library(tidyverse)Download the compressed file, bikeshare-2011-01-01.zip,
from the Files section in our Canvas web-site. Extract the file,
bikeshare-2011-01-01.zip, so that you can use the file,
bikeshare-2011-01-01.csv. Read the data file,
bikeshare-2011-01-01.csv, as the data.frame object with the
name, bikeshare2011_01_01, using (1) the
read_csv() function and (2) the absolute path name
of the file bikeshare_2011_01_01.csv from your local hard
disk drive in your laptop.
Report the mean, median, minimum, maximum, and standard deviation for
each numeric variable in the data.frame
bikeshare2011_01_01.
Read the data file, bikeshare_cleaned.csv, as the
data.frame object with the name, bikeshare, using (1) the
read_csv() function and (2) its URL,
https://bcdanl.github.io/data/bikeshare_cleaned.csv.
Use the data.frame bikeshare for the rest of questions
in Question 2.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the distribution of cnt.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the distribution of cnt by
year and month.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the distribution of temp by
year and month.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the distribution of hum by
year and month.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the distribution of windspeed by
year and month.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between temp and
cnt.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between temp and
cnt by year and month.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between weather_cond
and cnt.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between weather_cond
and cnt by hr.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between wkday and
cnt.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between wkday and
cnt by hr.
Read the data file, NY_school_enrollment_socioecon.csv,
as the data.frame object with the name,
NY_school_enrollment_socioecon, using (1) the
read_csv() function and (2) its URL,
https://bcdanl.github.io/data/NY_school_enrollment_socioecon.csv.
For description of variables in
NY_school_enrollment_socioecon, refer to the file,
ny_school_enrollment_socioecon_description.zip, which is in
the Files section in our Canvas web-page. (I recommend you to extract
the zip file, and then read the file,
ny_school_enrollment_socioecon_description.csv, using Excel or
Numbers.)
Provide both (1) ggplot codes and (2) a couple of
sentences to describe the relationship between college enrollment and
educational attainment of population 45 to 64 years, and how such
relationship varies by the type (public or private) of colleges.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe how the relationships described in Q3b vary by
gender of population 45 to 64 years.
Provide both (1) ggplot codes and (2) a couple of
sentences to describe how the relationships described in Q3b vary by
gender of college enrollment.