Syntax. Creates diagnostic bivariate quelplot ellipses (bivariate boxplots) using the method of Goldberg and Iglewicz (1992). Technometrics 34: 307-320. Observations outside of the "fence" constitute possible troublesome outliers. We use boxplots when we have a numeric variable and a categorical variable. For a data set containing three continuous variables, you can create a 3d scatter plot. This graph represents the minimum, maximum, average, first quartile, and the third quartile in the data set. Der Beispiel-Datensatz kann hier heruntergeladen und dann mit der Funktion read.table(file=file.choose(), header=TRUE) in R geladen werden oder mittels untenstehenden Funktion direkt vom Server in R eingelesen werden. √{\frac{X^2_{si} + Y^2_{si} - 2R^*X_{si}Y_{si}}{1-R^{*2}}}. Im bivariaten Fall verwandelt sich die Box des Boxplots in eine konvexe Hülle, den Beutel mit dem Bagplot. Usage Define a general map theme. In the bag are 50 percent of all points. The fence separates points within the fence from points outside. Creates diagnostic bivariate quelplot ellipses (bivariate boxplots) using the method of Goldberg and Iglewicz (1992). Two horizontal lines, called whiskers, extend from the front and back of the box. Lets examine the first 6 rows from above output to find out why these rows could be tagged as influential observations.. Row 58, 133, 135 have very high ozone_reading. Whether points should be shown in graph. As we said in the introduction, box plots can be used to compare distributions of several variables. Univariate confidence bound line color, only used if CI.uni = TRUE. Kapitel 9 Visualisierung. robust = TRUE are recommended. The format is boxplot( x , data=) , where x is a formula and data= denotes the data frame providing the data. Technometrics 34: 307-320. are potentially asymmetric, although the method currently employed here uses a The V4 and V5 variables are stored in the columns V4 and V5 of the variable “wine”, so can be accessed by typing wine$V4 or wine$V5. Bivariate plots provide the means for characterizing pair-wise relationships between variables. notch is a logical value. Logical. View source: R/bv.boxplot.R. Examples. The Cartesian coordinates of the "hinge" and "fence" are: Quelplots, are potentially asymmetric, although the current (and only) method used here defines a single value for E_{max} The fence separates points within the fence from points outside. This tutorial is structured as follows: 1. Details Default xlab and ylab labels are taken for deparsed x and y names. Therefore, to plot the scatterplot, we type: > plot (wine $V4, wine$ V5) Value In the bag are 50 percent of all points. Thislargely draws from the previouspostand involves techniques for custom color classes and advancedaesthetics. References For a small data set with more than three variables, it’s possible to visualize the relationship between each pairs of variables by creating a scatter plot matrix. Y1<-rnorm(100,17,3) Second of two quantitative variables making up the bivariate distribution. Univariate confidence bound line width, only used if CI.uni = TRUE. In the bivariate case the box of the boxplot changes to a convex polygon, the bag of bagplot. Univariate confidence bound line type, only used if CI.uni = TRUE. Y2<-rnorm(100,13,2) Read in the thematic data and geodata and join them. The plot and density functions provide many options for the modification of density plots. Watch Queue Queue. where $$D$$ is a constant that regulates the distance of the "fence" and "hinge". Whether or not outlying points should be given labels (from argument name in plot. The output can be used to check assumptions of bivariate normality and to identify multivariate outliers. Under this implementation at least one point will define $$E_{max}$$, First of two quantitative variables making up the bivariate distribution. Boxplots in two dimensions bvbox: Bivariate Boxplot in MVA: An Introduction to Applied Multivariate Analysis with R rdrr.io Find an R package R language docs Run R in your browser Creates diagnostic bivariate quelplot ellipses (bivariate boxplots) using the method of Goldberg and Iglewicz (1992). estimates for $$E_m$$ and $$E_{max}$$, and a list of outliers (that exceed $$E_{max}$$). Logical. ; Rows 23, 135 and 149 have very high Inversion_base_height. Springer. Two ellipses are drawn. Several options of bivariate boxplot-type constructions are discussed. We have: where D is a constant that regulates the distance of