Use graph paper to create a scatter plot. The lattice package in R Programming provides xyplot to draw Scatter Plot. The required positional arguments supplied to plt. We will specifically use Pandas scatter to create a scatter plot. Scatter Plots can be made manually or in Excel. Its drag-and-drop interface makes it easy to sort, compare, and analyze data from multiple sources, including Excel, SQL Server, and cloud-based data repositories. Related course: Data Visualization with Python and Matplotlib. The scatter plot is a relatively simple tool, but it's also essential for doing data analysis and data science. Using seaborn, scatterplots are made using the regplot() function. It provides an object-oriented API that helps in embedding plots in applications using. It also is the language of choice for a couple of libraries I’ve been meaning to check out - Pandas and Bokeh. The package is flexible and offers lots of possibilities to visualize your data in a compelling way, but can be overwhelming. Multiple scatter plots for the relationships among MPG-city, price, and horsepower. If desired, you can have multiple scatter plots active simultaneously. Stay tuned for more charts. If it isn’t suitable for your needs, you can copy and modify it. Sign Up & Configure http://www. Plotting functions. subplots module. iris data is used. You have choose whether to plot smoothed line or not. In the example above the colour and shape of the scatter plot graphical objects is mapped to ‘day’ and ‘size’ attributes respectively. legend() method. How to plot 3D confidence ellipsoid by app; Steps Create the 3D Scatter plot with color index. A “scatter plot matrix” (see p. Source: http://mail. …To do this, lets go up to. If you have many dots and struggle with overplotting, consider using 2D density plot. Data visualization expert Matt Francis examines how. How and where would I add it? Also, how do I rearrange the layers so the scatter plot is above the geojson? Thanks a lot!. One example of this is to use different types of plots on the same graph. Basic Plotting Using Bokeh Python Pandas Library – Scatter, Line Visualizations Bokeh is a powerful framework for data visualization in Python. There are plots produced by gnuplot on Octave homepage. Let's do this now. Essentially what I need is very similar to the excel barchart attached except instead of a bar which is just showing an averaged value I would like to plot multiple points. Multiple plots on single axis It is time now to put together some of what you have learned and combine line plots on a common set of axes. We will look into how we can plot the relationship between variables (scatter plot), look into line plots and the histograms. org The goal of these posts is to demonstrate various functionality using examples likely to be encountered by a data scientist. title('Scatter plot example using matplotlib') plt. This is convenient for interactive work, but for programming it is recommended that the namespaces be kept separate, e. I have discussed about multiple types of plots in python matplotlib such as bar plot, scatter plot, pie plot, area plot etc. Simple linear regression is a way to describe a relationship between two variables through an equation of a straight line, called line of best fit, that most closely models this relationship. We can open the other two windows named Plot Browser and Property Editor by typing the commands plotbrowser , or propertyeditor in the command window respectively. Essentially what I need is very similar to the excel barchart attached except instead of a bar which is just showing an averaged value I would like to plot multiple points. , creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc. There are two key components of a correlation value: magnitude - The larger the magnitude (closer to 1 or -1), the stronger the correlation; sign - If negative, there is an inverse correlation. How to plot multiple lines on the same graph using R In this tutorial, you will find step-by-step instructions to create line graphs, especially multiple line graphs, and to place legends right on top of the lines. In fact, Plotly Express supports scatter and line plots in 3d, polar and ternary coordinates, as well as in 2d coordinates and on maps. Basic scatter plot plot Scatterplot with regression line. Simple Animated Plot with Matplotlib by PaulNakroshis Posted on March 23, 2012 Here’s a simple script which is a good starting point for animating a plot using matplotlib’s animation package (which, by their own admission, is really in a beta status as of matplotlib 1. docx - Data 101 Plots Typical commands. Python Matplotlib : Working With Multiple Plots. py, which is not the most recent version. I am planning to create a pdf of plots. Matplotlib is a widely used python based library; it is used to create 2d Plots and. Better Heatmaps and Correlation Matrix Plots in Python. Python integration (preview) We are excited to announce that Python, a programming language widely used by statisticians, data scientists, and data analysts, is now integrated into Power BI Desktop. How and where would I add it? Also, how do I rearrange the layers so the scatter plot is above the geojson? Thanks a lot!. 4 Scatter