# HG changeset patch # User anoop # Date 1286573382 -19800 # Node ID 2ed3c5a3f8563da205be883411dac8f3c5ec3524 # Parent f9d7cedf85364f4395589250ffe32341535c1c19 removed a duplicate file. other_types_of_plots.rst. diff -r f9d7cedf8536 -r 2ed3c5a3f856 other_types_of_plots.rst --- a/other_types_of_plots.rst Sat Oct 09 02:39:11 2010 +0530 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,220 +0,0 @@ -.. 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: