1 .. 2.4 LO: other types of plots (3) [anoop] 

     2 .. -----------------------------------------

     3 .. * scatter 

     4 .. * pie chart 

     5 .. * bar chart 

     6 .. * log 

     7 .. * illustration of other plots, matplotlib help

     8 

     9 ===================

    10 Other type of plots

    11 ===================

    12 

    13 {{{ show the first slide }}}

    14 

    15 Hello and welcome to the tutorial other type of plots.

    16 

    17 {{{ show the outline slide }}}

    18 

    19 In this tutorial we will cover scatter plot, pie chart, bar chart and

    20 log plot. We will also see few other plots and also introduce you to

    21 the matplotlib help.

    22 

    23 

    24 Let us start with scatter plot. 

    25 

    26 {{{ switch to the next slide }}}

    27 

    28 In a scatter plot, the data is displayed as a collection of points,

    29 each having the value of one variable determining the position on the

    30 horizontal axis and the value of the other variable determining the

    31 position on the vertical axis. This kind of plot is also called a

    32 scatter chart, scatter diagram and scatter graph.

    33 

    34 Before we proceed further get your IPython interpreter running with

    35 the ``-pylab`` option. Start your IPython interpreter as

    36 ::

    37 

    38     ipython -pylab

    39 

    40 {{{ open the ipython interpreter in the terminal using the command

    41 ipython -pylab }}}

    42 

    43 {{{ switch to the next slide having the problem statement of first

    44 exercise }}}

    45 

    46 Now, let us plot a scatter plot showing the percentage profit of company A

    47 from the year 2000-2010. The data for the same is available in the

    48 file ``company-a-data.txt``. 

    49 

    50 {{{ open the file company-a-data.txt and show the content }}}

    51 

    52 The data file has two lines with a set of values in each line, the

    53 first line representing years and the second line representing the

    54 profit percentages.

    55 

    56 {{{ close the file and switch to the terminal }}}

    57 

    58 To product the scatter plot first we need to load the data from the

    59 file using ``loadtxt``. We learned in one of the previous sessions,

    60 and it can be done as ::

    61 

    62     year,profit = loadtxt('/home/fossee/other-plot/company-a-data.txt',dtype=type(int()))

    63 

    64 Now in-order to generate the scatter graph we will use the function 

    65 ``scatter()`` 

    66 ::

    67 

    68 	scatter(year,profit)

    69 

    70 Notice that we passed two arguments to ``scatter()`` function, first

    71 one the values in x-coordinate, year, and the other the values in

    72 y-coordinate, the profit percentage.

    73 

    74 {{{ switch to the next slide which has the problem statement of

    75 problem to be tried out }}}

    76 

    77 Now here is a question for you to try out, plot the same data with red

    78 diamonds. 

    79 

    80 **Clue** - *try scatter? in your ipython interpreter* 

    81 

    82 .. scatter(year,profit,color='r',marker='d')

    83 

    84 Now let us move on to pie chart.

    85 

    86 {{{ switch to the slide which says about pie chart }}}

    87 

    88 A pie chart or a circle graph is a circular chart divided into

    89 sectors, illustrating proportion.

    90 

    91 {{{ switch to the slide showing the problem statement of second

    92 exercise question }}}

    93 

    94 Plot a pie chart representing the profit percentage of company A, with

    95 the same data from file ``company-a-data.txt``. So let us reuse the

    96 data we have loaded from the file previously.

    97 

    98 We can plot the pie chart using the function ``pie()``.

    99 ::

   100 

   101    pie(profit,labels=year)

   102 

   103 Notice that we passed two arguments to the function ``pie()``. The

   104 first one the values and the next one the set of labels to be used in

   105 the pie chart.

   106 

   107 {{{ switch to the next slide which has the problem statement of

   108 problem to be tried out }}}

   109 

   110 Now here is a question for you to try out, plot a pie chart with the

   111 same data with colors for each wedges as white, red, black, magenta,

   112 yellow, blue, green, cyan, yellow, magenta and blue respectively.

