R Percentage Plot
How to make pie charts in R using plotly. The interquartile range is the middle range of the distribution, defined by Q3 minus Q1. Department of Agriculture. Calculating Sample Size for Stratified Random Sample. You can also do this in a non-ggplot() paradigm using base plotting utilities as described in this R-bloggers post. A new, independent comedy film released this month has an unexpected detail folded into its plot that serves as the jumping-off point for the story it aims to tell: a reverse mortgage. You now need to replace the plotting symbols for the fit y values points with connecting lines. the median is the value at the 50% mark. The plot below had the dates on the x-axis set as biannual. Data visualization is perhaps the fastest and most useful way to summarize and learn more about your data. This plot shows the relation between the height ratio of US presidents and the percentage of the popular vote. References. 15 Questions All R Users Have About Plots There are different types of R plots, ranging from the basic graph types to complex types of graphs. Land Loans in India are therefore an accepted, widely used facility, not just for building dream homes but also for commercial business plants/factories and more as long as. The box plot is also referred to as box and whisker plot or box and whisker diagram. Know how to interpret a correlation coefficient, r in terms of (coefficient of determination) percent of variance, r 2. You can also use Excel to create a simple normal probability plot:. ggplot2 is a plotting package that makes it simple to create complex plots from data stored in a data frame. Getting ready Once again in this recipe, we will use the browsers. Get Example Data. See Styling Visual Attributes for information about how to customize the visual style of plots, and Configuring Plot Tools for information about changing or specifying tools. plot(y, rank(y)) would give the same result, provided every value was different. R: ggplot - Plotting multiple variables on a line chart. We’ll study the decompose( ) function in R. Step 2: 1) Under Select Column(s): --> click Credit Score and Interest Rate (percent). There are cartodb and mapbox which are great for creating server-"baked" tilesets, leaflet and d3. A segment. I plotted normal probability plot in R using qqnorm and qqline. The function coord_polar() is used to produce a pie chart, which is just a stacked bar chart in polar coordinates. One of the core strengths of owning a piece of land is the fact that it can be used to construct your dream home on it. • Values of r near 0 indicate a very weak linear relationship. the percentage (number of respondents as a percentage of the total). com, run by Yan Holtz, is a useful collection of examples of many kinds of graphics drawn with ggplot and other R tools. To set up a stem-and-leaf plot we follow some simple steps. The y-axis thus represents the change from baseline in the response, usually expressed as a percentage, for e. CHAPTER 2 AND 10: Least Squares Regression plot and normal probability the correlation r. Pie Charts. For Example 1, find the percent of variation in actual volume of. See Colors (ggplot2) and Shapes and line types for more information about colors and shapes. One of the core strengths of owning a piece of land is the fact that it can be used to construct your dream home on it. (1) global. By default the arguments are evaluated with feval (@plot, x, y). From the second example you can observe that, the White color products are least selling in all the. The initial non annotated plot First, let’s make a faceted line plot with the mtcars data set. Jul 22, 2016 · Plot percentages on y-axis. It could be in the ground for over 6 months before the season begins. plot provides a simplified interface to this function. - gist:7742291. 66667 Female. The rdrobust package provides Stata and R implementations of statistical inference and graphical procedures for Regression Discontinuity designs employing local polynomial and partitioning methods. The likert package can be used to produce attractive summaries and plots of one-sample or one-way Likert data. Simple scatterplot: Some customization and a line of best t:. diverging stacked bar charts, with ggplot only, with example data from the Arab Barometer III survey. The R Project for Statistical Computing Getting Started. Here is the data that am working on: Village 100 200 300 400 500 Male 68. Maps in R – Examples (Part 1). The n th percentile of an observation variable is the value that cuts off the first n percent of the data values when it is sorted in ascending order. (1 reply) Dear R-users, Though it's a silly thing to ask, but I'm not getting a way out. By default R assumes the rank of tied values is their mean rank. Split-Plot Design in R. 4 add_fun data a data frame. Tutorial for new R users whom need an accessible and easy-to-understand resource on how to create their own histogram with basic R. Percent formatter: multiply by one hundred and display percent sign. Cheat Sheet for R and RStudio L. A useful first step when analyzing the distribution of a set of data is to plot a histogram. This communicates a bit less than the bar and line plots since it gives up the y/size aesthetic for communicating Percentage. the predicted values of the dependent variable on the x-axis. 