Why use R if you know Excel and SPSS already?

You are pretty awesome at using Excel and SPSS. So why would you want to learn R? The following piece of code will answer that question:

library(rvest)

# Read in the raw data.
htmlpage <- read_html("http://www.kdnuggets.com/2016/06/r-python-top-analytics-data-mining-data-science-software.html")

# Extract all tables.
tables <- html_nodes(htmlpage, "table")

# Select a particular table.
ranking <- html_table(tables, fill = TRUE)[3][[1]]

# Display the data in the selected table.
ranking

           Tool 2016% share % change % alone
1             R         49%    +4.5%    1.4%
2        Python       45.8%     +51%    0.1%
3           SQL       35.5%     +15%      0%
4         Excel       33.6%     +47%    0.2%
5    RapidMiner       32.6%    +3.5%   11.7%
6        Hadoop       22.1%     +20%      0%
7         Spark       21.6%     +91%    0.2%
8       Tableau       18.5%     +49%    0.2%
9         KNIME       18.0%     -10%    4.4%
10 scikit-learn       17.2%    +107%      0%

# Plot the data in rainbow colors.
barplot(height = as.numeric(sub("%","",ranking$'2016% share')),
        names.arg = ranking$Tool,
        ylim = c(0,50),
        main = "Ranking software for data-analyse",
        xlab = "Tool",  
        ylab = "% market share 2016",
        col = rainbow(10),
        las = 2)

These few lines of code show how powerful R is:

1. It is very easy to read in unstructured data (eg. html) and structure it.
2. Data can be easily visualized.
3. The data shows that R is currently the #1 tool for data analysis. SPSS has not been included in this survey, but is outranked by R in other ones.

PS: This article has been written in R.