   113 

   114 **Clue** - *try pie? in your ipython interpreter* 

   115 

   116 .. pie(t,labels=s,colors=('w','r','k','m','y','b','g','c','y','m','b'))

   117 

   118 {{{ switch to the slide which says about bar chart }}}

   119 

   120 Now let us move on to bar chart. A bar chart or bar graph is a chart

   121 with rectangular bars with lengths proportional to the values that

   122 they represent.

   123 

   124 {{{ switch to the slide showing the problem statement of third

   125 exercise question }}}

   126 

   127 Plot a bar chart representing the profit percentage of company A, with

   128 the same data from file ``company-a-data.txt``. 

   129 

   130 So let us reuse the data we have loaded from the file previously.

   131 

   132 We can plot the bar chart using the function ``bar()``.

   133 ::

   134 

   135    bar(year,profit)

   136 

   137 Note that the function ``bar()`` needs at least two arguments one the

   138 values in x-coordinate and the other values in y-coordinate which is

   139 used to determine the height of the bars.

   140 

   141 {{{ switch to the next slide which has the problem statement of

   142 problem to be tried out }}}

   143 

   144 Now here is a question for you to try, plot a bar chart which is not

   145 filled and which is hatched with 45\ :sup:`o` slanting lines as shown

   146 in the image in the slide.

   147 

   148 **Clue** - *try bar? in your ipython interpreter* 

   149 

   150 .. bar(year,profit,fill=False,hatch='/')

   151 

   152 {{{ switch to the slide which says about bar chart }}}

   153 

   154 Now let us move on to log-log plot. A log-log graph or log-log plot is

   155 a two-dimensional graph of numerical data that uses logarithmic scales

   156 on both the horizontal and vertical axes. Because of the nonlinear

   157 scaling of the axes, a function of the form y = ax\ :sup:`b` will

   158 appear as a straight line on a log-log graph

   159 

   160 {{{ switch to the slide showing the problem statement of fourth

   161 exercise question }}}

   162 

   163 

   164 Plot a `log-log` chart of y=5*x\ :sup:`3` for x from 1-20.

   165 

   166 Before we actually plot let us calculate the points needed for

   167 that. And it could be done as,

   168 ::

   169 

   170     x = linspace(1,20,100)

   171     y = 5*x**3

   172 

   173 Now we can plot the log-log chart using ``loglog()`` function,

   174 ::

   175 

   176     loglog(x,y)

   177 

   178 To understand the difference between a normal ``plot`` and a ``log-log

   179 plot`` let us create another plot using the function ``plot``.

   180 ::

   181 

   182     figure(2)

   183     plot(x,y)

   184 

   185 {{{ show both the plots side by side }}}

   186 

   187 So that was ``log-log() plot``.

   188 

   189 {{{ switch to the next slide which says: "How to get help on

   190 matplotlib online"}}}

   191 

   192 Now we will see few more plots and also see how to access help of

   193 matplotlib over the internet.

   194 

   195 Help about matplotlib can be obtained from

   196 matplotlib.sourceforge.net/contents.html

   197 

   198 .. #[[Anoop: I am not so sure how to do the rest of it, so I guess we

   199    can just browse through the side and tell them few. What is your

   200    opinion??]]

   201 

   202 Now let us see few plots from

   203 matplotlib.sourceforge.net/users/screenshots.html

   204 

   205 {{{ browse through the site quickly }}}

   206 

   207 {{{ switch to recap slide }}}

   208 

   209 Now we have come to the end of this tutorial. We have covered scatter

   210 plot, pie chart, bar chart, log-log plot and also saw few other plots

   211 and covered how to access the matplotlib online help.

   212 

   213 {{{ switch to the thank you slide }}}

   214 

   215 Thank you!

   216 

   217 ..  Author: Anoop Jacob Thomas <anoop@fossee.in>

   218     Reviewer 1:

   219     Reviewer 2:

   220     External reviewer: