Adding New Inputs to a Chart of Monthly Operating Profits

[dsjensen]

I pulled some data from Fama French web site on operating data by month...here is my code that works (below).

I have 7 columns of data, with headers, including Date. I have successfully graphed one column data, but I would like to add several of the other columns of data to my chart with colors, and I'm struggling to add the additional columnar data. Suggestions? Thank you.

Step 1: Set Working Directory

setwd("c:/Users/Dean/OneDrive/Desktop")

Step 2: Call up Working Directory

getwd()

Step 3: Call up packages and libraries

install.packages("tidyverse")
library(tidyverse)
install.packages("rio")
library(rio)
install.packages("dplyr")
library("dplyr")

Step 4: Read FF_OP_Analysis_Since_1963

read.csv("c:/Users/Dean/OneDrive/Desktop/FF_OP_Analysis_Since_1963.csv")
read.csv("FF_OP_Analysis_Since_1963.csv")

Step 5: Create dataframe

df<-read.csv("FF_OP_Analysis_Since_1963.csv")

Install ggplot2 (if not already installed)

install.packages("ggplot2")

Load ggplot2

library(ggplot2)

Example: Calculate Operating Profit by Date

ggplot(data = df, aes(Date, SMALL_LoOP)) +
geom_line()

[dsjensen]

Also, here are the column names as well: Date, SMALL_LoOP, ME1_OP2, ME1_OP9, SMALL_HiOP, BIG_LoOP, BIG_HiOP

[FJCC]

Try the following. I don't have your data, so I couldn't test the code.

df |> select(Date, SMALL_LoOP, ME1_OP2, ME1_OP9, SMALL_HiOP, BIG_LoOP, BIG_HiOP) |> 
  pivot_longer(cols = -Date, names_to = "Variable", values_to = "Value") |> 
  ggplot(aes(x= Date, y = Value, color = Variable))

[dsjensen]

That looked like it set up the table properly, but you cannot see any lines on the chart...empty.

Data is an Excel CSV file...here is a snippet of the table:

Date	SMALL_LoOP	ME1_OP2	ME1_OP9	SMALL_HiOP	BIG_LoOP	BIG_HiOP
196307	-0.9657	-0.8294	-2.2346	2.5642	-1.0687	1.1313
196308	2.4333	2.6256	-0.6244	5.0913	6.2374	5.7975
196309	-2.1246	-0.031	3.6577	-0.7201	-4.9282	-0.5708
196310	1.549	-1.517	4.5372	-0.5986	-2.0294	10.3195
196311	-4.8866	-0.789	-5.7208	-3.999	1.6446	-4.3612
196312	-3.785	-1.3718	-0.1347	-2.1368	3.169	1.6677
196401	7.5529	5.147	2.9066	4.8603	0.2483	3.5718
196402	3.918	4.7447	2.8176	-0.2699	6.1887	2.1659
196403	2.7378	-0.1299	2.3133	3.7433	-1.7251	1.8864
196404	-0.6952	-0.7992	-0.2116	-1.4397	4.1876	1.3738
196405	1.5796	0.7386	2.2588	-1.7503	2.9169	3.6611
196406	2.3038	-3.4242	1.113	3.76	4.4891	0.2734
196407	3.8523	6.0508	1.8796	5.7071	-0.9219	2.3778
196408	-0.3194	2.6002	-2.3171	-1.8086	-5.4859	-1.1284
196409	2.4605	9.7302	5.6853	8.2176	1.8623	2.3715
196410	3.7606	-0.1009	1.3762	2.6976	1.373	-0.6697
196411	-1.4074	-0.9774	-2.6125	1.3333	-6.1009	-1.3031
196412	-1.5714	0.6171	-1.0029	-1.7434	-4.1665	1.2899
196501	8.4073	7.4467	12.068	7.2627	6.9792	6.1292

[dsjensen]

Here is a copy of the output now...

[FJCC]

Oops, I had a copy and paste failure. Try this:

df |> select(Date, SMALL_LoOP, ME1_OP2, ME1_OP9, SMALL_HiOP, BIG_LoOP, BIG_HiOP) |> 
  pivot_longer(cols = -Date, names_to = "Variable", values_to = "Value") |> 
  ggplot(aes(x= Date, y = Value, color = Variable)) + geom_line()

[dsjensen]

FJCC, that is AWESOME!!! Thank you.

Do you know what might be the best way to convert monthly data into annual (average) data? '

Thank you. This is very helpful for a personal research project.

[FJCC]

Here is code for computing a yearly average for each variable. The dates were coming in as integers, so I extracted the year by truncating the date/100

library(tidyverse)
df <- read.csv("~/R/Play/Dummy.csv")
ByYear <- df |> select(Date, SMALL_LoOP, ME1_OP2, ME1_OP9, SMALL_HiOP, BIG_LoOP, BIG_HiOP) |> 
  pivot_longer(cols = -Date, names_to = "Variable", values_to = "Value") |> 
  mutate(Year = trunc(Date/100)) |> 
  group_by(Year, Variable) |> 
  summarize(Avg = mean(Value, na.rm = TRUE))
#> `summarise()` has grouped output by 'Year'. You can override using the
#> `.groups` argument.
ggplot(ByYear, aes(x= Year, y = Avg, color = Variable)) + geom_line() +
  scale_x_continuous(breaks = 1963:1965)

^{Created on 2024-01-07 with reprex v2.0.2}

[dsjensen]

FJCC, thank you so much…you’ve saved me a ton of frustration and time.