-------------------------------------------------------------------------------
log: C:\AAA Miker Files\newer web pages\soc_meth_proj3\class 4.smcl
log type: smcl
opened on: 21 May 2003, 11:24:33
. set mem 50m
Current memory allocation
current memory usage
settable value description (1M = 1024k)
--------------------------------------------------------------------
set maxvar 5000 max. variables allowed 1.733M
set memory 50M max. data space 50.000M
set matsize 400 max. RHS vars in models 1.254M
-----------
52.987M
. graph using "C:\AAA Miker Files\newer web pages\soc_meth_proj3\Gender age ear
> nings.gph"
. graph using "C:\AAA Miker Files\newer web pages\soc_meth_proj3\gender age ed.
> gph"
. use "C:\AAA Miker Files\newer web pages\soc_meth_proj3\cps_y2k_numeric.dta",
> clear
. table age sex
--------------------------
| p20
p15 | male female
----------+---------------
0 | 902 811
1 | 1,012 920
2 | 989 961
3 | 1,020 919
4 | 952 1,013
5 | 1,002 996
6 | 1,035 1,024
7 | 1,096 1,080
8 | 1,106 1,057
9 | 1,124 1,119
10 | 1,118 1,084
11 | 1,022 1,061
12 | 1,028 1,007
13 | 1,054 993
14 | 978 1,001
15 | 1,038 1,008
16 | 1,025 940
17 | 1,012 986
18 | 923 924
19 | 942 884
20 | 847 875
21 | 847 840
22 | 807 831
23 | 798 824
24 | 784 878
25 | 798 868
26 | 797 843
27 | 855 871
28 | 899 902
29 | 919 1,076
30 | 964 943
31 | 998 993
32 | 922 968
33 | 923 975
34 | 952 1,072
35 | 1,066 1,068
36 | 1,024 1,099
37 | 1,023 1,076
38 | 1,019 1,045
39 | 1,074 1,154
40 | 1,031 1,159
41 | 1,001 1,114
42 | 1,028 1,109
43 | 1,060 1,031
44 | 1,026 1,088
45 | 1,044 1,074
46 | 918 1,021
47 | 961 996
48 | 892 935
49 | 839 928
50 | 924 941
51 | 885 917
52 | 883 942
53 | 815 880
54 | 634 667
55 | 662 661
56 | 616 708
57 | 651 653
58 | 504 624
59 | 517 612
60 | 547 607
61 | 508 543
62 | 532 541
63 | 456 482
64 | 436 516
65 | 464 550
66 | 416 453
67 | 435 491
68 | 398 510
69 | 424 480
70 | 395 518
71 | 392 493
72 | 323 447
73 | 337 460
74 | 366 448
75 | 350 446
76 | 275 429
77 | 272 374
78 | 276 411
79 | 252 350
80 | 212 302
81 | 198 278
82 | 173 252
83 | 159 268
84 | 118 207
85 | 110 196
86 | 79 169
87 | 77 132
88 | 52 120
89 | 53 102
90 | 121 295
--------------------------
. *That's just like using tabulate to cross tabulate age and sex
. table age sex, contents (mean ernval2)
------------------------------
| p20
p15 | male female
----------+-------------------
0 | 0 0
1 | 0 0
2 | 0 0
3 | 0 0
4 | 0 0
5 | 0 0
6 | 0 0
7 | 0 0
8 | 0 0
9 | 0 0
10 | 0 0
11 | 0 0
12 | 0 0
13 | 0 0
14 | 0 0
15 | 358.9066 237.7391
16 | 1034.555 696.8564
17 | 1685.804 1470.296
18 | 3256.117 2903.62
19 | 6180.71 5154.389
20 | 8064.335 5878.957
21 | 9959.556 7101.669
22 | 12128.76 8590.962
23 | 14623.76 10270.05
24 | 16481.92 11636.9
25 | 20902.39 13811.94
26 | 24276.9 15750.91
27 | 25474.01 16302.89
28 | 27417.74 16703.85
29 | 27814.31 17828.96
30 | 29839.51 17174.32
31 | 31598.28 18059.29
32 | 34460.11 18063.74
33 | 34904.86 19340.78
34 | 34620.96 17544.7
35 | 36505.16 19231.13
36 | 37502.23 18436.33
37 | 37686.13 18566.77
38 | 40886.73 20323.18
39 | 40714.84 18531.64
40 | 38992.59 20154.87
41 | 39452.46 21551.37
42 | 41979.26 21292.34
43 | 40804.45 21790.84
