: I was able to successfully create what I needed to do for this project and gained practice on how to create and use dictionaries in python. I upgraded my skills on processing strings and reading files in python. I was also able to successfully solve all the bugs that had occurred as I had a friend test my program to pick out those bugs. Thus, I also gained more skills on debugging.
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