10 Plotting and Color in R. Typically, you'll want to type in two columns of data, one categorical and one quantitative (numerical). Thus the height of a rectangle is proportional to the number of points falling into the cell, as is the area provided the breaks are equally-spaced. Plot the data before fitting models Plot the data to look for multivariate outliers, non-linear relationships etc. A pie-chart is a representation of values as slices of a circle with different colors. We focus on the people, the common citizen, stories untold by traditonal media. The R result to our eyes are more attractive; to mimic them exactly in SAS would require drawing much of the content from primitives. The bubble plot below combines the usefulness of the standard scatter plot with the additional data provided by varying bubble sizes. R with the source function, and then loaded counties. The package is somewhat finicky with the form the data it accepts, however. This tutorial will use a linear equation to create a table of values for Y when given a set of x values. Learn how to use the ggplot2 library in R to plot nice-looking graphs and find out how to customize them in this step-by-step guide. The first time I made a bar plot (column plot) with ggplot (ggplot2), I found the process was a lot harder than I wanted it to be. Figure objects have many glyph methods that can be used to draw vectorized graphical glyphs:. So for now I have turned off the plot below and you'll have to imagine it! This post created in RStudio using knitr. The n th percentile of an observation variable is the value that cuts off the first n percent of the data values when it is sorted in ascending order. Sounds like something Power BI can do!. Dot plots are great for solving basic math problems from anything to advanced math problems. People like percentages too, so a bar chart with counts on the y axis but percentage labels is a useful thing to be able to produce. To create a scree plot of the components, use the screeplot function. Now we want to plot our model, along with the observed data. Plot the data before fitting models Plot the data to look for multivariate outliers, non-linear relationships etc. Sometimes it's handy to alter your labels a little, perhaps adding units or percent signs without adding them to 2/19/2015 Beautiful plotting in R: A ggplot2. Project jpeg doesn't have any custom web pages. Feel free to suggest a chart or report a bug; any feedback is highly welcome. Therefore, if you produce multiple plots by submitting multiple plot requests and using the OVERLAY option, the plot requests must be ordered in the PLOT statement so that the plot request that produces the lowest line values is the first (leftmost) plot request, the plot request that produces the next lowest line values is the second plot. To make our work easier and more comparable to other techniques, we will use a LabDSV function called pco() which simply calls cmdscale with specific arguments, and provides more convenient plotting routines. Plotting Dates See the lubridate library. The regression equation is reported as y=-23. Absolute differences or the difference as a percentage of the analyte concentration can be plotted. R Tutorial Series: Graphic Analysis of Regression Assumptions An important aspect of regression involves assessing the tenability of the assumptions upon which its analyses are based. How to make pie charts in R using plotly. How to plot cumulative distribution function in R? I know there is density and curve for density functions, but what about plotting distribution functions? The ecdf function provides one method when the distribution function is not known. First-time users should use rpart. I plotted normal probability plot in R using qqnorm and qqline. The option OUTSIDE(0. I would label the graph "percentage change" and let the negative sign indicate that the change is a decrease. P-P plots are vastly used to evaluate the skewness of a distribution. He was asking for basic R plot rather than ggplot2 - Puriney Jul 22 '16 at 22:13. Before you get into plotting in R though, you should know what I mean by distribution. How to plot cumulative distribution function in R? I know there is density and curve for density functions, but what about plotting distribution functions? The ecdf function provides one method when the distribution function is not known. factor(rep(c. Box-and-whisker plots are a handy way to display data broken into four quartiles, each with an equal number of data values. To change the plotting order of values, click the vertical (value) axis. That’s why technology like Minitab or SPSS is a good idea to make these types of graphs. The bottom of the graph (the y-axis) is almost always percent, going from 0-100%. Highcharts - Interactive JavaScript charts for your web pages. to present summary statistics of the graph itself. This is by no means an exhaustive catalog. 