44 | 40789.16 20274.15
45 | 39718.97 21736.62
46 | 42730.95 21239.43
47 | 42783.79 21636.39
48 | 45377.23 21605.61
49 | 43001.77 21963.61
50 | 43366.89 21823.49
51 | 42470.98 22146.05
52 | 42029.13 21475.88
53 | 44518.15 20417.05
54 | 40579.79 19080.14
55 | 40002.8 18192.76
56 | 39262.53 19099.1
57 | 40540.59 15432.12
58 | 34512.29 15309.23
59 | 34754.65 14814.33
60 | 31289.06 13148.44
61 | 29602.38 13898.95
62 | 24327.11 10629.85
63 | 21897.96 7777.759
64 | 19935.72 7266.785
65 | 15314.79 5157.113
66 | 12429.09 3629.925
67 | 9046.913 3427.409
68 | 10520.75 3109.065
69 | 7394.212 2579.933
70 | 7469.731 1319.745
71 | 5409.038 2365.813
72 | 6568.935 1410.045
73 | 7248.267 1370.62
74 | 5254.582 1228.623
75 | 3330.326 1016.991
76 | 2335.666 946.6294
77 | 4229.669 803.0267
78 | 1679.007 441.7032
79 | 4122.377 624.6543
80 | 3185.873 250.0298
81 | 3836.202 594.5756
82 | 2204.63 326.3413
83 | 3118.245 705.5597
84 | 1823.475 519.0966
85 | 1242.727 33.20408
86 | 1743.038 0
87 | 792.2208 198.4848
88 | 400 0
89 | 4883.34 0
90 | 942.1487 209.1525
------------------------------
. table age sex [fweight=wgt2], contents (mean ernval2) replace
------------------------------
| p20
p15 | male female
----------+-------------------
0 | 0 0
1 | 0 0
2 | 0 0
3 | 0 0
4 | 0 0
5 | 0 0
6 | 0 0
7 | 0 0
8 | 0 0
9 | 0 0
10 | 0 0
11 | 0 0
12 | 0 0
13 | 0 0
14 | 0 0
15 | 396.319 183.7211
16 | 1020.365 713.4266
17 | 1610.828 1465.907
18 | 3243.765 2903.755
19 | 6337.779 5588.09
20 | 7875.336 5902.063
21 | 9815.773 7328.729
22 | 12394.81 8554.747
23 | 14481.45 10592.13
24 | 16769.89 12120.36
25 | 21444.51 14749.22
26 | 25498.8 16947.93
27 | 26538.1 17267.25
28 | 29215 17458.98
29 | 29169.08 18324.94
30 | 31499.9 18273.63
31 | 31936.6 19024.94
32 | 36682.82 19109.75
33 | 36278.11 20206.75
34 | 36316.5 18442.74
35 | 38402.54 19924.91
36 | 38287.57 19088.01
37 | 38749.87 19072.99
38 | 42316.86 20287.62
39 | 42051.19 18374.46
40 | 40630.51 20844.5
41 | 40755.96 22472.4
42 | 43016.46 21300.15
43 | 42146.82 22280.97
44 | 41745.25 20729.45
45 | 41480.81 22355.97
46 | 44197.24 21996.38
47 | 43890.82 22360.41
48 | 48550.66 22202.53
49 | 45050.73 22651.13
50 | 44697.07 22753.46
51 | 44547 22754.16
52 | 44251.02 22612.03
53 | 45776.5 21017.59
54 | 43153.59 19101.49
55 | 41474.79 18239.59
56 | 39952.82 19010.76
57 | 41662.03 15656.72
58 | 35080.16 15512.6
59 | 36322.61 14706
60 | 31705.73 13512.34
61 | 32187.32 14354.84
62 | 25179.5 10299.66
63 | 23907.55 8270.257
64 | 19459.92 7731.409
65 | 16299.65 5060.667
66 | 12058.98 3553.587
67 | 9790.435 3496.792
68 | 11131.51 3238.803
69 | 7651.15 2648.869
70 | 7762.551 1359.102
71 | 6021.53 2262.92
72 | 7369.7 1384.317
73 | 7036.694 1555.345
74 | 5632.944 1439.468
75 | 3564.04 1088.662
76 | 2251.615 956.7117
77 | 4255.651 904.6344
78 | 1519.77 535.3051
79 | 3802.322 544.5576
80 | 4496.77 249.0527
81 | 4428.576 788.4609
82 | 1690.87 356.2551
83 | 3756.357 882.6436
84 | 2287.44 491.2287
85 | 1471.763 48.12194
86 | 1797.336 0
87 | 753.168 339.1927
88 | 375.0294 0
89 | 2934.092 0
90 | 1295.411 188.9299
------------------------------
. *This is a new dataset, and a small one, so this would be easy to save anywhe
> re.
