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| -rw-r--r-- | other_types_of_plots/script.rst | 189 |
1 files changed, 104 insertions, 85 deletions
diff --git a/other_types_of_plots/script.rst b/other_types_of_plots/script.rst index d87cb8c..21de16e 100644 --- a/other_types_of_plots/script.rst +++ b/other_types_of_plots/script.rst @@ -23,7 +23,6 @@ Language Reviewer : Bhanukiran Checklist OK? : <10-11-2010, Anand, OK> [2010-10-05] -.. #[Puneeth: Quickref missing] =================== Types of plots @@ -55,27 +54,18 @@ At the end of this tutorial, you will be able to #. Create log-log plots #. Use the matplotlib help -Let us begin with the scatter plot. - .. L3 {{{ Show slide with pre-requisite }}} -{{{ switch to the next slide, scatter plot }}} - .. R3 Before beginning this tutorial,we would suggest you to complete the tutorial on "Loading data from files" and "Plotting data". -In a scatter plot, the data is displayed as a collection of points, -where each point determines it's position on the horizontal axis and the -vertical axis respectively.This kind of plot is also called a -scatter chart, a scatter diagram or a scatter graph. - .. R4 -Before we proceed further, start your IPython interpreter +Before we start with the topic, let us start our IPython interpreter .. L4 @@ -85,33 +75,44 @@ ipython -pylab }}} ipython -pylab - .. L5 -{{{ switch to the slide having exercise 1 }}} +{{{ switch to the next slide, scatter plot }}} .. R5 +In a scatter plot, the data is displayed as a collection of points, +where each point determines it's position on the horizontal axis and the +vertical axis respectively.This kind of plot is also called a +scatter chart, a scatter diagram or a scatter graph. +Let us now generate a scatter plot with the help of an exercise + +.. L6 + +{{{ switch to the slide having exercise 1 }}} + +.. R6 + Plot a scatter plot showing the percentage profit of a company A from the year 2000-2010. The data for the same is available in the file ``company-a-data.txt``. -.. L6 +.. L7 {{{ open the file company-a-data.txt and show the content }}} -.. R6 +.. R7 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. -.. R7 +.. R8 To produce the scatter plot, we first need to load the data from the file using ``loadtxt`` command. -.. L7 +.. L8 {{{ close the file and switch to the terminal }}} @@ -121,179 +122,192 @@ file using ``loadtxt`` command. loadtxt('/home/fossee/other-plot/company-a-data.txt',dtype=type(int())) -.. R8 +.. R9 By default loadtxt converts the value to float. The ``dtype=type(int())`` argument in loadtxt converts the value to integer, as we require the data as integer further in the tutorial. -.. L8 +.. L9 -.. R9 +.. R10 Now in-order to generate the scatter graph we will use the function ``scatter()`` -.. L9 +.. L10 :: scatter(year,profit) -.. L10 +.. L11 {{{ switch to next slide, ``scatter`` function }}} -.. R10 +.. R11 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. -.. L11 +.. L12 {{{ switch to the next slide exercise 2 }}} -.. R11 +.. R12 Plot a scatter plot of the same data in company-a-data.txt with red diamond markers. Pause the video here, try out the following exercise and resume the video. -.. L12 +.. L13 +{{{continue from paused state}}} +{{{ Switch to the terminal }}} :: + clf() scatter(year,profit,color='r',marker='d') -.. R12 +.. R13 +Thus, we got our scatter plot. +It is always a good practice to clear the previous figure before +creating another one. Now let us see another kind of plot, the pie chart, for the same data. -.. L13 +.. L14 {{{ switch to the slide which says about pie chart }}} -.. R13 +.. R14 A pie chart or a circle graph is a circular chart divided into sectors, illustrating proportion. -.. L14 +.. L15 {{{ switch to the slide showing exercise 3 }}} -.. R14 +.. R15 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. +the same data from file ``company-a-data.txt``. -.. R15 +So let us reuse the data we have loaded from the file previously. + +.. R16 We can plot the pie chart using the function ``pie()``. -.. L15 +.. L16 +{{{ Switch to the terminal }}} :: + clf() pie(profit,labels=year) -.. L16 +.. L17 {{{ switch to next slide, ``pie()`` function }}} -.. R16 +.. R17 Notice that we passed two arguments to the function ``pie()``. First one the values and the next one the set of labels