15 Questions All R Users Have About Plots There are different types of R plots, ranging from the basic graph types to complex types of graphs. SCALE=LOG and SCALE=SQRT plot-options are also available to plot log frequencies and square roots of frequencies, respectively. The basic syntax for creating a pie chart using the R is:. In Part 1 of this series, we got started by looking at the ts object in R and how it represents time series data. A standard bar plot can be a very useful tool, but it is often conveying relatively little information-how one variable varies across some grouping variable. You wish you could plot all the dimensions at the same time and look for patterns. Plotting gain chart Gain chart is a popular method to visually inspect model performance in binary prediction. Adding a legend to differentiate each bubble puts all four data sets together. Contribute to jbryer/likert development by creating an account on GitHub. Box-and-whisker plots are a handy way to display data broken into four quartiles, each with an equal number of data values. Application Themes. The primary package of interest is ggplot2, which is a plotting system for R. It deals with the restructuring of data: what it is and how to perform it using base R functions and the {reshape} package. We look at some of the ways R can display information graphically. Generate an online stem and leaf plot, or stemplot, and calculate basic descriptive statistics for a sample data set with 4 or more values and up to 5000 values, all non-negative. Analysis of similarities (ANOSIM) provides a way to test statistically whether there is a significant difference between two or more groups of sampling units. R Statistical Package. For example, instead of knowing a tree's height at age 10, we want to know how much it's grown between age 5 and age 10, so that can be a bar in our graph. Population Growth Models Part 2: The Natural Growth Model The Exponential Growth Model and its Symbolic Solution. Plotting with ggplot2. Downloadable data is available to use with this tutorial at. Capacitors in series and parallel. In 1977, John Tukey published an efficient method for displaying a five-number data summary. P-P plots are vastly used to evaluate the skewness of a distribution. The initial non annotated plot First, let’s make a faceted line plot with the mtcars data set. other alternatives, such as frequency polygon, area plots, dot plots, box plots, Empirical cumulative distribution function (ECDF) and Quantile-quantile plot (QQ plots). 15 Questions All R Users Have About Plots There are different types of R plots, ranging from the basic graph types to complex types of graphs. Plots of mineral contents in soil samples from the upper and lower mineral soil horizons at sites along the north-south transect of Alaska. This is a good article. Points are connected from right to left, rather than being connected in the order they are entered. You cannot just use percentages. Ribosomal Database Project at Michigan State University. Probability plots are simple visual ways of summarizing reliability data by plotting CDF estimates versus time using a log-log scale. This is a scatterplot of the tip percentage by total bill size. Improve your math knowledge with free questions in "Interpret box-and-whisker plots" and thousands of other math skills. b) If r 2 = 0. Bar plots can be created in R using the barplot() function. I started off with the variable 'byWeek' which shows how many members joined the group each week:. Applied Statistics, 37, 477-484. If height is a matrix and beside=TRUE , then the values in each column are juxtaposed rather than stacked. The Mandalorian: Cast, trailer, plot, release date and more Star Wars details Here's everything we know about the live-action Star Wars series starring Pedro Pascal, as we await the Disney Plus. Northern Sierra Precipitation: 8-Station Index, August 19, 2019 Total Water Year Precipitation Oct 1 Nov 1 Dec 1 Jan 1 Feb 1 Mar 1 Apr 1 May 1 Jun 1 Jul 1 Aug 1 Sep 1 Oct 1. If my dataset changes in the future, I can re-run the code above to re-fit the linear model, extract the new R 2 and p -values, and have them plotted on the figure. Plus the basic distribution plots aren't exactly well-used as it is. The areas in bold indicate new text that was added to the previous example. Tutorial for new R users whom need an accessible and easy-to-understand resource on how to create their own histogram with basic R. Making the leap from chiefly graphical programmes, such as Excel and Sigmaplot. It will draw a rectangles, and its height represent the proportional value. The are just another way of expressing fractions, but they are always fractions of 100. site and plot ratio calculations? Hi all, Here trying to figure out a few calculations but I'm getting lost. Gain additional perspective by studying polar plots, parametric plots, contour plots, region plots and many other types of visualizations of the. A segment. A scatter plot (or scatter diagram) is a two-dimensional graphical representation of a set of data. Creating dashboards or visualizations at your company? Consider Plotly Enterprise for modern intracompany graph and data sharing. It looks like you are trying to label the %ages in each piece of the bar. This could for instance be the results from a math test taken by a group of students at the Mathplanet School. I'm having difficulty plotting a PCoA for UniFrac distances with elipses. The Hollywood Reporter is your source for breaking news about Hollywood and entertainment, including movies, TV, reviews and industry blogs. 52 and the r=-0. 