I am doing research on the pandemic on Net Sales figures of companies in different industries. For this I have a dataset containing Net Sales figures of companies of the different industries. Now I would like to create plots per industry on one graph with 1 line corresponding to the aggregated Net Sales per year (from 2010-2020), and the other being a trend line from 2010-2019 onto 2020 (so the expected Net Sales for 2020 taking the previous years into account). This way I have a visual aid to see whether 2020 has seen significantly worse numbers. I have gotten the first graphs (aggregated Net Sales per year per industry) sorted using dplyr
with:
library(ggplot); library(tidyverse) Industries <- df %>% group_by(NAICS, Year) %>% summarize(Sales = mean(`Net Sales`)) Industry_Plot <- ggplot(data = Industries, aes(Year, Sales)) + theme_bw() + theme(axis.text.y = element_blank(), axis.ticks.y = element_blank(), panel.grid = element_blank()) + geom_line(color = "steelblue", size = 1)
Now for the second part, I need to know:
- How to graph the trend line per industry for 2020, and
- How can I combine these onto 1 graph.
I have included a 'dput()' sample of my dataset for one industry below (these are the aggregated Net Sales for one industry (NAICS):
Industries <- structure(list(NAICS = c(315, 315, 315, 315, 315, 315, 315, 315, 315, 315, 315), Year = c(2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020), Sales = c(1839.94, 2227.27, 2203.9, 2421.88, 2681.7, 2789.2, 2834.07, 2944.34, 3129.65, 3213.13, 2757.85)), row.names = c(NA, -11L), groups = structure(list(NAICS = 315, .rows = structure(list(1:11), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr", "list"))), row.names = 1L, class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"))
I am at a total loss. Thanks in advance for helping me.
https://stackoverflow.com/questions/67400117/adding-linear-trend-lines-using-subsets-of-data-to-a-time-series-graph-in-ggplot May 05, 2021 at 07:09PM
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