to be used in the pie chart. -.. L17 +Pause the video here, try out the following exercise and resume the video. + +.. L18 {{{ switch to the next slide with exercise 4 }}} -.. R17 +.. R18 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. -Pause the video here, try out the following exercise and resume the video. - -.. L18 +.. L19 +{{{ Switch to the terminal }}} :: + clf() pie(t,labels=s,colors=('w','r','k','m','y','b','g','c','y','m','b')) -.. R18 +.. R19 -.. L19 +.. L20 {{{ switch to the slide which says about bar chart }}} -.. R19 +.. R20 Now let us move on to the bar charts. A bar chart or bar graph is a chart with rectangular bars with lengths proportional to the values that they represent. -.. L20 +.. L21 {{{ switch to the slide showing exercise 5 }}} -.. R20 +.. R21 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. -.. R21 +.. R22 We can plot the bar chart using the function ``bar()``. -.. L21 +.. L22 +{{{ Switch to the terminal }}} :: - bar(year,profit) + clf() + bar(year,profit) -.. R22 +.. R23 {{{ switch to the next slide, ``bar()`` function }}} -.. R22 +.. R23 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. -.. L23 +.. L24 {{{ switch to the next slide with exercise 6 }}} -.. R23 +.. R24 Plot a bar chart which is not filled and which is hatched with 45\ :sup:`o` slanting lines as shown in the image.The data for the chart may be obtained from the file ``company-a-data.txt``. -.. L24 +.. L25 :: - bar(year,profit,fill=False,hatch='/') - -.. R24 + clf() + bar(year,profit,fill=False,hatch='/') +.. R25 -.. L25 +.. L26 {{{ switch to the slide which says about log-log graph }}} -.. R25 +.. R26 Now let us move on to the log-log plot. A log-log graph or a log-log plot is a two-dimensional graph of numerical data that uses logarithmic scales @@ -301,72 +315,75 @@ 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 -.. L26 +.. L27 {{{ switch to the slide showing exercise 7 }}} -.. R26 +.. R27 Plot a `log-log` chart of y=5*x\ :sup:`3` for x from 1-20. -.. R27 +.. R28 Before we actually plot let us calculate the points needed for that. -.. L27 +.. L28 +{{{ Switch to the terminal }}} :: x = linspace(1,20,100) y = 5*x**3 -.. L28 +.. L29 {{{ switch to next slide, ``loglog()`` function }}} -.. R28 +.. R29 -Here is the syntax of the log-lof function. +Here is the syntax of the log-log function. Now we can plot the log-log chart using ``loglog()`` function, -.. L29 +.. L30 +{{{ Switch to the terminal }}} :: + clf() loglog(x,y) -.. R29 - .. R30 +.. R31 + To understand the difference between a normal ``plot`` and a ``log-log plot`` let us create another plot using the function ``plot``. -.. L30 +.. L31 :: figure(2) plot(x,y) -.. L31 +.. L32 {{{ show both the plots side by side }}} -.. R31 +.. R32 -The differnce is clear.So that was ``log-log() plot``. +The difference is clear.So that was ``log-log() plot``. -.. L32 +.. L33 {{{ switch to the next slide which says: "How to get help on matplotlib online"}}} -.. R32 +.. R33 Now we will see few more plots and also see how to access help of -matplotlib over the internet. +matplotlib over the Internet. Help about matplotlib can be obtained from matplotlib.sourceforge.net/contents.html @@ -376,11 +393,11 @@ More plots can be seen at matplotlib.sourceforge.net/users/screenshots.html and also at matplotlib.sourceforge.net/gallery.html -.. L33 +.. L34 {{{ switch to summary slide }}} -.. R33 +.. R34 This brings us to the end of this tutorial. In this tutorial we learnt to, @@ -391,11 +408,11 @@ In this tutorial we learnt to, #. Plot a log-log graph using ``loglog()`` function #. Access the matplotlib online help. -.. L34 +.. L35 {{Show self assessment questions slide}} -.. R34 +.. R35 Here are some self assessment questions for you to solve. @@ -413,23 +430,25 @@ Here are some self assessment questions for you to solve. - bar(x, y, fill=False, hatch='|') - bar(x, y, color='w', hatch='\') -.. L35 +.. L36 {{{solution of self assessment questions on slide}}} -.. R35 +.. R36 And the answers, 1. False. Both functions do not produce the same kind of plot. + 2. ``bar(x, y, fill=False, hatch='|')`` is the correct option to generate a bar chart with vertical line hatching. -.. L36 +.. L37 {{{ switch to the thank you slide }}} -.. R36 +.. R37 Hope you have enjoyed this tutorial and found it useful. Thank you! + |