Histogram
One of the most frequently encountered visualizations for continuous variables is the histogram.
Histogram: Bin similar values into a group, then plot the frequency of occurrence of the data values in each bin as the height of the corresponding bar.
A call to a function to create a histogram has to contain the name of the variable that creates the bins and then tabulates the counts. With the Histogram() function, that variable name is the first argument passed to the function, and often, as in this example, the only argument passed to the function.
First read the Employee data included as part of lessR.
##
## >>> Suggestions
## Details about your data, Enter: details() for d, or details(name)
##
## Data Types
## ------------------------------------------------------------
## character: Non-numeric data values
## integer: Numeric data values, integers only
## double: Numeric data values with decimal digits
## ------------------------------------------------------------
##
## Variable Missing Unique
## Name Type Values Values Values First and last values
## ------------------------------------------------------------------------------------------
## 1 Years integer 36 1 16 7 NA 15 ... 1 2 10
## 2 Gender character 37 0 2 M M M ... F F M
## 3 Dept character 36 1 5 ADMN SALE SALE ... MKTG SALE FINC
## 4 Salary double 37 0 37 53788.26 94494.58 ... 56508.32 57562.36
## 5 JobSat character 35 2 3 med low low ... high low high
## 6 Plan integer 37 0 3 1 1 3 ... 2 2 1
## 7 Pre integer 37 0 27 82 62 96 ... 83 59 80
## 8 Post integer 37 0 22 92 74 97 ... 90 71 87
## ------------------------------------------------------------------------------------------To illustrate, consider the continuous variable Salary in the Employee data table. Use Histogram() to tabulate and display the number of employees in each department, here relying upon the default data frame (table) named d.
Histogram of tablulated counts for the bins of Salary.
## >>> Suggestions
## bin_width: set the width of each bin
## bin_start: set the start of the first bin
## bin_end: set the end of the last bin
## Density(Salary) # smoothed density curves plus histogram
## Plot(Salary) # Violin/Box/Scatterplot (VBS) plot
##
##
## --- Salary ---
##
## n miss mean sd min mdn max
## 37 0 73795.557 21799.533 46124.970 69547.600 134419.230
##
##
## (Box plot) Outliers: 1
##
## Small Large
## ----- -----
## 134419.2
##
##
## Bin Width: 10000
## Number of Bins: 10
##
## Bin Midpnt Count Prop Cumul.c Cumul.p
## ---------------------------------------------------------
## 40000 > 50000 45000 4 0.11 4 0.11
## 50000 > 60000 55000 8 0.22 12 0.32
## 60000 > 70000 65000 8 0.22 20 0.54
## 70000 > 80000 75000 5 0.14 25 0.68
## 80000 > 90000 85000 3 0.08 28 0.76
## 90000 > 100000 95000 5 0.14 33 0.89
## 100000 > 110000 105000 1 0.03 34 0.92
## 110000 > 120000 115000 1 0.03 35 0.95
## 120000 > 130000 125000 1 0.03 36 0.97
## 130000 > 140000 135000 1 0.03 37 1.00The Histogram() function provides a default color theme. The function also provides the corresponding frequency distribution, summary statistics, the table that lists the count of each category, from which the histogram is constructed, as well as an outlier analysis based on Tukey’s rules for box plots.