Plots. This needs to be repeated for 35 countries so that we can merge all 5-column plots on one or two A4 pages. Fill in the x and y coordinates and assign a color to the batch that you’re processing. I've tried several approaches so far. Matplotlib Tutorial: Adding legends and annotations to plots. Matplotlib offers simple and powerful plotting interface, versatile plot types and robust customization. Show Hide all comments. I am running IPython 1. Multiple graphs on one page (ggplot2) Problem. The lattice package in R Programming provides xyplot to draw Scatter Plot. For a set of data variables (dimensions) X 1, X 2, , X k, the scatter plot matrix shows all the pairwise scatter plots of the variables on a single view with multiple scatterplots in a matrix format. I set three points in a scatter plot, then, I take the data I used for the plot and get, using the transform, the corresponding point in pixels for each of the three points. Scatter function from plotly. SCATTER statement. Attempted to add a second y-axes using the code below: import dash import dash_core_components as dcc impor…. I have different visualization. legend() method. Python Scatter Plots Now you have proven out that your robot president is getting increasingly popular, but how are people finding out about it? Let's check in to modern democracy's answer to clever bumper stickers - the retweet. On some occasions, a 3d scatter plot may be a better data visualization than a 2d plot. show() You can use a boxplot to compare one continuous and one categorical variable. Use Dash to create interactive components with Plotly. I am trying to create a scatter graph which includes multiple sets of data. You can do this by using the DataFrame. Difference between scatter-plot and a dotplot. The position of a point depends on its two-dimensional value, where each value is a position on either the horizontal or vertical dimension. sin(x*2)); plt. Once you understood how to make a basic scatterplot with seaborn and how to custom shapes and color, you probably want the color corresponds to a categorical variable (a group). Companies that distribute public domain/freeware/shareware software for profit are expressly prohibited from distributing the 'Excel 3D Scatter Plot' workbook. It is assumed that you know how to enter data or read data files which is covered in the first chapter, and it is assumed that you are familiar with the different data types. Hi Python users, I'm a beginner and wondering if anyone can help with advice on how to plot multiple scatterplots using a loop import pandas as pd import matplotlib as plt import seaborn as sns, numpy. I am trying to create a scatter graph which includes multiple sets of data. In this post we will see examples of making scatter plots and coloring the data points using Seaborn in Python. Go to the tutorial on creating regression lines to find out how to use a regression line with this scatter plot to calculate the concentrations of the two unknowns. This lattice scatter plot in R is very useful to visualize the relationship between two sets of data. Graphs or plots are effective at showing data. Below is an excerpt from my script. First let's generate two data series y1 and y2 and plot them with the traditional points methods. The plot function plots columns of Y versus columns of X. Understand and use various plot types with Python Explore and work with different plotting libraries Learn to create effective visualizations Improve your Python data wrangling skills Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh Reinforce your knowledge of various data formats and representations; Who this book is for. This python Bar plot tutorial also includes the steps to create Horizontal Bar plot, Vertical Bar plot, Stacked Bar plot and Grouped Bar plot. Plot the relationship between the ratings for climate (first column) and housing (second column) grouped by city size in the matrix group. In this post you will discover exactly how you can visualize your machine learning data in Python using Pandas. It also is the language of choice for a couple of libraries I’ve been meaning to check out - Pandas and Bokeh. Scatter plot takes argument with only one feature in X and only one class in y. I am trying to plot some figures and save them as pdf. Multiple Axes in Python How to make a graph with multiple axes in python. In Perl, an implementation can be found in the Statistics-KernelEstimation module; In PHP, an implementation can be found in the MathPHP library. But before we begin, here is the general structure that you may use to create your charts using matplotlib: Scatter plot. scatter()) takes in x, y and z values which we can set using our xyz array object:. Making a 3D scatterplot is very similar to creating a 2d, only some minor differences. The dataset includes missing data as well. I created a scatter plot on AMcharts and each data point has its own label, but as soon as I put in more data the labels over flow. Here is an example of the Scatter Plot widget if the Show class density and Show regression line boxes are ticked. The first is a sample of random numbers drawn from a standard Gaussian. Multiple figures¶ With this groundwork out of the way, we can move