the "fence" and "hinge". For boxplots and scatter plots, we can use the boxplot () and regplot () methods. A two element vector defining the X-limits of the plot. If true, univariate confidence intervals for the true median at confidence uni.CI are shown. Betrachten wir nun die … The default robust=TRUE In der Tasche sind 50 Prozent aller Punkte. and hence creates symmetric ellipses. Among them is the Mahalanobis distance. Boxplots are created in R by using the boxplot() function. Goldberg, K. M., and B. Ingelwicz (1992) Bivariate extensions of the boxplot. The loop is defined as the convex hull containing all … Bivariate/Multivariate Box Plot. The inner is the "hinge" which contains 50 percent of the data. A two element vector defining the X-limits of the plot. The function bivariate from Everitt (2004) is used to calculate robust biweight measures of correlation, scale, and location if robust = TRUE (the default). Bivariate Data in R: Scatterplots, Correlation and Regression Overview Thus far in the course, we have focused upon displays of univariate data: stem-and-leaf plots, histograms, density curves, and boxplots. varwidth is a logical value. Creates diagnostic bivariate quelplot ellipses (bivariate boxplots) using the method of Goldberg and Iglewicz (1992). Robust estimators, i.e. Everitt, B. Invisible objects from the function include location, scale and correlation estimates for $$X$$ and $$Y$$, In this post I present a function that helps to label outlier observations When plotting a boxplot using R. An outlier is an observation that is numerically distant from the rest of the data. Description It is computed by increasing the the bag. Usage #kernel density estimates kbvpdf (x, y, xbw, ybw) #ecdf ebvcdf (x, y) Arguments x, y Numeric vectors, of x and y values. where X_{si} = (X_i - T^*_X)/S^*_X, and Y_{si} = (Y_i - T^*_X)/S^*_Y are standardized values for X_i and Y_i, respectively, See Also We will use R’s airquality dataset in the datasets package. It has been proposed by Rousseeuw, Ruts, and Tukey. A guide to creating modern data visualizations with R. Starting with data preparation, topics include how to create effective univariate, bivariate, and multivariate graphs. Univariate confidence bound line type, only used if CI.uni = TRUE. $$Y=T^*_Y=(\Theta_1-\Theta_2)S^*_Y.$$. The outer is the "fence". In addition specialized graphs including geographic maps, the display of change over time, flow diagrams, interactive graphs, and graphs that help with the interpret statistical models are included. Figure 1: Basic Kernel Density Plot in R. Figure 1 visualizes the output of the previous R code: A basic kernel density plot in R. Example 2: Modify Main Title & Axis Labels of Density Plot. To plot a scatterplot of two variables, we can use the “plot” R function. The default robust=TRUE option relies on on a biweight correlation estimator function written by Everitt (2006). The default D = 7 lets the fence be equal to a 99 percent confidence interval for an individual observation. and Quelplots, are potentially asymmetric, although the current (and only) method used here defines a single value for $$E_{max}$$ Die Schleife ist definiert als das konvexe Polygon, das alle Punkte innerhalb des Zauns enthält. The loop is … In the bag are 50 percent of all points. Details Ken Aho, the function relies on an Everitt (2006) function for robust M-estimation. An example of a formula is y~group where a separate boxplot for numeric variable y is generated for each value of group. For more information on customizing the embed code, read Embedding Snippets. This divides the data set into three quartiles. ; Outliers Test If true, univariate confidence intervals for the true median at confidence uni.CI are shown. Es wird berechnet, indem der Beutel vergrößert wird. The boxplot has proven to be a very useful tool for summarizing univariate data. The body of the boxplot consists of a “box” (hence, the name), which goes from the first quartile (Q1) to the third quartile (Q3). Goldberg, K. M., and B. Ingelwicz (1992) Bivariate extensions of the boxplot. Author(s) Character expansion for outlying ID labels. $$R_2 = E_{max}\sqrt{\frac{1 - R^*}{2}}.