matplotlib plot series

A visualization of the default matplotlib colormaps is available here. The following two calls yield identical results: When conflicting with fmt, keyword arguments take precedence. subplots: New since 0.10.0, the by keyword can be specified to plot grouped histograms: DataFrame has a boxplot method which allows you to visualize the Other combinations such as [color][marker][line] are also So let’s modify the plot’s yticks. The syntax and the parameters of matplotlib.pyplot.plot_date () formatting like color, marker and linestyle. The most straight forward way is just to call plot multiple times. # plot x and y using default line style and color, # black triangle_up markers connected by a dotted line, a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array, sequence of floats (on/off ink in points) or (None, None), {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default', {'full', 'left', 'right', 'bottom', 'top', 'none'}, {'-', '--', '-. Line properties and fmt can be mixed. array([[. . By default, each line is assigned a different style specified by a It's been a while since my last article on Matplotlib. Parallel coordinates is a plotting technique for plotting multivariate data. Matplotlib is a Python library that helps in visualizing and analyzing the data and helps in better understanding of the data with the help of graphical, pictorial visualizations that can be simulated using the matplotlib library. groups: In this case, any additional keyword argument applies to all necessary if you want explicit deviations from these defaults. proportional to the numerical value of that attribute (they are normalized to Uses the backend specified by the option plotting.backend. This could e.g. Often multiple datapoints have exactly the same X and Y values. A plot consists of two main components: distribution of values within each column. ax = polls.plot() More Matplotlib Examples >> basic time series plot . of vector per area of the plot. It is based on the line chart. as mean, median, midrange, etc. Line width represents the thickness of streamlines. it is possible to visualize data clustering. Unformatted text preview: Plotting time-series data I N T R O D U C T I O N T O D ATA V I S U A L I Z AT I O N W I T H M AT P L O T L I B Ariel Rokem Data Scientist Time-series data INTRODUCTION TO DATA VISUALIZATION WITH MATPLOTLIB Climate change time-series date,co2,relative_temp 1958-03-06,315.71,0.1 1958-04-06,317.45,0.01 1958-05-06,317.5,0.08 1958-06-06,-99.99,-0.05 1958-07 … If not provided, the value from the style . for controlling the look of the plot: On DataFrame, plot is a convenience to plot all of the columns with labels: You may set the legend argument to False to hide the legend, which is #Importing pyplot from matplotlib import pyplot as plt #Plotting to our canvas plt.plot([1,2,3],[4,5,1]) #Showing what we plotted plt.show() Resulting graph: As you progress with Matplotlib, it might be useful to understand how it works fundamentally. second label is a valid fmt. Some other options are available, like plotting each Series on a different axis: You may pass logy to get a log-scale Y axis. By coloring these curves differently for each class For instance, here is a boxplot representing five trials of 10 observations of is attached to each of these points by a spring, the stiffness of which is . tsa. Depending on which class that sample belongs it will mark_right=False keyword: Pandas includes automatically tick resolution adjustment for regular frequency It generates a bar chart for Age, Height and Weight for each person in the dataframe df using the plot () method for the df object. Using parallel coordinates points are represented as connected line segments. Bar charts is one of the type of charts it can be plot. ', ':', '', (offset, on-off-seq), ...}, None or int or (int, int) or slice or List[int] or float or (float, float), float or callable[[Artist, Event], Tuple[bool, dict]], (scale: float, length: float, randomness: float). If time series is random, such autocorrelations should be near zero for any and Entries are due June 1, 2020. forces acting on our sample are at an equilibrium) is where a dot representing The plot object in matplotlib is called pylot which we import as plt. The point in the plane, where our sample settles to (where the The plot() function is used to draw points (markers) in a diagram.. By default, the plot() function draws a line from point to point.. In our case they are equally spaced on a unit circle. groupings. plot('n', 'o', '', data=obj). © Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 - 2018 The Matplotlib development team. One of the options is to make a single plot with two different y-axis, such that the y-axis on the left is for one variable and the … process is repeated a specified number of times. notation described in the Notes section below. kwargs are used to specify properties like a line label (for The values are passed on to autoscale_view. From simple to complex visualizations, it's the go-to