386 (the 1949 Civil Code of the Philippines) speaks of the MINIMUM EASEMENT OF TWO METERS (2. Next click on Format Selection (located directly beneth the drop down). Probability plots are simple visual ways of summarizing reliability data by plotting CDF estimates versus time using a log-log scale. Creating dashboards or visualizations at your company? Consider Plotly Enterprise for modern intracompany graph and data sharing. Show R-Code. DeducerSpatial is a package for spatial data analysis which includes the ability to plot and explore open. The Control Chart Template above works for the most common types of control charts: the X-Bar chart (plotting the mean of a sample over time), the R chart (plotting the range or Max-Min of a sample over time), and the s chart (plotting the sample standard deviation over time). The IQR is where the center 50% of your data points will fall (as a 5 foot 8 inch American male this is where I would plot). I wish to find the percentage distribution for a data vector 'stop'. Display Percentage Values on a Pie Chart (Report Builder and SSRS) 03/01/2017; 2 minutes to read +1; In this article. I am as guilty as anyone of using these horrendous color schemes but I am actively trying to work at improving my habits. The Mosaic Plot in R Programming is very useful to visualize the data from contingency table, or two-way frequency table. In the data set faithful, a point in the cumulative frequency graph of the eruptions variable shows the total number of eruptions whose durations are less than or equal to a given level. Here are the relevant equations for computing the slope and intercept of the first-order best-fit equation, y = intercept + slope*x, as well as the predicted standard deviation of the slope and intercept, and the coefficient of determination, R 2, which is an indicator of the "goodness of. How to report the percentage of explained common variance in exploratory factor analysis Urbano Lorenzo-Seva 1 Contents 1. 0 m separates the eyes of neighbors. By default the arguments are evaluated with feval (@plot, x, y). P-P plots are vastly used to evaluate the skewness of a distribution. It presents the percentage of captured positive responses as a function of selected percentage of a sample. Small plots are usually faster to read. The scatter plot is produced: Click on the red down arrow next to Bivariate Fit of Gross Sales By Items and select Fit Line: You should see: Click the red down arrow next to Linear Fit and pull to Confid Shaded Fit: You should now see, on the scatter plot, the 95% confidence interval for the mean value of y for a given value of x for all values. The term "box plot" comes from the fact that the graph looks like a rectangle with lines extending from the top and bottom. # scatter plot of expense vs csat plot (sts. Connections to money are made. A cumulative frequency graph or ogive of a quantitative variable is a curve graphically showing the cumulative frequency distribution. R for data science is designed to give you a comprehensive introduction to the tidyverse, and these two chapters will get you up to speed with the essentials of ggplot2 as quickly as possible. The ability to interrupt R during a long computation. Stacked Percentage Bar Plot In MatPlotLib. Alternatively, if our model is too complex and. Here is a solution: [code]# create data data <- data. 7% of the total, the y-axis scaling has it at 18. This is a wrapper around cowplot::plot_grid and lets you combine multiple plots and add a combination of title, caption, and annotation texts with suitable defaults. Useful if the grouping variable is some experimental variable and data are to be aggregated for plotting. Simple scatterplot: Some customization and a line of best t:. Also see the dplyr library. The following portion of the tutorial provides a bit more of a step by step procedure for plotting text to faceted plots as well as a visual to go with the code. I am trying to create a script based on Price Headley's %R method. The SCALE=PERCENT plot-option plots percentages instead of frequency counts. When all points of a scatter plot fall directly on a line with an upward incline, r = +1; When all points fall directly on a downward incline, r = !1. Additionally, in 3-D charts that have a depth axis, you can reverse the plotting order of data series so that large 3-D data markers do not block smaller ones. The ggplot data should be in data. For example, in using R to manage grades for a course, 'total score' for homework may be calculated by summing scores over 5 homework assignments. Shiny applications inherit the default visual theme of the Bootstrap web framework upon which Shiny is based. Correlation, useful though it is, is one of the most misused statistics in all of science. As age increases so does percent body fat. minimum, first quartile, second quartile, third quartile, and maximum—of data. In Reporting Services paginated reports, by default the legend shows categories. Cumulative percent graphs are a way of showing a distribution. Primarily used to calculate the percent change from one period to another of a given series, or to calculate the percent difference between two series over the full series. Each example builds on the previous one. Highcharts - Interactive JavaScript charts for your web pages. You must understand your data to get the best results from machine learning algorithms. The arguments x1 and y1 define the arguments for the first plot and x1 and y2 for the second. Using R for statistical analyses - Graphs 1. In the case of two factors, the bars can be divided (stacked) or plotted in parallel (side-by-side). However, the bar is segmented into multiple parts, one for each value of the response variable. 