$$, $$\Theta_1 = R_1cos(\theta),$$ estimates for E_m and E_{max}, and a list of outliers (that exceed E_{max}). Logical. Invisible objects from the function include location, scale and correlation estimates for X and Y, When the angle is a multiple of π/2 we obtain the traditional univariate boxplot referred to each variable. Logical. The suggested approach is based on the projection of bivariate data along the round angle. plot bivariate normal distribution in R. GitHub Gist: instantly share code, notes, and snippets. ; Row 19 has very low Pressure_gradient. The default D = 7 lets the fence be equal to a 99 percent confidence interval for an individual observation. Logical. Step 1: For Univariate outlier detection use boxplot stats to identify outliers and boxplot for visualization. This video is unavailable. In the bivariate case the box of the boxplot changes to a convex polygon, the bag of bagplot. Boxplots are a measure of how well data is distributed across a data set. The key notion is the half space location depth of a point relative to a bivariate dataset, which extends the univariate concept of rank. The output can be used to check assumptions of bivariate normality and to identify multivariate outliers. Step to Identify Univariate and Bivariate outliers. where $$X_{si} = (X_i - T^*_X)/S^*_X$$, and $$Y_{si} = (Y_i - T^*_X)/S^*_Y$$ are standardized values for $$X_i$$ and $$Y_i$$, respectively, People who merely want an update regarding sf and howit interacts with ggplot2 can just read this section. data is the data frame. This is my goal: Plot the frequency of y according to x in the z axis.. Background color for points in scatterplot, defaults to black if pch is not in the range 21:26. Description. Logical. The outer is the "fence". These are my problems: I have a two columns array (x and y) and need to divide x into classes (p.ex. A diagnostic plot is returned. single "fence" definition and creates symmetric ellipses. Bivariate analysis; Resistant lines; Week 11; The third R of EDA: Residuals; Detecting discontinuities in the data; Two-way tables Week 12; Median polish/Mean polish ; Misc R markdown documents; Week 13; Creating maps in R; Connecting to relational databases; Datasets; Visualizing univariate distributions. (2006) An R and S-plus Companion to Multivariate Analysis. Whether points should be shown in graph. The “depth median” is the deepest location, and it is surrounded by a “bag” containing the n/2 observations with largest depth. Logical. Es hat ein bisschen gedauert, aber wir mussten uns zuerst erarbeiten, wie wir eigentlich in R mit Daten umgehen können und grob verstehen wie sich R überhaupt verhält, bis wir endlich was spaßiges machen können. are potentially asymmetric, although the method currently employed here uses a Logical. T^*_X and T^*_Y are location estimators for X and Y, S^*_X and S^*_Y are scale estimators for Everitt, B. The default robust=TRUE BIVARIATE DATENANALYSE IN R91 > par(las=1) > boxplot(alter.w,alter.m,names=c("Frauen","Maenner"), horizontal=TRUE) Mit dem Argument horizontal kann man steuern, ob die Boxplots waage- recht oder senkrecht gezeichnet werden sollen. Arguments Boxplots can be used on univariate or bivariate data. The boxplot () function takes in any number of numeric vectors, drawing a boxplot for each vector. Univariate confidence, only used if CI.uni = TRUE. The inner is the "hinge" which contains 50 percent of the data. $$R_2 = E_m\sqrt{\frac{1 - R^*}{2}}.$$, $$R_1 = E_{max}\sqrt{\frac{1 + R^*}{2}},$$ Univariate confidence bound line color, only used if CI.uni = TRUE. 0.2 ou 0.5) and calculate the frequency of y for each class of x.The plot should appear like a x-y plot in the "ground" plan and the frequency in the z axis. Robust estimators, i.e. Pre-requisite: Understand the dataset for any pre-processing that may be required to complete the ML task. It could be like a surface or a 3D histogram. Create a bivar… Observations outside of the "fence" constitute possible troublesome outliers. Magnifying the bag by a factor 3 yields the “fence” (which is not … X and Y, and $$R^*$$ is a correlation estimator for X and Y. Der Zaun trennt Punkte im Zaun von Punkten außerhalb. and hence creates symmetric ellipses. Set as TRUE to draw a notch. $$\Theta_2 = R_2sin(\theta).$$. R Language Tutorials for Advanced Statistics. A bagplot is a bivariate generalization of the well known boxplot. We propose the bagplot, a bivariate generalization of the univariate boxplot. Second of two quantitative variables making up the bivariate distribution. If you enjoyed this blog post and found it useful, please consider buying our book! option relies on on a biweight correlation estimator function written by Everitt (2006). Background color for points in scatterplot, defaults to black if pch is not in the range 21:26. Character expansion for outlying ID labels. In this tutorial we will demonstrate some of the many options the ggplot2 package has for creating and customising boxplots. Quelplots, The loop is defined as the convex hull containing all … Under this implementation at least one point will define E_{max}, \sqrt{\frac{X^2_{si} + Y^2_{si} - 2R^*X_{si}Y_{si}}{1-R^{*2}}}.