Homework 1: Quarto, Basic Syntax and Data Importing

Spring 2024 MATH/COSC 3570 Introduction to Data Science by Dr. Cheng-Han Yu

Author

Insert Your Name!!

Published

May 2, 2024

1 Autobiography

  1. Please introduce yourself. You can share anything, your hometown, major, family, hobbies, working experience, honors and awards, special skills, etc, yes anything! Your autobiography should include:

    • At least two paragraphs (Paragraphs are separated by a blank line)
    • Bold text
    • Italic text
    • Text with both bold AND italic font (Not mentioned in class, but you should be able to figure it out)
    • Clickable text with a hyperlink
    • Blockquote
    • Listed items
    • emoji (Add emoji to your writing by typing :EMOJICODE:, check emoji cheatsheet)

    Your Self-Introduction:

2 Chunk Options

Please check the references https://quarto.org/docs/reference/cells/cells-knitr.html or https://yihui.org/knitr/options/ and answer the following questions.

  1. Please add your nice picture using knitr::include_graphics(). Please use

    1. echo to not to show the code

    2. fig-cap to add a figure caption

    3. fig-cap-location to put the caption on the margin.

  1. Use the chunk option

    1. echo to NOT to show library(tidyverse), library(ggplot2), and library(ggrepel). Note: you may need to use !expr. Check https://stackoverflow.com/questions/72217651/quarto-rmarkdown-code-block-to-only-display-certain-lines and https://quarto.org/docs/computations/r.html#chunk-options

    2. fig-align to have the figure right-aligned.

    library(tidyverse)
library(ggplot2)
class_avg <- mpg |> 
    group_by(class) |> 
    summarise(displ = median(displ), hwy = median(hwy))
library(ggrepel)
ggplot(mpg, aes(displ, hwy, colour = class)) + 
    geom_label_repel(aes(label = class), data = class_avg, size = 6, 
                     label.size = 0, segment.color = NA) + 
    geom_point() + theme(legend.position = "none")

  2. A Marquette student has a really bad code style. Please

    1. Add the chunk option tidy in the chunk labelled style to make her code below more readable.

    2. Add another option eval so that the code is NOT run.

for(k in 1:10){j=cos(sin(k)*k^2)+3;l=exp(k-7*log(k,base=2));print(j*l-5)}
[1] 4.966218
[1] -4.985713
[1] -4.998994
[1] -4.999823
[1] -4.999956
[1] -4.999988
[1] -4.999988
[1] -4.999991
[1] -4.999995
[1] -4.999996
  1. Use the chunk option results in the chunk labelled cat, so that the text output is “I love Marquette and Data Science!”.
cat("I love **Marquette** and *Data Science*!\n")
I love **Marquette** and *Data Science*!
  1. We can re-use a code chunk by using its name! Please create a code chunk and use the option #| label: photo to run the code in the code chunk named photo. Note that the chunk options are not carried.

3 Basic R

3.1 Vector

Use the built-in data set LakeHuron.

  1. Find the number of data values in LakeHuron.
  1. What is the highest and lowest level (in feet) of LakeHuron during the 1875-1972 period?
  1. Return a logical vector that shows whether the lake level is higher than the average level or not.
  1. Return years that have higher level than the average.

3.2 Data Frame

  1. Make the mtcars dataset as a tibble using as_tibble(). Call it tbl.
  1. Print the sub data of tbl that contains the 11th to 15th rows and the last three columns.
  1. Grab the second and the third columns of tbl using list method and their name. (Do NOT use matrix method, and their index)
  1. Extract the fourth column of tbl as a numerical vector.

  1. Start with tbl, use the pipe operator |> to do the followings sequentially.

    1. extract the first 10 observations (rows)

    2. find the column names

    3. sort the columns names using sort() in a decreasing order. (alphabetically from z to a)

3.3 Data Importing

  1. Read the data sales.xlsx from the data folder. Use arguments sheet, skip and col_names so that the output looks like

    # A tibble: 9 x 2
  id      n    
  <chr>   <chr>
1 Brand 1 n    
2 1234    8    
3 8721    2    
4 1822    3    
5 Brand 2 n    
6 3333    1    
# … with 3 more rows
  1. Read in the favourite-food.xlsx file from the data folder and call the data fav_food. Use the argument na to treat “N/A” and “99999” as a missing value. Print the data out.

4 Basic Python

import numpy as np
import pandas as pd

4.1 Data Frame

  1. Import the data set mtcars.csv using pd.read_csv(). Then print the first five rows.
  1. Use method .iloc to obtain the first and fourth rows, and the second and third columns. Name the data dfcar.
  1. Set the row names of dfcar to Mazda and Hornet.
  1. Use method .loc to obtain row Hornet and column disp.