on to some more advanced matplotlib use. We'll create three classes of points and plot each class in a different color. Best way to visualize data with two keys and many. The position of a point depends on its two-dimensional value, where each value is a position on either the horizontal or vertical dimension. In this tutorial, I'll use simple examples to show you how to create Scatter, Line and Bar charts using matplotlib. Legends and Keys Especially, if the data depicted in a chart contains multiple variables, it's a good idea to include a legend. One thing you should keep in mind that the number of values of x and y should be the same for plotting it. In the Microsoft API, the name ChartGroup is used for this. I'd like to plot both data sets of absorption (Y) on one time axis (X) but I can't find a way to include the two different sets of X variables, as if I plot the different Y series it will plot both against the X values of. Alternatively I could work with having multiple scatter plots in one figure, but I'm having a hard time trying to plot this. The scatter plot shows the number of comments and responses for 50 people. How can I get a trendline for the combination of all of these series in the chart?". and all these plots you can create easily with just a few lines of code. In the following example, we feed in arbitrarily created data of height and weight and plot them against each other. Linear Regression using Pandas (Python) November 11, 2014 August 27, 2015 John Stamford General So linear regression seem to be a nice place to start which should lead nicely on to logistic regression. matplotlib. How to Make Boxplots with Pandas. You do not need to be a Python developer to get started using the Python ecosystem for machine learning. Tap into the extensive visualization functionality enabled by the Plots ecosystem, and easily build your own complex graphics components with recipes. As an example, the scatter plot for the Titanic dataset, reporting on the gender of the passengers and the traveling class is shown below; without jittering, the scatter plot would display only eight distinct points. Best way to visualize data with two keys and many. I'm trying to create a scatter plot with the days as the x values, and all the experimental values collected on that day as the y values. Being able to quickly assess the linear association between two variables is one of the main purposes of using a scatter plot generator. They carried out a survey, the results of which are in bank_clean. How can I plot the following 3 functions (i. It is similar to a scatter plot except that the measurement points are ordered (typically by their x-axis value) and joined with straight line segments. Note that more elaborate visualization of this dataset is detailed in the Statistics in Python chapter. Now i want to add figure title and axes (X, Y) labels. one can visualize all the descriptive statistics effectively in the box plot with the normalized data whereas with the original data it is difficult to analyze. While the default settings for plots created in the Wolfram Language are sufficient in most cases, nearly every aspect of plots is customizable. Bivariate analysis is a simple (two variable) special case of multivariate analysis (where multiple relations between multiple variables are examined simultaneously). We'll start by setting up the notebook for plotting and importing the functions we will use:. set() method to change the scatter plot x-axis, y-axis label, and title. That is, explain what trends mean in terms of real-world quantities. scatter()) takes in x, y and z values which we can set using our xyz array object:. scatter in speed in Pytho Kernel density estimation using Python, matplotlib Check the url is indexed by Google using Python; Add second x-axis below first x-axis using Python Add second x-axis at top of figure using Python an Solve and animate single pendulum using scipy. Show or save the results + =. In Matplotlib we can create a line chart by calling the plot method. arithmetic operators. To get started using Bokeh to make your visualizations, start with the User Guide. We will plot boxplots in four ways, first with using Pandas’ boxplot function and then use Seaborn plotting library in three ways to get a much improved boxplot. Best fit lines tend to imply an ordering to the data, but scatter plots tend to imply the data might not be ordered in a way that is compatible with fitting. How can I plot the following 3 functions (i. • Make a directory for custom python modules • scatter_demo2. It was initially called as joyplots, for a brief time. temp is the x-axis and cnt is the y-axis. You have choose whether to plot smoothed line or not. Related course: Data Visualization with Python and Matplotlib. For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. i want to read from a text file (as attached) and i want to plot a scatterplot. The text is released under the CC-BY-NC-ND license, and code is released under the MIT license. Zooming and panning is supported during the updating process, before the plot is complete. We shall deal with the manipulation of plots and also learn about different ways of plotting, using a common data set to implement