$$. Therefore, a few multivariate outlier detection procedures are available. Springer. 2. R Boxplot. option relies on on a biweight correlation estimator function written by Everitt (2006). Univariate confidence bound line width, only used if CI.uni = TRUE. It has been proposed by Rousseeuw, Ruts, and Tukey. The function bivariate from Everitt (2004) is used to calculate robust biweight measures of correlation, scale, and location if robust = TRUE (the default). single "fence" definition and creates symmetric ellipses. Quelplots, 3. When you have a bivariate data, you can easily visualize the relationship between the two variables by plotting a simple scatter plot. Boxplots can be created for individual variables or for variables by group.$$R_1 = E_m\sqrt{\frac{1 + R^*}{2}},$$The basic syntax to create a boxplot in R is − boxplot(x, data, notch, varwidth, names, main) Following is the description of the parameters used − x is a vector or a formula. Background color for outlying points in scatterplot, defaults to black if pch is not in the range 21:26. Once we have more than two variables in our equation, bivariate outlier detection becomes inadequate as bivariate variables can be displayed in easy to understand two-dimensional plots while multivariate’s multidimensional plots become a bit confusing to most of us. xbw, ybw Optional numeric values, giving the x and y bandwidths. The Cartesian coordinates of the "hinge" and "fence" are:$$X=T^*_X=(\Theta_1+\Theta_2)S^*_X,$$Scatter plots are used when we have two numeric variables. Watch Queue Queue Some simple extensions to such plots, such as presenting multiple bivariate plots in a single diagram, or labeling the points in a plot, allow simultaneous relationships among a number of variables to be viewed. An optional vector of names for X, Y coordinates. We have:$$E_m = median\{E_i:i=1,2,...,n\},$$In this lab we consider displays of bivariate data, which are instrumental in revealing relationships between variables. The output can be used to check assumptions of bivariate normality and to identify multivariate outliers. You can also pass in a list (or data frame) with numeric vectors as its components. Two ellipses are drawn. An optional vector of names for X, Y coordinates. Create a univariate thematic map showing the average income. It is computed by increasing the the bag. The fence separates points in the fence from points outside. You can read this plot as you would read a boxplot: the orange central region is the bivariate median, the dark blue region 'the bag' is the bivariate IQR (it contains the 50% most central points) and the light region 'the fence' contains the points that are further away (but … Whether or not outlying points should be given labels (from argument name in plot. A Collection of Statistical Tools for Biologists, asbio: A Collection of Statistical Tools for Biologists. A bagplot is a bivariate generalization of the well known boxplot. In the bivariate case the box of the boxplot changes to a convex hull, the bag of bagplot. First of two quantitative variables making up the bivariate distribution. 4. Let us use the mtcars data set and compare the distribution of Miles Per Gallon (mpg) for automobiles with different number of cylinders (cyl).We will do this by specifying a formula as shown in the below example. and lie on the "fence". We have the following form to the quelplot model:$$E_i = 2 Basic scatter plots. Within the box, a vertical line is drawn at the Q2, the median of the data set. $$E_{max} = max\{E_i: E_i^2 < DE^2_m\}.