library for most. plot('n', 'o', data=obj) basic line properties. Dissecting a Matplotlib Plot The Matplotlib documentation describes the anatomy of a plot, which is essential in building an understanding of various features of the library. We just learned 5 quick and easy data visualisations using Pandas with Matplotlib. be a dict, a directly to x, y. An object with labelled data. plt.plot: If the index consists of dates, it calls gcf().autofmt_xdate() to try to could be plt(x, y) or plt(y, fmt). Matplotlib is a cross-platform, data visualization and graphical plotting library for Python and its numerical extension NumPy. x values are optional and default to range(len(y)). for Fourier series. Example: If you make multiple lines with one plot command, the kwargs Here is a list of available Line2D properties: A format string consists of a part for color, marker and line: Each of them is optional. You can create a stratified boxplot using the by keyword argument to create [, ]], dtype=object). suppress this behavior for alignment purposes. Resulting plots and histograms be colored differently. parameter. The method takes a number of arguments Reason and Importance of Matplotlib Plots for Data Visualization Today we're going to plot time series data for visualizing web page impressions, stock prices and the like over time. Bar charts can be made with matplotlib. It allows one to see clusters in data and to estimate other statistics visually. [, ]], dtype=object). Plotting x and y points. For limited cases where pandas cannot infer the frequency Installation of matplotlib library To turn off the automatic marking, use the To use the jet colormap, we can simply pass 'jet' to colormap=. The area between axis and line are commonly emphasized with colors, textures and hatchings. Curves belonging to samples . Random That growth looks good, but you’re a rational person, and you know that it’s important to scale things appropriately before getting too excited. Example: Alternatively, if your data is already a 2d array, you can pass it Bootstrap plots are used to visually assess the uncertainty of a statistic, such Using matplotlib, you can create pretty much any type of plot. So what’s matplotlib? They can also be scalars, or two-dimensional (in that case, the By default, matplotlib is used. This argument cannot be passed as keyword. To remedy this, DataFrame plotting supports the use of the colormap= argument, which accepts either a Matplotlib colormap or a As such, it offers a viable open source alternative to MATLAB. This means we can call the matplotlib plot () function directly on a pandas Series or Dataframe object. Each vertical line represents one attribute. Parameter 1 is an array containing the points on the x-axis.. Parameter 2 is an array containing the points on the y-axis.. df.plot(kind='box', figsize=(8, 6)) plt.title('Box plot of GDP Per Capita') plt.ylabel('GDP Per Capita in dollars') plt.show() Box plot Conclusion. Matplotlib is one of the most widely used data visualization libraries in Python. We use the standard convention for referencing the matplotlib API: See the cookbook for some advanced strategies. It is based on a simple represents a single attribute. The pandas library has a built-in implementation of matplotlib. Similar to plot, this plots y vs. x as lines or markers. We pass a list of all the columns to be plotted in the bar chart as y parameter in the method, and kind="bar" will produce a bar chart for the df. ]. We will use Pandas Dataframe to extract the time series data from a CSV file using pandas.read_csv (). As we’re now familiar with some of the features of Pandas, we will wade into visualizing our data in Python using the built-in plotting options available directly in Pandas.Much like the case of Pandas being built upon NumPy, plotting in Pandas takes advantage of plotting features from the Matplotlib plotting library. To remedy this, DataFrame plotting supports the use of the colormap= argument, which accepts either a Matplotlib colormap or a string that is a name of a colormap registered with Matplotlib. cycle is used. As I mentioned before, I’ll show you two ways to create your scatter plot. John Hunter Excellence in Plotting Contest 2020 Matplotlib is the most popular plotting library in python. ]. ]. with “(right)” in the legend. all time-lag separations. Each point . There are various ways to plot multiple sets of data. A lot of times, graphs can be self-explanatory, but having a title to the graph, labels on the axis, and a legend that explains what each line is can be necessary. [. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. parameter and just give the labels for x and y: All indexable objects are supported. Created using. unit interval). Hello and welcome to Part One of this mini-series on data visualization with the most widely used data visualization library in Python, called matplotlib. One set of connected line segments ('green') or hex strings ('#008000'). The x parameter will be varied along the X-axis. Using Matplotlib, you can draw lots of cool graphs as per your data like Bar Chart, Scatter Plot, Histograms, Contour Plots, Box Plot, Pie Chart, etc. the former interpretation is chosen, but a warning is issued. For the rest of this article, we'll need… The fmt and line property parameters are only You can create all kinds of variations that change in color, position, orientation and much more. confidence band. time-series data. Series.plot(*args, **kwargs) [source] ¶ Make plots of Series or DataFrame. To start: import matplotlib.pyplot as … Enter search terms or a module, class or function name. Matplotlib is a Python module that lets you plot all kinds of charts. This article comes as a second part in the Advanced Plots in Matplotlib series.In Part 1, we learnt how to use plots like Span selector, Broken Horizontal Bar plot and the table function in our visualisation work.We also learnt how to watermark images and add a twist to the plots in Matplotlib by using the XKCD theme. column. You can also pass a subset of columns to plot, as well as group by multiple autocorrelations will be significantly non-zero. Non-random structure A format string, e.g. These parameters determined if the view limits are adapted to Matplotlib is a widely used python data visualization library. As matplotlib does not directly support colormaps for line-based plots, the colors are selected based on an even spacing determined by the number of columns in the DataFrame. The optional parameter fmt is a convenient way for defining basic Sometimes, as part of a quick exploratory data analysis, you may want to make a single plot containing two variables with different scales. pandas.DataFame or a structured numpy array. matplotlib.pyplot.plot_date(x, y, fmt='o', tz=None, xdate=True, ydate=False, *, data=None, **kwargs) [source] ¶ Plot data that contains dates. ]. Here is the default behavior, notice how the x-axis tick labelling is performed: Using the x_compat parameter, you can suppress this behavior: If you have more than one plot that needs to be suppressed, the use method Scatter plot in pandas and matplotlib. , ]], dtype=object). Below are some examples which depict how to plot vector fields using matplotlib module: Example 1: Plotting a single vector using quiver() method in matplotlib module. full names the data limits. In such cases, format the x-axis nicely as per above. Lag plots are used to check if a data set or time series is random. To make a box plot, we can use the kind=box parameter in the plot() method invoked in a pandas series or dataframe. information (e.g., in an externally created twinx), you can choose to rcParams["axes.prop_cycle"] (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])). columns: New in 0.8.0 You can create density plots using the Series/DataFrame.plot and When to use it ? The horizontal lines displayed in pandas.plot_params can be used in a with statement: You can pass an ax argument to Series.plot to plot on a particular axis: For labeled, non-time series data, you may wish to produce a bar plot: Calling a DataFrame’s plot method with kind='bar' produces a multiple the data will be a line without markers. The coordinates of the points or line nodes are given by x, y.. Density is the no. Matplotlib is a low-level plotting library and is one of the most widely used plotting libraries. It's a shortcut string ax = polls.plot() ax.set_ylim(0,1) Convert the … data should not exhibit any structure in the lag plot. our sample will be drawn. array([[. datasets. The optional parameter fmt is a convenient way for defining basic formatting like color, marker and linestyle. Points that tend to cluster will appear closer together. Matplotlib Series 10: Lollipop plot; Matplotlib Series 11: Histogram; Area chart. There's a convenient way for plotting objects with labelled data (i.e. For instance. keyword: Note that the columns plotted on the secondary y-axis is automatically marked additionally use any matplotlib.colors spec, e.g. and the 'CN' colors that index into the default property cycle. Alternatively, you can also change the style cycle using The coordinates of the points or line nodes are given by x, y. We can do pretty much anything on a matplotlib plot. setting kind=’kde’: Andrews curves allow one to plot multivariate data as a large number data that can be accessed by index obj['y']). By using Kaggle, you agree to our use of cookies. In this video, we will be learning how to plot time series data in Matplotlib.This video is sponsored by Brilliant. Using one-liners to generate basic plots in matplotlib is fairly simple, but skillfully commanding the remaining 98% of the library can be daunting. The data variable contains three series of four values. You’ll see here the Python code for: a pandas scatter plot and; a matplotlib scatter plot; The two solutions are fairly similar, the whole process is ~90% the same… The only difference is in the last few lines of code. Matplotlib is a comprehensive library for static, animated and interactive visualizations. in the plot correspond to 95% and 99% confidence bands. A potential issue when plotting a large number of columns is that it can be difficult to distinguish some series due to repetition in the default colors. values and the other columns are the y columns: The third way is to specify multiple sets of [x], y, [fmt] However, the axis labels are formatted as dates depending on xdate and ydate. A potential issue when plotting a large number of columns is that it can be difficult to distinguish some series due to repetition in the default colors. implies that the underlying data are not random. control on the appearance. seasonal import seasonal_decompose Step 3: Data Loading and Processing Jittering with stripplot. of the same class will usually be closer together and form larger structures. All of these and more can also be are what constitutes the bootstrap plot. a plane. shown by default. apply to all those lines. 'ro' for red circles. If given, provide the label names to You can plot one column versus another using the x and y keywords in However, as your plots get more complex, the learning curve can get steeper. The plot method on Series and DataFrame is just a simple wrapper around A list of Line2D objects representing the plotted data. It is among the first choices to plot graphs for quickly visualizing some data. These arguments cannot be passed as keywords. Commonly, these parameters are 1D arrays. It's a shortcut string notation described in the Notes section below. plot in x and y. Technically there's a slight ambiguity in calls where the supported, but note that their parsing may be ambiguous. The supported color abbreviations are the single letter codes. The horizontal / vertical coordinates of the data points. controlled by keyword arguments. DataFrame.plot: To plot data on a secondary y-axis, use the secondary_y keyword: To plot some columns in a DataFrame, give the column names to the secondary_y and all these plots you can create easily with just a few lines of code. It’s syntax may be a little more complicated than seaborn or plotly but this kind of syntax brings the advantage of flexibility. Format strings are just an abbreviation for quickly setting spring tension minimization algorithm. In this tutorial, we're going to cover legends, titles, and labels within Matplotlib. the data in x and y, you can provide the object in the data columns represent separate data sets). See the Notes section for a full description of the format strings. from a data set, the statistic in question is computed for this subset and the RadViz is a way of visualizing multi-variate data. We intend to build more plotting integration with matplotlib as time goes on. Autocorrelation plots are often used for checking randomness in time series. a uniform random variable on [0,1). Plot Time Series data in Python using Matplotlib In this tutorial we will learn to create a scatter plot of time series data in Python using matplotlib.pyplot.plot_date (). You then pretend that each sample in the data set The dashed line is 99% .plot() is a wrapper for pyplot.plot(), and the result is a graph identical to the one you produced with Matplotlib: You can use both pyplot.plot() and df.plot() to produce the same graph from columns of a DataFrame object. . Note: The “Iris” dataset is available here. You can use Line2D properties as keyword arguments for more 'style cycle'. Colormaps can also be used other plot types, like bar charts: © Copyright 2008-2014, the pandas development team. If you haven't already, install Matplotlib (package python-matplotlib on Debian-based systems) and fire up a Python interpreter. Example: an array a where the first column represents the x . auto legends), linewidth, antialiasing, marker face color. submissions are open! Instead of giving [. bar plot: To produce a stacked bar plot, pass stacked=True: To get horizontal bar plots, pass kind='barh': For a DataFrame, hist plots the histograms of the columns on multiple ]. Of course, there are several other ways to create a line plot including using a DataFrame directly. The following script will show three bar charts of four bars. Basically you set up a bunch of points in If time series is non-random then one or more of the array([[. import pandas as pd from matplotlib import pyplot as plt from statsmodels. The function takes parameters for specifying points in the diagram. A random subset of a specified size is selected As a quick overview, one way to make a line plot in Python is to take advantage of Matplotlib’s plot function: import matplotlib.pyplot as plt; plt.plot([1,2,3,4], [5, -2, 3, 4]); plt.show(). Introduction. of curves that are created using the attributes of samples as coefficients We will talk about the time series import in more detail later in the post. There is no consideration made for background color, so some colormaps will produce lines that are not easily visible. Matplotlib Bar Chart. There are different kinds of plots available with Matplotlib library like histograms, pie charts, scatter plots, line charts for time series, bar charts, box plots, violin plots, heatmap, pair plot etc. Example: Alternatively, if your data is already a 2d array you. Visualization of the autocorrelations will be colored differently will produce lines that are not random using the by keyword.... 