. describe
Contains data
obs: 182
vars: 3
size: 1,820 (100.0% of memory free)
-------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------
age byte %8.0g p15
sex byte %8.0g sexnm p20
table1 float %9.0g mean(ernval2)
-------------------------------------------------------------------------------
Sorted by: age sex
Note: dataset has changed since last saved
. rename table1 mean_earnings
. graph mean_earnings age if sex==2
. graph mean_earnings age if sex==1
. gen men_earnings= mean_earnings if sex==1
(91 missing values generated)
. gen female_earnings= mean_earnings if sex==2
(91 missing values generated)
. graph men_earnings female_earnings age
. *Now let's say we wanted to make the axes look nicer
. graph men_earnings female_earnings age, xlab(0 (5) 90) ylab(0 (10000) 50000)
. *That last command got the axes looking right.
. graph men_earnings female_earnings age, xlab(0 (5) 90) ylab(0 (10000) 50000)
> b2title("age")
. *there's a tutorial for graph
. tutorial graph
file graph.tut not found
r(601);
. tutorial graphics
___ ____ ____ ____ ____ tm
/__ / ____/ / ____/
___/ / /___/ / /___/ How to Make Graphs
--------------------------------------------------
We are about to demonstrate Stata's graphics. Actually, we will only scratch
the surface of those capabilities, so you should read the manual.
This tutorial can be discontinued at any time by pressing the Break button;
under Unix(console), type q.
This will cause Stata to terminate the tutorial and Stata will await your
next command.
If you are a Unix(console) user, you will not be able to view the graphs.
Graphic styles
--------------
Stata provides eight graphic styles, known as
twoway meaning two-way scatterplots
matrix meaning two-way scatterplot matrices
histogram meaning histograms
oneway meaning one-way scatterplots
box meaning box-and-whisker plots
star meaning star charts
bar meaning bar charts
pie meaning pie charts
Please type y or n in the Command window:
Would you like to see examples of each? (y/n) . y
(Press the Space Bar when you see --more-- in this window)
Would you like to see them again? (y/n) . n
Enough preliminary
------------------
-------------------------------------------------------------------------------
To teach you how to use Stata's graphics capabilities, we will use the auto-
mobile data that we used in the introduction. Remember that these data are
stored in the file 'auto.dta':
-------------------------------------------------------------------------------
. use "C:\Stata/auto", clear
(1978 Automobile Data)
-------------------------------------------------------------------------------
We will begin with the two-way scatterplot, plotting miles per gallon against
engine displacement:
-------------------------------------------------------------------------------
. graph mpg displacement
-------------------------------------------------------------------------------
Stata will allow us to manipulate the basic image and add labeling, grid lines,
and titles. Let's ask Stata to label the axes:
-------------------------------------------------------------------------------
. graph mpg displacement, xlabel ylabel
-------------------------------------------------------------------------------
We'll get to grid lines and titles in a moment, but first we'll show you how to
vary the text size. The Stata parameter textsize says how big the characters
are supposed to be. Its default value is 100, which means 100% of what Stata
thinks looks good. Let's redraw our last image varying the textsize:
-------------------------------------------------------------------------------
. set textsize 200
. graph mpg displacement, xlabel ylabel
. set textsize 125
. graph mpg displacement, xlabel ylabel
. set textsize 75
. graph mpg displacement, xlabel ylabel
-------------------------------------------------------------------------------
You get the idea. We're not going to play with textsize again, but you may
want to. We'll set it back to the default 100:
-------------------------------------------------------------------------------
. set textsize 100
-------------------------------------------------------------------------------
Now let's return to adding titles and grid lines. There are two titles on
every side of the graph, called t1title, t2title, b1title, b2title, l1title,
l2title, r1title, and r2title. The 't', 'b', 'l', and 'r' stand for top,
bottom, left, and right. The b1title is also known as simply the title.
Here's a graph showing where all the titles are:
-------------------------------------------------------------------------------
. graph mpg displacement, t1title(This is the t1title)
t2title(This is the t2title)
b1title(This is the b1title also known as title)
b2title(This is the b2title)
r1title(This is the r1title)
r2title(This is the r2title)
l1title(This is the l1title)
l2title(This is the l2title)
--Break--
--Break--
r(1);
. exit, clear