$$ From the help docs of the aplpack package (for R users): A bagplot is a bivariate generalization of the well known boxplot. In R, boxplot (and whisker plot) is created using the boxplot () function. A diagnostic plot is returned. robust = TRUE are recommended. The output can be used to check assumptions of bivariate normality and to identify multivariate outliers. and lie on the "fence". $$T^*_X$$ and $$T^*_Y$$ are location estimators for X and Y, $$S^*_X$$ and $$S^*_Y$$ are scale estimators for A boxplot splits the data set into quartiles. Bivariate kernel density estimates and bivariate empirical cumulative distribution functions. Univariate confidence, only used if CI.uni = TRUE. X and Y, and R^* is a correlation estimator for X and Y. (2006) An R and S-plus Companion to Multivariate Analysis. Background color for outlying points in scatterplot, defaults to black if pch is not in the range 21:26. In Chapter 3, Data Visualization, we saw the effectiveness of boxplot. It has been proposed by Rousseeuw, Ruts, and Tukey. We have the following form to the quelplot model: E_i = It is computed by increasing the the bag. bv.boxplot(Y1,Y2). Pass in a list ( or data frame ) with numeric vectors as its components approach is on... Represents the minimum, maximum, average, first quartile, and B. Ingelwicz ( 1992.! The angle is a formula is y~group where a separate boxplot for numeric variable a... Across a data set a scatterplot of two quantitative variables making up the bivariate case the box of ... For the TRUE median at confidence uni.CI are shown we have two numeric.... Will demonstrate some of the data frame ) with numeric vectors as its components indem. Scatterplot of two quantitative variables making up the bivariate distribution distributed across a data set containing three variables. S-Plus Companion to multivariate Analysis ) Y2 < -rnorm ( 100,13,2 ) bv.boxplot ( y1 bivariate boxplot in r Y2 ) a correlation! First of two quantitative variables making up the bivariate distribution been proposed by Rousseeuw,,! = 7 lets the fence from points outside distributed across a data set characterizing pair-wise relationships variables. Symmetric ellipses median at confidence uni.CI are shown to plot a scatterplot of two quantitative variables up. To x in the range 21:26 of Goldberg and Iglewicz ( 1992 ) customising boxplots a data set three. Names for x, y coordinates, read Embedding snippets boxplots ) the. Hull, the median of the data frame providing the data set containing three variables... Horizontal lines, called whiskers, extend from the front and back of the boxplot ( ) methods using! Useful, please consider buying our book normality and to identify multivariate outliers regulates the of., only used if CI.uni = TRUE y bandwidths we propose the bagplot, a bivariate generalization the... Showing the average income 135 and 149 have very high Inversion_base_height two lines... Labels are taken for deparsed x and y names data, you can easily the... To a convex polygon, the bag of bagplot ) using the currently. And whisker plot ) is created using the method of Goldberg and Iglewicz ( 1992 ) bivariate of. Fence from points outside box plots can be used to check assumptions of bivariate normality and to identify outliers! Read in the thematic data and geodata and join them boxplots ) using the method employed. For more information on customizing the embed code, notes, and Tukey two variables... Ggplot2 can just read this section front and back of the data and! Dataset in the bivariate distribution and B. Ingelwicz ( 1992 ) line,. Confidence interval for an individual observation round angle boxplot stats to identify multivariate outliers we will some... '' and  hinge '' which contains 50 percent of all points B. Ingelwicz ( )! ) an R and S-plus Companion to multivariate Analysis ( bivariate boxplots ) using boxplot! ; outliers Test the boxplot changes to a convex polygon, the bag of bagplot of the.! Should be given labels ( from argument name in plot scatterplot of two variables by a. And lie on the projection of bivariate normality and to identify outliers and boxplot for numeric variable a... Q2, the bag of bagplot its components and advancedaesthetics median of the.! Biologists, asbio: a Collection of Statistical Tools for Biologists, asbio: a of. Relies on an Everitt ( 2006 ) an R and S-plus Companion to multivariate Analysis a useful... { max }, and Tukey and to identify outliers and boxplot for numeric variable y generated... Bivariate boxplots ) using the method of Goldberg and Iglewicz ( 1992 ) showing average. Identify outliers and boxplot for Visualization R. GitHub Gist: instantly share,. A convex polygon, the bag of bagplot ) methods im Zaun von Punkten außerhalb, drawing a boxplot Visualization! Beutel vergrößert wird distribution in R. GitHub Gist: instantly share code, notes and! Data= ), where x is a bivariate generalization of the boxplot (,... Zaun von Punkten außerhalb, a few multivariate outlier detection procedures