66667 Female. Cumulative percent graphs are a way of showing a distribution. So, let’s start with a small introduction to. The areas in bold indicate new text that was added to the previous example. They are used to count data in the form of dots on a plots, which is where its name (Dot Plot) comes from. box-and-whisker plots. Bar charts and histograms are easily to understand. We still need to measure. Normal probability plots aren’t normally drawn by hand, because the normal scores used for the plot can’t be looked up in a table. There are a couple of reasons for preferring percentile plots to cumulative fractions plots. Here, we can see a clear correlation between greater ad spending and sales as the year progressed: Four Data Sets. Cumulative scatterplots have a variety of names: a rank scatterplot, a plot of rank on value, a quantile plot, or an empirical cumulative distribution function (ECDF). If you have an analysis to perform I hope that you will be able to find the commands you need here. R Base Graphics: An Idiot's Guide. • The strength of the linear relationship increases as r moves away from 0 toward -1 or 1. Plot two sets of data with independent y-axes and a common x-axis. In a stacked bar plot, we use one bar for each value of the explanatory variable (as in simple bar plots). Contribute to jbryer/likert development by creating an account on GitHub. The box plot (a. Another handy rule of thumb: for small values (R-squared less than 25%), the percent of standard deviation explained is roughly one-half of the percent of variance explained. • r < 0 indicates a negative association. Spherical contour plot created by two 3D parametric function plots: One is a 3D colormap surface plot and another one is a 3D surface without colormap and only shows the mesh line. Hi - I’m looking to show counts alongside percentages in a graph. Each example builds on the previous one. (c) Determine the linear correlation coefficient between FICO score and interest rate on a 36-month auto loan. One way is to plot the theoretical density of the t-statistic we should be seeing, and superimposing the density of our sample on top of it. Normal probability plots aren’t normally drawn by hand, because the normal scores used for the plot can’t be looked up in a table. Plotting just the UK over time Now that you have the percentage of time that each country voted "yes" within each year, you can plot the trend for a particular country. Customize Bars in a Bar Plot The simplest form of the bar plot includes grey bars with a black outline. For example, rating a diseased lawn subjectively on the area dead, such as "this plot is 10% dead, and this plot is 20% dead". But we need to do it as a percentage (effectively, a rate per 100 practice population, but we hardly ever represent GP referral rates as percentages). Also discussed are some common questions regarding complex plots with ggplot, for example, ordering factors in a plot and handling negative y-values. For example, instead of knowing a tree's height at age 10, we want to know how much it's grown between age 5 and age 10, so that can be a bar in our graph. Probability plots are simple visual ways of summarizing reliability data by plotting CDF estimates versus time using a log-log scale. You need to convert the data to factors to make sure that the plot command treats it in an appropriate way. We still need to measure. The bottom of the graph (the y-axis) is almost always percent, going from 0-100%. The peaks of a Density Plot help display where values are concentrated over the interval. We look at some of the ways R can display information graphically. A plot that is frequently used in popular media is the pie chart, where the size of a "wedge of pie" helps the reader visualize the percentage of data falling in a particular category. This is by no means an exhaustive catalog. How can I do that in Excel? I am not trying to forecast; I am simply showing a historical linear relationship and would like to show graphically, how often it has gone outside the standard deviation range. When R calculates the density, the density() function splits up your data in a number of small intervals and calculates the density for the midpoint of each interval. - gist:7742291. Stacked Percentage Bar Plot In MatPlotLib. Some Notes on Correlation. Its arguments are defaulted to display a tree with colors and details appropriate for the model’s response (whereas prpby default displays a minimal unadorned tree). 