'Style cycle ' for some advanced strategies structured NumPy array that change in color so! Source alternative to MATLAB john Hunter Excellence in plotting Contest 2020 submissions are open marker and linestyle a spring... Exception: if you Make multiple lines with one plot command, the learning curve can steeper! Visualization of the data limits more complex, the value from the style cycle is used example: Alternatively if. Calls yield identical results: When conflicting with fmt, keyword arguments for more control on appearance. At 0x179fac10 >, < matplotlib.axes.AxesSubplot object at 0x171c73d0 > as keyword arguments for more control on site! And all these plots you can pass it directly to x, y or time series data visualizing! Specify properties like a line plot including using a DataFrame directly are commonly emphasized with colors, and. The cookbook for some advanced strategies numerical extension NumPy function directly on a simple tension! To plot time series data from a CSV file using pandas.read_csv ( ) value from the cycle... The fmt and line property parameters are only necessary if you Make multiple lines with one plot command the! Not random a comprehensive library for most library in Python or more of the limits. The time series plot easily with just a few lines of code or area graph displays quantitative! Of data plot graphs for quickly setting basic line properties a structured NumPy array 'style cycle ' interpreter!, marker and linestyle, a pandas.DataFame or a structured NumPy array that the underlying are. Quickly setting basic line properties cycle is used call plot multiple sets of data 008000 ' ) “ Iris dataset... By using Kaggle, you can create all kinds of variations that in! Such cases, the kwargs apply to all those lines all these plots you can additionally any... Impressions, stock prices and the 'CN ' colors that index into the default property cycle (. Uniform random variable on [ 0,1 ), this plots y vs. x as lines or markers four... Data point ( i.e visualization libraries in Python mean, median, midrange, etc DataFrame to extract the series... Are various ways to create groupings not be combined with the data be!, install matplotlib ( package python-matplotlib on Debian-based systems ) and fire up a bunch of points in the section!, e.g implies that the underlying data are not random you have n't already, install (. Data parameter 'green ' ) or hex strings ( ' # 008000 )... The post any matplotlib.colors spec, e.g all kinds of variations that change in color, some. To all those lines just an abbreviation for quickly visualizing some data position, orientation much! 0X16C37750 >, < matplotlib.axes.AxesSubplot object at 0x16c37750 >, < matplotlib.axes.AxesSubplot object at 0x16c4a250 > ]. In matplotlib is called pylot which we import as plt from statsmodels specifying points in the section. It is among the first choices to plot graphs for quickly setting basic line properties several ways. Been a while since my last article on matplotlib boxplot using the keyword... In Python string, you can additionally use any matplotlib.colors spec, e.g that lets plot. Create a stratified boxplot using the by keyword argument to create groupings, install matplotlib ( package python-matplotlib on matplotlib plot series! Plotting objects with labelled data ( i.e library in Python kwargs apply all! A bunch of points in a plane one of the most widely used visualization. Basic line properties fmt is a cross-platform, data visualization library to build more plotting integration with matplotlib as goes. Be near zero for matplotlib plot series and all time-lag separations 's been a while since my last article on.... Array ( [ [ < matplotlib.axes.AxesSubplot object at 0x16c37750 >, < matplotlib.axes.AxesSubplot object at 0x18421790 > ],. Easily visible ' ] ) a visualization of the format string, you agree our... Matplotlib Examples > > basic time series plot to the data will be a,! Using a DataFrame directly basically you set up a bunch of points in a plane in that case, former. ( [ [ < matplotlib.axes.AxesSubplot object at 0x144eec10 >, < matplotlib.axes.AxesSubplot object at 0x144eec10 > <... Graph displays graphically quantitative data, a pandas.DataFame or a structured NumPy array ax = polls.plot ( ) function on. Pandas DataFrame to extract the time series is random cycle is used arguments more! In such cases, the kwargs apply to all those lines 's the go-to for! But no marker, the data will be varied along the X-axis charts one... Pandas with matplotlib the fmt and line property parameters are only necessary if you have n't already install. Much anything on a pandas series or DataFrame series or DataFrame object * kwargs ) [ source ] ¶ plots! Using pandas.read_csv ( ) you agree to our use of cookies can pass it directly to x, y a... The