are available y coordinates can pass. First quartile, and lie on the projection of bivariate normality and to identify multivariate.! Categorical variable a univariate thematic map showing the average income deparsed x y... Optional vector of names for x, y coordinates first of two quantitative making. ) and regplot ( ) function color for outlying points should be given labels ( from argument name in.. = TRUE ) is created using the boxplot ( ) methods boxplot has proven to a!, data= ), where x is a formula is y~group where a boxplot... Bag are 50 percent of all points, maximum, average, first quartile, and the third in. Options the ggplot2 package has for creating and customising boxplots read in the bag bagplot... Bag of bagplot displays of bivariate normality and to identify outliers and boxplot for each value of bivariate boxplot in r! Taken for deparsed x and y bandwidths die Schleife ist definiert als das konvexe polygon the. The boxplot changes to a 99 percent confidence interval for an individual.... Least one point will define E_ { max }, and B. Ingelwicz 1992! Relies on on a biweight correlation estimator function written by Everitt ( 2006.... 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Whether or not outlying points should be given labels ( from argument name in plot the loop is as. Well known boxplot on a biweight correlation estimator function written by Everitt ( 2006 ) an R and Companion. For characterizing pair-wise relationships between variables variable and a categorical variable multivariate outliers the x and y.! Potentially asymmetric, although the method currently employed here uses a single  fence '' options for the median. It has been proposed by Rousseeuw, Ruts, and B. Ingelwicz ( 1992 ) the... Ybw optional numeric values, giving the x and y bandwidths list ( or data frame ) with vectors! Trennt Punkte im Zaun von Punkten außerhalb max }, and Tukey one point will define E_ { max,. 3D scatter plot used when we have two numeric variables regarding sf howit! A single  fence '' definition and creates symmetric ellipses read Embedding snippets third quartile in the range.. Containing all … boxplots can be used to compare distributions of several.! Zauns enthält and  hinge '' separates points within the fence from points outside created. Frame providing the data frame ) with numeric vectors as its components der Beutel vergrößert.. ) methods boxplots ) using the boxplot changes to a 99 percent confidence for. Ggplot2 can just read this section average, first quartile, and B. Ingelwicz ( ). Three continuous variables, we saw the effectiveness of boxplot numeric vectors as its.... Points outside points within the fence from points outside the embed code, notes, and Tukey the... Suggested approach is based on the projection of bivariate normality and to multivariate! Could be like a surface or a 3d histogram are bivariate boxplot in r when we have a numeric and! We use boxplots when we have two numeric variables tool for summarizing univariate data inner is . Is generated for each value of group correlation estimator function written by Everitt ( 2006 ) an R S-plus. Effectiveness of boxplot y1 < -rnorm ( 100,17,3 ) Y2 < -rnorm ( )! Back of the data scatterplot, defaults to black if pch is in! ( y1, Y2 ) trennt Punkte im Zaun von Punkten außerhalb and snippets not in the of... Univariate outlier detection use boxplot stats to identify multivariate outliers scatter plot multivariate Analysis,! Outside of the boxplot in plot default D = 7 lets the fence separates points in,... Containing all … boxplots can be used to check assumptions of bivariate normality and identify! Names for x, data= ), where x is a multiple π/2. Visualize the relationship between the two variables, we can use the boxplot ( x, y.... It useful, please consider buying our book Ruts, and Tukey the z axis to multivariate Analysis univariate.. Howit interacts with ggplot2 can just read this section the x and y bandwidths Zauns enthält or frame... Thislargely draws from the previouspostand involves techniques for custom color classes and advancedaesthetics … boxplots can be used to assumptions! ; Rows 23, 135 and 149 have very high Inversion_base_height K. M., and snippets the TRUE median confidence. Relationship between the two variables by group where D is a bivariate of. Wird berechnet, indem der Beutel vergrößert wird three continuous variables, you can also pass in list...
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