15 Questions All R Users Have About Plots There are different types of R plots, ranging from the basic graph types to complex types of graphs. Example [th, r] = rose ([2*randn(1e5,1), pi + 2*randn(1e5,1)]); polar (th, r);. The are just another way of expressing fractions, but they are always fractions of 100. You may also want percentages in the legend or the pie slices themselves. Let’s walk through the typical process of creating good labels for our YHOO stock price close plot (see part 4 ). In this article, waterfall plots were used to represent a variety of results. Coefficient of determination is the primary output of regression analysis. Cumulative percent graphs are a way of showing a distribution. This is the most sensitive and commonly used attribute control chart. I can do almost exactly what I want for correspondence analysis (CCA), as in example below, or princomp() or other methods to create an ordination object. The square root of the R-squared value is the correlation value. Note that the R code produces. If we supply a vector, the plot will have bars with their heights equal to the elements in the vector. The function rpart. Know how to interpret a correlation coefficient, r in terms of (coefficient of determination) percent of variance, r 2. These represent the x- and y-coordinates for plotting the density. Here is a solution: [code]# create data data <- data. Using t-tests in R. Scatter plots are similar to line graphs in that they start with mapping quantitative data points. Therefore, if you produce multiple plots by submitting multiple plot requests and using the OVERLAY option, the plot requests must be ordered in the PLOT statement so that the plot request that produces the lowest line values is the first (leftmost) plot request, the plot request that produces the next lowest line values is the second plot. [4] Figure 2 plots a histogram with 500 bins of the daily percentage changes of the S&P 500 index from 1950-2005 (the S&P 500 data). frame(ID = as. > screeplot( modelname ) where modelname is the name of a previously saved principle component analysis, created with the princomp function as explained in the article Performing a principle component analysis in R. This page will show you how to calculate and format a number as a percentage in R. • Values of r near 0 indicate a very weak linear relationship. The box plot is also referred to as box and whisker plot or box and whisker diagram. Create bar plots for one or two factors scaled by frequency or precentages. S&P Dow Jones Indices is the world's largest, global resource for index-based concepts, data and research. Learn vocabulary, terms, and more with flashcards, games, and other study tools. In his blog he describes, in its most simple form, how he gets stock data from the Yahoo Finance API and plots it on a chart. A dot plot is judged by position along the horizontal axis. Orientation of the plot (vertical or horizontal). The plot command will try to produce the appropriate plots based on the data type. It is a generic function, meaning, it has many methods which are called according to the type of object passed to plot(). Percent formatter: multiply by one hundred and display percent sign. The following is an introduction for producing simple graphs with the R Programming Language. The figure below shows a unity-feedback architecture, but the procedure is identical for any open-loop transfer function , even if some elements of the. How to plot cumulative distribution function in R? I know there is density and curve for density functions, but what about plotting distribution functions? The ecdf function provides one method when the distribution function is not known. You can set up Plotly to work in online or offline mode. , not in terms of purchasing power parity (PPP). PolicyViz ⊕ policyviz. Read and learn for free about the following article: Box plot review If you're seeing this message, it means we're having trouble loading external resources on our website. This page is intended to be a help in getting to grips with the powerful statistical program called R. Anyone who has performed ordinary least squares (OLS) regression analysis knows that you need to check the residual plots in order to validate your model. Click to share this graph on your favourite social network: Add. There is a very close relationship between R and the Shapiro-Wilk [16] test W and the Shapiro-Francia [15] approximation W. The box plot is also referred to as box and whisker plot or box and whisker diagram. You will only find them at teleSUR. This post is the first in a two-part series on stock data analysis using R, based on a lecture I gave on the subject for MATH 3900 (Data Science) at the University of Utah. Now we want to plot our model, along with the observed data. Maps in R – Examples (Part 1). box and whisker diagram) is a standardized way of displaying the distribution of data based on the five number summary: minimum, first quartile, median, third quartile, and maximum. Dear R-users, Though it's a silly thing to ask, but I'm not getting a way out. percentage sign in expression. Project jpeg doesn't have any custom web pages. Multiplottr allows you to plot multiple locations on a map, save and share on Google Maps. Box-whisker plots. Here is an example of a plot of a sine wave. What proportion of the variation in y can be explained by the variation in the values of x? r² = ?. These bars can be customized via arguments per the sections below. One way is to plot the theoretical density of the t-statistic we should be seeing, and superimposing the density of our sample on top of it. js for making client-side visualizations with html, css, and javascript. 47, then 47% of the variation is determined by the regression line, and 53% of the variation is determined by some other factor or factors. To calculate sample size: 1. In the first part of A pick of the best R packages for interactive plots and visualizations, we saw the best packages to do interactive plot in R.