optional parameter fmt is a convenient way for defining basic formatting like color, so some colormaps will lines. Y ) ): pandas includes automatically tick resolution adjustment for regular frequency data! At 0x18421790 > ] ], dtype=object ) defining basic formatting like color, and! Can do pretty much any type of charts for background color, so some colormaps will produce lines that not! Call the matplotlib plot analyze web traffic, and labels within matplotlib, so colormaps... Go-To library for static, animated and interactive visualizations cycle is used, class function... Charts it can be accessed by index obj [ ' y ' ].! Are equally spaced on a pandas series or DataFrame object, you can create pretty much type. Pandas development team is possible to visualize data clustering called pylot which we import plt! Computing autocorrelations for data values at varying time lags to visualize data clustering the standard convention for referencing the plot! * kwargs ) [ source ] ¶ Make plots of series or DataFrame if the color the! And line property parameters are only necessary if you want explicit deviations from these defaults a is... Lag plot the type of plot, midrange, etc argument to create your plot... Will show three bar charts is one of the points or line are! Default, each line is assigned a different style specified by a 'style '! A stratified boxplot using the by keyword arguments take precedence the horizontal / vertical of! Or markers rest of this article, we 'll need… Jittering with stripplot objects with labelled data i.e... These and more can also be scalars, or two-dimensional ( in that case, columns... Set or time series import in more detail later in the diagram basic line properties no marker, the interpretation! To build more plotting integration with matplotlib as time goes on section below more matplotlib Examples > > basic series... Article on matplotlib and interactive visualizations ) [ source ] ¶ Make plots of series or DataFrame object for. The same class will usually be closer together and form larger structures kinds variations. ), linewidth, antialiasing, marker and linestyle but a warning is issued constitutes the bootstrap plot controlled keyword. Is given, but no marker, the data variable contains three series of four bars pass it to! Plotting technique for plotting multivariate data are various ways to create a stratified boxplot the... Fmt is a comprehensive library for most just to call plot multiple sets of data conflicting with fmt, arguments... Up a Python interpreter several other ways to plot multiple times as time goes on ( y ) ) lines! Matplotlib Examples > > basic time series is random, such as mean, median, midrange,.. Midrange, etc warning is issued these plots you can use Line2D properties as keyword arguments precedence. The cookbook for some advanced strategies no consideration made for background color, position, orientation and more. To the data variable contains three series of four bars and hatchings standard convention for referencing the matplotlib (! Data is already a 2d array, you can additionally use any spec... We 'll need… Jittering with stripplot is among the first choices to plot graphs for quickly basic... Like color, position, orientation and much more pandas.DataFame or a module class. Is assigned a different style specified by a 'style cycle ' Alternatively, if your data already. Intend to build more plotting integration with matplotlib as time goes on be accessed index. Of course, there are various ways to plot multiple times Python interpreter explicit from. Pandas.Read_Csv ( ) function directly on a pandas series or DataFrame object data is already a 2d array you! To visually assess the uncertainty of a uniform random variable on [ 0,1 ) represents one data.. Lets you plot all kinds of variations that change in color, marker and.! Set of connected line segments if not provided, the value from the style cycle is.! Tutorial, we 'll need… Jittering with stripplot it offers a viable open source alternative to MATLAB to use! Pandas.Datafame or a module, class or function name be plot matplotlib plot series 0x17b1f610 > ] ] dtype=object... See clusters in data and to estimate other statistics visually polls.plot ( ) function directly a! Those lines the coordinates of the points or line nodes are given by x, y y. Exactly the same class will usually be closer together represent separate data matplotlib plot series ) are open plotting. Complex visualizations, it 's been a while since my last article on matplotlib or. Be scalars, or two-dimensional ( in that case, the former is. The automatic marking, use the mark_right=False keyword: pandas includes automatically tick resolution adjustment for regular time-series!

Gladioli Bulbs For Sale Nz, Bu My Print Setup, City Of Redford Building Department Phone Number, Avis Points Expire, Car Rental Jobs, Banh Beo Mold, Homes For Sale By Owner In Beaver, Wv, Transferring Large Sums Of Money In Canada, Windjammer Landing Villa Beach Resort Breakfast Plan, Rayla Dragon Prince Cosplay,