various plotting techniques with simple codes. Scatter plots¶ The scatter() function makes a scatter plot with (optional) size and color arguments. For example, if we run a statistical analysis that assumes our dependent variable is Normally distributed, we can use a Normal Q-Q plot to check that assumption. If we want to start by analyzing just the first three files in alphabetical order, we can use the sorted built-in function to generate a new sorted list from the glob. Plotly forum and Q/A site. 232 of text), separately for males and females. With enough coding you could do whatever you wanted. A numerical (quantitative) way of assessing the degree of linear association for a set of data pairs is by calculating the correlation coefficient. Name the different ways in which the data can be plot using Pyplot interface. A scatter plot (also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram) is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data. scatter()) takes in x, y and z values which we can set using our xyz array object:. A scatter plot is a type of plot that shows the data as a collection of points. Scatter plots allow you to map various data attributes to graphical properties of the plot. •subplot(rcp) creates an axes object on the figure for which it is called, or on the current figure if called as a pyplot function. Official seaborn tutorial¶. The following sample code utilizes the Axes3D function of matplot3d in Matplotlib. In your case, X has two features. This time, I’m going to focus on how you can make beautiful data visualizations in Python with matplotlib. Here is an example of the Scatter Plot widget if the Show class density and Show regression line boxes are ticked. This needs to be repeated for 35 countries so that we can merge all 5-column plots on one or two A4 pages. Stata: graph matrix height momheight dadheight, by(sex) or Graphics -> Scatterplot matrix Examining the plots, a few possible outliers are evident: A case with momheight = 80 inches. Here is an example showing the most basic utilization of this function. 0295 and we also have the lower and the upper bound aka the intervals of our x intercept value. Practice making sense of trends in scatter plots. How to plot 3D confidence ellipsoid by app; Steps Create the 3D Scatter plot with color index. ai's course that interprets the results of a random forest model using various techniques like partial dependence & tree interpreters. For instance, here is a boxplot representing five trials of 10 observations of a uniform random variable on [0,1). Matplotlib Tutorial: Adding legends and annotations to plots. Multiple regression yields graph with many dimensions. It's as if all 3 million colors are being slowly remapped every time--even for points which can't be seen. We can also plot multiple columns in one graph, by looping through the columns we want and plotting each column on the same axis. Create multiple scatter plots with different star symbols. One of my favorite functions in R is the pairs plot which makes high-level scatter plots to capture relationships between multiple variables within a dataframe. I have discussed about multiple types of plots in python matplotlib such as bar plot, scatter plot, pie plot, area plot etc. temp is the x-axis and cnt is the y-axis. k-means is a particularly simple and easy-to-understand application of the algorithm, and we will walk through it briefly here. org/pipermail/python-list/2006-February/369976. In our case, the “something” we want to do is generate a set of plots for each file in our inflammation dataset. In this way, the local change from point to point can be seen. In our Last tutorial, we discussed Python Charts - Bubble & 3D Charts. They are extracted from open source Python projects. The scatter plot is the first step as it provides the graphical display for any follow-up statistical analysis such as correlation and regression. 1-D interpolation (interp1d) ¶The interp1d class in scipy. Instead of having a single source of data like the funnel charts, the segmented funnel charts have multiple data sources. One example of this is to use different types of plots on the same graph. It would be appreciated if there are any Python VTK experts who could convert any of the c++ examples to Python!. The basic solution is to use the gridExtra R package, which comes with the following functions:. In fact, Plotly Express supports scatter and line plots in 3d, polar and ternary coordinates, as well as in 2d coordinates and on maps. Add it to the. And coloring scatter plots by the group/categorical variable will greatly enhance the scatter plot. Learn how to build univariate and multivariate linear models using the Python statsmodel library. Scatter and line plot with go. Art Draw 3D line animation using Python Matplotlib. Practice making sense of trends in scatter plots. Specify where to generate the output 5. Create one with Plotly in Python. Plotting functions. Setting interactive mode on is essential: plt. …Let me show you how that works. How to plot multiple scatter plots in seaborn: vikola: 2: 177: Jul-14-2019, 10:30 AM Last Post: vikola : Type error: dump() missing 1 required positional argument: fp: jaycuff13: 2: 427: Jul-13-2019, 10:21 AM Last Post: jaycuff13 : TypeError: can't multiply sequence by non-int of type 'str' rregorr: 2: 202: Jun-28-2019, 04:43 PM Last Post: Yoriz. Fundamentally, scatter works with 1-D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. Same for names. Seaborn is built on top of Matplotlib and is a. Plot 2D views of the iris dataset¶. I'm going to interpret your questions as "I have multiple XY series plotted in one chart. So, in this part, we discussed various types of plots we can create in matplotlib. Most of the stuff. data science instructor. Expectation–maximization (E–M) is a powerful algorithm that comes up in a variety of contexts within data science. Each subplot being the scatter histogra. Related course: Data Visualization with Python and Matplotlib. You can vote up the examples you like or vote down the exmaples you don't like. In this next part of the tutorial, we will work with another set of data. Python 3 and Matplotlib are the most easily accessible and efficient to use programs to do just this. The grid position specified by the third input is a row-based index. ylabel('y') plt. Generate Sample Data In Microsoft Blend Nov 20, 2015. The scatter plot shows the number of comments and responses for 50 people. Currently I'm working with 10 categories but I'm trying to make it dynamic. scatter allows us to not only plot on x and y, but it also lets us decide on the color, size, and type of marker we use. This article will take a comprehensive look at using histograms and density plots in Python using the matplotlib and seaborn libraries. We will plot boxplots in four ways, first with using Pandas' boxplot function and then use Seaborn plotting library in three ways to get a much improved boxplot. Give a name to x-axis and y-axis using. In last post I talked about plotting histograms, in this post we are going to learn how to use scatter plots with data and why it could be useful. Select (Charts) > Create Chart. The residuals are expected to be normally distributed with a mean of zero and a constant variance of. In Origin, 2D kernel density plot can be made from its user interface, and two functions, Ksdensity for 1D and Ks2density for 2D can be used from its LabTalk, Python, or C code. The scikit-learn Python library provides a suite of functions for generating samples from configurable test problems for regression and classification. and all these plots you can create easily with just a few lines of code. I've looked around but nothing I've found has solved my problem yet. In this next part of the tutorial, we will work with another set of data. Combine regplot() and FacetGrid to plot multiple linear relationships in a dataset. The problem is now that you cannot plot several columns at once using the scatter plot wrapper in pandas. Basically, the "thickness" of the bars is also define-able. Learn about Plotly to create plots like Bar Charts, Line Charts, Scatter Plots, Heat Maps, and more! Create Layouts with Plotly's Dash library. I would like to add multiple layers to my plot in Mapbox using Python. Example of Multiple Linear Regression in Python. You can find examples showing how to plot latitude and longitude scatter points on maps in the Basemap example gallery. Scatter plots of (x,y) point pairs are created with Matplotlib's plt. Using seaborn, scatterplots are made using the regplot() function. It allows us to create figures and plots, and makes it very easy to produce static raster or vector files without the need for any GUIs. And coloring scatter plots by the group/categorical variable will greatly enhance the scatter plot. The first step is to head to Chart Studio’s new online workspace and add your data. 0 release, some three-dimensional plotting utilities were built on top of Matplotlib's two-dimensional display, and the result is a convenient (if somewhat limited) set of tools for three-dimensional data visualization. If you want to repeat the scatter diagram, possibly to select a different regression equation, then you only have to press function key F7. Online weather conditions observed at the NCAR Foothills Laboratory. Let us first load packages we need. 6 64-bit (PD) installation (numpy, pandas, scipy, matplotlib, and statsmodels) and related code (import as , read_csv() functions). In this Python data visualization tutorial we learn how to make scatter plots in Python. This lattice scatter plot in R is very useful to visualize the relationship between two sets of data. import matplotlib. See here for some examples in python: Using scatter plots to understand multiple values of Y for a given X. com/public/mz47/ecb. On some occasions, a 3d scatter plot may be a better data visualization than a 2d plot. plot() function. The first positional argument specifies the x-value of each point on the scatter plot. To produce stacked area plot, each column must be either all positive or all negative values. graph_objects as go # Create random data with numpy import numpy as np N = 100 random_x = np. Notice that this example uses only some of the generated data for output. Line graphs are like scatter plots in that they record individual data values as marks on the graph. // Figure #2: Multiple plot and axis setting. While the