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Community Contributions for EDAV Fall 2022 Tues/Thurs

57 Waterfall chart using meta income statement

Soheil Fakhrieh Kashan

57.0.1 Why to use Waterfall chart?

Waterfall chart is one of the most popular data visualizations in the Consulting and Finance presentations. The chart has a similar presentation as a bar chart but only highlights the positive or negative cumulative sequential impact variables. The purpose of a waterfall chart is mostly to explain how one number relates to another number through a series of variables or events. For example, we can effectively visualize how a company’s revenue is changed from one year to the next and what factors positively or negatively contributed to it.

57.0.1.1 Data Source

In this short tutorial we will be exploring META’s quarterly income statement and use Waterfall charts to visualize their Q3 - 2022 financial statement.

META Quarterly Earnings reports: https://investor.fb.com/financials/default.aspx

#### Data prep

## downlaod the Q3-2022 META's Income Statement from the above link
## read the Excel file

META_IS <- read_excel('resources/waterfall_plot_meta_income_statement/Downloadable-PL-Q3-2022.xlsx')

## select relevant revenue lines for the waterfall chart
META_summary <- META_IS[c(10,11,12,13,40,41,43),]

## remove empty columns
remove_na <- function(x) any(!is.na(x))
META_summary <- 
  META_summary |> select(where(remove_na))

## renaming variables
colnames(META_summary) <- c('Breakdown','Q3-2020', 'Q4-2020', 'Q1-2021', 'Q2-2021',
                            'Q3-2021', 'Q4-2021', 'Q1-2022', 'Q2-2022', 'Q3-2022')

57.0.2 Waterfall library

57.0.2.1 META Q3-2022 Income Statement

  • To use this library, the data frame must contain two columns. One with numeric values, and one with categorical variable showing the labels.

  • The order of the records on the label field will be the order on the graph. If that order is not desirable, you need to change the order of the records.

# For this cahrt we are going to use Q3-2022
# Selecting the income statement breakdown and one quarter
waterfall(META[,c(1,3)])+
  ggtitle('META Q3-2022 Income Statement Waterfall')+
  labs(x='Income Breakdown', y='$MM')+
  theme_minimal()

57.0.2.2 Improving the chart

  • Add a total calculation to show the final summation: calc_total = TRUE
  • Change the text size to make it larger: rect_text_size = 1.5
  • Change the scale to show dollar: scale_y_continuous(labels = dollar) 
# 'META Q3-2021 Income Statement Waterfall chart
waterfall(
  META_cond[,c(1,3)],
  rect_text_size = 1.5,
  rect_text_labels_anchor = "centre",
  calc_total = TRUE, 
  fill_by_sign = TRUE,
  total_rect_color ='Dark Green',
  total_axis_text ='Income')+
  ggtitle('META Q3-2021 Income Statement Waterfall')+
  labs(x='Income Breakdown', y='$MM')+
  theme_minimal()+
  scale_y_continuous(labels = dollar)

57.0.2.3 How year-over-year quarterly income changed?

  • Create two new records. One for the Q3-2021 and one for Q3-2022.
  • For the income breakdown categories, calculate the delta between two periods
kable(META_QoQ)
breakdown Amount
Income-Q3-2021 10423
Advertising -1039
Other revenue 16
Reality Labs -273
Cost of revenue 55
Research and development -2854
Marketing and sales -226
General and administrative -438
Income-Q3-2022 5664 
# META Q3-2022 to Q4-2022 Income Waterfall chart
waterfall(META_QoQ,
          # changing the text size
          rect_text_size = 1.5,
          # selecting desired colors for each bar
          fill_colours = c("seagreen", "orangered2", "seagreen", "orangered2",
                           "seagreen", "orangered2","orangered2","orangered2",
                           "seagreen"),
          # changing the default fill by sign so we can assign individual color          
          fill_by_sign = FALSE)+
  ggtitle('META Q3-2022 to Q4-2022 Income')+
  labs(x='Income Breakdown', y='$MM')+
  theme_minimal()+
  scale_y_continuous(labels = dollar)

From the waterfall chart we can observe that Q3-2022 income is significantly lower than the last year. This is a mainly driven by the increase in expenses in research and development, and the decrease in revenue from advertising.

57.0.2.3.1 Using plotly to create simple waterfall

Alternatively we can use plotly to create interactive waterfall charts. https://plotly.com/r/waterfall-charts/

wf <- plot_ly(
  META_cond[,c(1,3)], type = "waterfall",
  ## list the breakdown. if the list is not specified. plotly order the categories alphabetically.
  x = ~list('Advertising', 'Reality Labs', 'Other revenue',
            'Research and development', 'Cost of revenue',
            'Marketing and sales', 'General and administrative'), 
  textposition = "outside", y= ~META_cond$`Q3-2022`) 
wf <- wf %>%
  layout(title = "META Q3-2022 Income Statement Waterfall ",
         xaxis = list(title = "Income Breakdown"),
         yaxis = list(title = "$MM"),
         autosize = TRUE,
         showlegend = TRUE)

wf