W2 Deliverable

Quarto

Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see https://quarto.org.

Running Code

When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.3     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(esquisse)
library(ggplot2)
library(dplyr)

github_url <- "https://raw.githubusercontent.com/t-emery/sais-susfin_data/main/datasets/etf_comparison-2022-10-03.csv"

blackrock_esg_vs_non_esg_etf <- github_url |> 
  read_csv() |> 
  select(company_name:standard_etf)

Rows: 537 Columns: 14
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (4): ticker, company_name, sector, esg_uw_ow
dbl (7): esg_etf, standard_etf, esg_tilt, esg_tilt_z_score, esg_tilt_rank, e...
lgl (3): in_esg_only, in_standard_only, in_on_index_only

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

ggplot(blackrock_esg_vs_non_esg_etf) +
  aes(x = esg_etf, y = standard_etf, colour = sector) +
  geom_point(shape = "circle", size = 1.5) +
  geom_smooth(span = 0.75) +
 scale_color_hue(direction = 1) +
  scale_x_continuous(trans = "log10") +
  scale_y_continuous(trans = "log10") +
  labs(
    x = "ESG ETF (ESGU)", y = "Standard ETF (IVV)", title = "ESG Fund vs. Non-ESG Fund", subtitle = "We made this chart using esquisse!", caption = "ValeriaLee"
  ) +
  theme_minimal() +
  facet_wrap(vars(sector))

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Warning: Removed 261 rows containing non-finite values (`stat_smooth()`).

blackrock_esg_vs_non_esg_etf_long <- blackrock_esg_vs_non_esg_etf |> 
  pivot_longer(cols = contains("etf"), names_to = "fund_type", values_to = "weight") |> 
  mutate(fund_type = case_when(fund_type == "esg_etf" ~ "ESG ETF (ESGU)",
                               fund_type == "standard_etf" ~ "Standard ETF (IVV)"))
blackrock_esg_vs_non_esg_etf_long

# A tibble: 1,074 × 4
   company_name                  sector                 fund_type         weight
   <chr>                         <chr>                  <chr>              <dbl>
 1 PRUDENTIAL FINANCIAL INC      Financials             ESG ETF (ESGU)    0.537 
 2 PRUDENTIAL FINANCIAL INC      Financials             Standard ETF (IV… 0.106 
 3 GENERAL MILLS INC             Consumer Staples       ESG ETF (ESGU)    0.552 
 4 GENERAL MILLS INC             Consumer Staples       Standard ETF (IV… 0.151 
 5 KELLOGG                       Consumer Staples       ESG ETF (ESGU)    0.453 
 6 KELLOGG                       Consumer Staples       Standard ETF (IV… 0.0592
 7 AUTOMATIC DATA PROCESSING INC Information Technology ESG ETF (ESGU)    0.649 
 8 AUTOMATIC DATA PROCESSING INC Information Technology Standard ETF (IV… 0.312 
 9 ECOLAB INC                    Materials              ESG ETF (ESGU)    0.441 
10 ECOLAB INC                    Materials              Standard ETF (IV… 0.118 
# ℹ 1,064 more rows

blackrock_esg_vs_non_esg_etf_long |>
 filter(weight >= 1L & weight <= 7L) |>
 ggplot() +
 aes(x = weight, y = company_name, colour = fund_type, size = weight) +
 geom_point(shape = "circle") +
 scale_color_manual(values = c(`ESG ETF (ESGU)` = "#009999", `Standard ETF (IVV)` = "#D6604D"
)) +
 labs(x = "Weight", y = "Company Name ",title = "Blackrock ETF", subtitle = "ESG Funds vs. non-ESG FUnds", caption = "ValeriaLee") +
 theme_minimal()

ggplot(blackrock_esg_vs_non_esg_etf_long) +
  aes(x = sector, y = weight, colour = fund_type) +
  geom_point(shape = "circle", size = 1.5) +
  scale_color_hue(direction = 1) +
  labs(x= "Sector", y = "Weight", title = "Weight on Different Sectors ", caption = "ValeriaLee"
  ) +
  theme_minimal()

ggplot(blackrock_esg_vs_non_esg_etf) +
  aes(x = esg_etf, y = sector) +
  geom_col(fill = "#009999")+
  labs(x = "Number of ESG ETFs", y = "Sector", title = "Number of ESG ETFs in each sector", caption = "ValeriaLee") +
  theme_minimal()

ggplot(blackrock_esg_vs_non_esg_etf) +
  aes(x = esg_etf, y = standard_etf, color = sector) +
  geom_point(shape = "circle", size = 1.5) +
  scale_color_hue(direction = 1) +
  geom_smooth() +
  scale_x_continuous(trans = "log10") +
  scale_y_continuous(trans = "log10") +
  theme_minimal()

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Warning: Removed 261 rows containing non-finite values (`stat_smooth()`).

ggplot(blackrock_esg_vs_non_esg_etf) +
  aes(x = esg_etf, y = standard_etf, colour = sector) +
  geom_point(shape = "circle", size = 1.5) +
  geom_smooth() +
  scale_color_hue(direction = 1) +
  scale_x_continuous(trans = "log10") +
  scale_y_continuous(trans = "log10") +
  theme_minimal()

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Warning: Removed 261 rows containing non-finite values (`stat_smooth()`).

ggplot(blackrock_esg_vs_non_esg_etf) +
  aes(x = esg_etf, y = standard_etf, colour = standard_etf) +
  geom_point(shape = "circle", size = 1.5) +
  geom_smooth() +
  scale_color_gradient(low = "#009999", high = "#D6604D") +
  scale_x_continuous(trans = "log10") +
  scale_y_continuous(trans = "log10") +
  theme_minimal()

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Transformation introduced infinite values in continuous y-axis

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Warning: Removed 261 rows containing non-finite values (`stat_smooth()`).

Warning: The following aesthetics were dropped during statistical transformation: colour
ℹ This can happen when ggplot fails to infer the correct grouping structure in
  the data.
ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
  variable into a factor?

ggplot(blackrock_esg_vs_non_esg_etf) +
 aes(x = standard_etf, y = sector) +
 geom_boxplot(fill = "#009999") +
 scale_x_continuous(trans = "log10") +
 labs(x = "Standard ETFS", 
      y = "Sector", 
      title = "Boxplot of Standard ETFs in each sector")

Warning: Transformation introduced infinite values in continuous x-axis

Warning: Removed 35 rows containing non-finite values (`stat_boxplot()`).

library(ggthemes)
library(ggplot2)

ggplot(blackrock_esg_vs_non_esg_etf_long, aes(x = company_name, y = weight)) +
  geom_point() + 
  geom_segment( aes(x = company_name, xend = company_name, y = 0, yend = weight)) +
  labs(x = "Company Name", y = "Weight", title = "Lollipop Plot of Company Weighted")

The echo: false option disables the printing of code (only output is displayed).