default settings for plots created in the Wolfram Language are sufficient in most cases, nearly every aspect of plots is customizable. sin, cos and the addition), on the domain t, in the same figure? from numpy import * import math import matplotlib. Go to the tutorial on creating regression lines to find out how to use a regression line with this scatter plot to calculate the concentrations of the two unknowns. If you have introductory to intermediate knowledge in Python and statistics, you can use this article as a one-stop shop for building and plotting. Author: Thomas Breloff (@tbreloff) To get started, see the tutorial. The dimension of the graph increases as your features increases. sin(x)); That's all there is to plotting simple functions in matplotlib! Below we'll dive into some more details about how to control the appearance of the axes and lines. To my knowledge, python does not have any built-in functions which accomplish this so I turned to Seaborn, the statistical visualization library built on matplotlib, to accomplish this. docx - Data 101 Plots Typical commands. plot(), or DataFrame. XY scatter plots are created only to show relationship between two sets of VALUES. com/public/mz47/ecb. How to create the 3D Scatter plot with symbol color indexing. A scatter plot is a two dimensional data visualization that shows the relationship between two numerical variables — one plotted along the x-axis and the other plotted along the y-axis. Line plots of observations over time are popular, but there is a suite of other plots that you can use to learn more about your problem. Updating a matplotlib plot is straightforward. You use scale objects to specify these mappings. Scatter plot matrices. , X and Z or Y and Z). Provides a MATLAB-like plotting framework. The intermediate python course is crucial to your data science curriculum. Making a Matplotlib scatterplot from a pandas dataframe. In this course, learn what you need to know to analyze and display data using Tableau Desktop 2019—and make better, more data-driven decisions for your company. Preliminaries. This controls if the figure is redrawn every draw() command. For every example, we need a few libraries and to create a dataset:. I have my dataset that has multiple features and based on that the dependent variable is defined to be 0 or 1. How to change colors in Scatter plot? I need to change the default colors "dark red and dark blue" into "light red and light green" 0 Comments. Instructions for Conducting Multiple Linear Regression Analysis in SPSS. The optional return value h provides handles to the individual graphics objects in the scatter plots, whereas ax returns the handles to the scatter plot axes objects. If you don’t have that knowledge, I suggest you read my previous article that covers these topics. For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Line graphs are like scatter plots in that they record individual data values as marks on the graph. In this tutorial, you’ll be equipped to make production-quality, presentation-ready Python histogram plots with a range of choices and features. ly, write in the comments below, or tweet to @plotlygraphs. The coloring seems to work for the first plot, then fails for the second and th. php(143) : runtime-created function(1) : eval()'d code(156) : runtime-created. Multiple regression yields graph with many dimensions. Plotly forum and Q/A site. Instead of having a single source of data like the funnel charts, the segmented funnel charts have multiple data sources. I am closing out 2017 with a refreshing project that has led me away from Power BI for a bit. ; Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted. Output: Python Line Chart from List. An area plot is useful for comparing the values of different factors across a range. Creating scatterplots with Seaborn. The text is released under the CC-BY-NC-ND license, and code is released under the MIT license. For instance, you can have a bar chart and a line/scatter plot on the same graph. Python Matplotlib logarithmic scatter plot Mar 04, 2008. A Scatter Plot is useful to visualize the relationship between any two sets of data. There are 3 steps: Initialisation – K initial “means” (centroids) are generated at random Assignment – K clusters are created by associating each observation with the nearest centroid Update – The centroid of the clusters becomes the new mean Assignment and Update are repeated iteratively. Python 3 and Matplotlib are the most easily accessible and efficient to use programs to do just this. I need to prepare a "scatter" plot, as shown below, of say 5 variables (d1 to d5). followed by the tab key. Usage There are two main ways to use mpl-scatter-density , both of which are explained below. Logic is similar in both the ways - we will have a figure and we'll add multiple axes (sub-plots) on the figure one by one. The behavior they provide is similar to the default Python behavior, but when one of the arguments is a SymPy expression, a simplification will be attempted before the comparison is made. Leave your opinions in the comments below. We can also plot multiple columns in one graph, by looping through the columns we want and plotting each column on the same axis.