diff -r 25b4e962b55e -r c7f0069d698a other-type-of-plots/script.rst --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/other-type-of-plots/script.rst Sat Oct 09 03:56:06 2010 +0530 @@ -0,0 +1,220 @@ +.. 2.4 LO: other types of plots (3) [anoop] +.. ----------------------------------------- +.. * scatter +.. * pie chart +.. * bar chart +.. * log +.. * illustration of other plots, matplotlib help + +=================== +Other type of plots +=================== + +{{{ show the first slide }}} + +Hello and welcome to the tutorial other type of plots. + +{{{ show the outline slide }}} + +In this tutorial we will cover scatter plot, pie chart, bar chart and +log plot. We will also see few other plots and also introduce you to +the matplotlib help. + + +Let us start with scatter plot. + +{{{ switch to the next slide }}} + +In a scatter plot, the data is displayed as a collection of points, +each having the value of one variable determining the position on the +horizontal axis and the value of the other variable determining the +position on the vertical axis. This kind of plot is also called a +scatter chart, scatter diagram and scatter graph. + +Before we proceed further get your IPython interpreter running with +the ``-pylab`` option. Start your IPython interpreter as +:: + + ipython -pylab + +{{{ open the ipython interpreter in the terminal using the command +ipython -pylab }}} + +{{{ switch to the next slide having the problem statement of first +exercise }}} + +Now, let us plot a scatter plot showing the percentage profit of company A +from the year 2000-2010. The data for the same is available in the +file ``company-a-data.txt``. + +{{{ open the file company-a-data.txt and show the content }}} + +The data file has two lines with a set of values in each line, the +first line representing years and the second line representing the +profit percentages. + +{{{ close the file and switch to the terminal }}} + +To product the scatter plot first we need to load the data from the +file using ``loadtxt``. We learned in one of the previous sessions, +and it can be done as :: + + year,profit = loadtxt('/home/fossee/other-plot/company-a-data.txt',dtype=type(int())) + +Now in-order to generate the scatter graph we will use the function +``scatter()`` +:: + + scatter(year,profit) + +Notice that we passed two arguments to ``scatter()`` function, first +one the values in x-coordinate, year, and the other the values in +y-coordinate, the profit percentage. + +{{{ switch to the next slide which has the problem statement of +problem to be tried out }}} + +Now here is a question for you to try out, plot the same data with red +diamonds. + +**Clue** - *try scatter? in your ipython interpreter* + +.. scatter(year,profit,color='r',marker='d') + +Now let us move on to pie chart. + +{{{ switch to the slide which says about pie chart }}} + +A pie chart or a circle graph is a circular chart divided into +sectors, illustrating proportion. + +{{{ switch to the slide showing the problem statement of second +exercise question }}} + +Plot a pie chart representing the profit percentage of company A, with +the same data from file ``company-a-data.txt``. So let us reuse the +data we have loaded from the file previously. + +We can plot the pie chart using the function ``pie()``. +:: + + pie(profit,labels=year) + +Notice that we passed two arguments to the function ``pie()``. The +first one the values and the next one the set of labels to be used in +the pie chart. + +{{{ switch to the next slide which has the problem statement of +problem to be tried out }}} + +Now here is a question for you to try out, plot a pie chart with the +same data with colors for each wedges as white, red, black, magenta, +yellow, blue, green, cyan, yellow, magenta and blue respectively. + +**Clue** - *try pie? in your ipython interpreter* + +.. pie(t,labels=s,colors=('w','r','k','m','y','b','g','c','y','m','b')) + +{{{ switch to the slide which says about bar chart }}} + +Now let us move on to bar chart. A bar chart or bar graph is a chart +with rectangular bars with lengths proportional to the values that +they represent. + +{{{ switch to the slide showing the problem statement of third +exercise question }}} + +Plot a bar chart representing the profit percentage of company A, with +the same data from file ``company-a-data.txt``. + +So let us reuse the data we have loaded from the file previously. + +We can plot the bar chart using the function ``bar()``. +:: + + bar(year,profit) + +Note that the function ``bar()`` needs at least two arguments one the +values in x-coordinate and the other values in y-coordinate which is +used to determine the height of the bars. + +{{{ switch to the next slide which has the problem statement of +problem to be tried out }}} + +Now here is a question for you to try, plot a bar chart which is not +filled and which is hatched with 45\ :sup:`o` slanting lines as shown +in the image in the slide. + +**Clue** - *try bar? in your ipython interpreter* + +.. bar(year,profit,fill=False,hatch='/') + +{{{ switch to the slide which says about bar chart }}} + +Now let us move on to log-log plot. A log-log graph or log-log plot is +a two-dimensional graph of numerical data that uses logarithmic scales +on both the horizontal and vertical axes. Because of the nonlinear +scaling of the axes, a function of the form y = ax\ :sup:`b` will +appear as a straight line on a log-log graph + +{{{ switch to the slide showing the problem statement of fourth +exercise question }}} + + +Plot a `log-log` chart of y=5*x\ :sup:`3` for x from 1-20. + +Before we actually plot let us calculate the points needed for +that. And it could be done as, +:: + + x = linspace(1,20,100) + y = 5*x**3 + +Now we can plot the log-log chart using ``loglog()`` function, +:: + + loglog(x,y) + +To understand the difference between a normal ``plot`` and a ``log-log +plot`` let us create another plot using the function ``plot``. +:: + + figure(2) + plot(x,y) + +{{{ show both the plots side by side }}} + +So that was ``log-log() plot``. + +{{{ switch to the next slide which says: "How to get help on +matplotlib online"}}} + +Now we will see few more plots and also see how to access help of +matplotlib over the internet. + +Help about matplotlib can be obtained from +matplotlib.sourceforge.net/contents.html + +.. #[[Anoop: I am not so sure how to do the rest of it, so I guess we + can just browse through the side and tell them few. What is your + opinion??]] + +Now let us see few plots from +matplotlib.sourceforge.net/users/screenshots.html + +{{{ browse through the site quickly }}} + +{{{ switch to recap slide }}} + +Now we have come to the end of this tutorial. We have covered scatter +plot, pie chart, bar chart, log-log plot and also saw few other plots +and covered how to access the matplotlib online help. + +{{{ switch to the thank you slide }}} + +Thank you! + +.. Author: Anoop Jacob Thomas + Reviewer 1: + Reviewer 2: + External reviewer: