234.ANALYZING DIFFERENT TYPES OF NEEM TREES USING PROC PRINT | PROC SORT | PROC MEANS | PROC FREQ | PROC UNIVARIATE | PROC SQL | PROC TRANSPOSE | PROC TABULATE | PROC REPORT | MACROS | FUNCTIONS | FORMATS IN SAS

ANALYZING DIFFERENT TYPES OF NEEM TREES USING PROC PRINT | PROC SORT | PROC MEANS | PROC FREQ | PROC UNIVARIATE | PROC SQL | PROC TRANSPOSE | PROC TABULATE | PROC REPORT | MACROS | FUNCTIONS | FORMATS IN SAS

/*Creating A Dataset Of Different Types of Neem Trees*/

1.SAS OPTIONS and FORMATS

options nocenter nodate nonumber formchar='|----|+|---+=';


proc format;

  value originfmt

    1 = "India"

    2 = "Sri Lanka"

    3 = "Pakistan"

    4 = "Bangladesh"

    5 = "Myanmar"

    6 = "Thailand"

    7 = "Africa"

    8 = "Australia"

    9 = "Indonesia";

  

  value usefmt

    1 = "Medicinal"

    2 = "Cosmetic"

    3 = "Agriculture"

    4 = "Timber"

    5 = "Pesticide"

    6 = "Ayurvedic"

    7 = "Spiritual";


run;


2.Create Dataset: Neem_Trees

data Neem_Trees;

  length TreeID 8 Name $20 Scientific_Name $30;

  infile datalines dsd truncover;

  input TreeID Name :$20. Scientific_Name :$30. Age_Years Height_m Yield_kg Origin

        Uses Max_Temp_Tol Min_Temp_Tol;

  format Origin originfmt. Uses usefmt.;

datalines;

1,Indian_Neem,Azadirachta_indica,35,15.2,32,1,1,48,5

2,Thai_Neem,Azadirachta_siamensis,25,12.5,28,6,1,42,10

3,African_Neem,Azadirachta_africana,40,16.0,35,7,3,50,8

4,Small_Neem,Azadirachta_minor,20,8.5,12,1,6,40,4

5,Bitter_Neem,Azadirachta_bittera,15,7.0,8,3,2,38,6

6,Wild_Neem,Azadirachta_wilda,22,10.0,15,2,4,45,7

7,Temple_Neem,Azadirachta_templi,30,14.0,20,1,7,44,5

8,Herbal_Neem,Azadirachta_herbalis,28,13.0,25,5,6,43,6

9,Rainy_Neem,Azadirachta_rainica,18,9.0,18,9,3,46,9

10,Bushy_Neem,Azadirachta_bushia,26,11.0,22,2,5,42,6

11,Giant_Neem,Azadirachta_giganta,42,17.5,40,1,4,49,7

12,Hill_Neem,Azadirachta_hilltop,20,10.0,16,8,1,41,5

13,Coastal_Neem,Azadirachta_coasta,21,9.5,19,9,3,44,6

14,Fertile_Neem,Azadirachta_fertila,27,13.5,29,1,2,45,8

15,Desert_Neem,Azadirachta_desserta,17,7.8,13,7,1,48,10

16,Red_Leaf_Neem,Azadirachta_rubra,25,12.0,24,1,2,43,6

17,Mountain_Neem,Azadirachta_montis,29,12.8,26,8,6,40,4

18,Riverbank_Neem,Azadirachta_flumina,22,9.2,14,1,3,41,5

19,Medicinal_Neem,Azadirachta_medica,31,15.0,33,5,1,46,5

20,Sacred_Neem,Azadirachta_sacra,35,14.8,31,1,7,44,6

21,Asian_Neem,Azadirachta_asiana,24,11.5,23,2,5,42,5

22,Windy_Neem,Azadirachta_winda,26,12.3,27,6,4,45,6

23,Urban_Neem,Azadirachta_urbana,20,9.0,16,1,2,39,7

24,Cold_Resist_Neem,Azadirachta_chilla,30,13.0,30,4,1,40,2

25,High_Altitude_Neem,Azadirachta_altia,33,14.0,34,8,1,38,3

26,Eastern_Neem,Azadirachta_eastera,27,13.2,28,3,6,46,6

27,Dryland_Neem,Azadirachta_arida,22,9.8,17,7,1,47,5

;

run;

proc print data=Neem_Trees; run;

Output:

Obs TreeID Name Scientific_Name Age_Years Height_m Yield_kg Origin Uses Max_Temp_Tol Min_Temp_Tol
1 1 Indian_Neem Azadirachta_indica 35 15.2 32 India Medicinal 48 5
2 2 Thai_Neem Azadirachta_siamensis 25 12.5 28 Thailand Medicinal 42 10
3 3 African_Neem Azadirachta_africana 40 16.0 35 Africa Agriculture 50 8
4 4 Small_Neem Azadirachta_minor 20 8.5 12 India Ayurvedic 40 4
5 5 Bitter_Neem Azadirachta_bittera 15 7.0 8 Pakistan Cosmetic 38 6
6 6 Wild_Neem Azadirachta_wilda 22 10.0 15 Sri Lanka Timber 45 7
7 7 Temple_Neem Azadirachta_templi 30 14.0 20 India Spiritual 44 5
8 8 Herbal_Neem Azadirachta_herbalis 28 13.0 25 Myanmar Ayurvedic 43 6
9 9 Rainy_Neem Azadirachta_rainica 18 9.0 18 Indonesia Agriculture 46 9
10 10 Bushy_Neem Azadirachta_bushia 26 11.0 22 Sri Lanka Pesticide 42 6
11 11 Giant_Neem Azadirachta_giganta 42 17.5 40 India Timber 49 7
12 12 Hill_Neem Azadirachta_hilltop 20 10.0 16 Australia Medicinal 41 5
13 13 Coastal_Neem Azadirachta_coasta 21 9.5 19 Indonesia Agriculture 44 6
14 14 Fertile_Neem Azadirachta_fertila 27 13.5 29 India Cosmetic 45 8
15 15 Desert_Neem Azadirachta_desserta 17 7.8 13 Africa Medicinal 48 10
16 16 Red_Leaf_Neem Azadirachta_rubra 25 12.0 24 India Cosmetic 43 6
17 17 Mountain_Neem Azadirachta_montis 29 12.8 26 Australia Ayurvedic 40 4
18 18 Riverbank_Neem Azadirachta_flumina 22 9.2 14 India Agriculture 41 5
19 19 Medicinal_Neem Azadirachta_medica 31 15.0 33 Myanmar Medicinal 46 5
20 20 Sacred_Neem Azadirachta_sacra 35 14.8 31 India Spiritual 44 6
21 21 Asian_Neem Azadirachta_asiana 24 11.5 23 Sri Lanka Pesticide 42 5
22 22 Windy_Neem Azadirachta_winda 26 12.3 27 Thailand Timber 45 6
23 23 Urban_Neem Azadirachta_urbana 20 9.0 16 India Cosmetic 39 7
24 24 Cold_Resist_Neem Azadirachta_chilla 30 13.0 30 Bangladesh Medicinal 40 2
25 25 High_Altitude_Neem Azadirachta_altia 33 14.0 34 Australia Medicinal 38 3
26 26 Eastern_Neem Azadirachta_eastera 27 13.2 28 Pakistan Ayurvedic 46 6
27 27 Dryland_Neem Azadirachta_arida 22 9.8 17 Africa Medicinal 47 5


3.Exploring Dataset with PROC PRINT

proc print data=Neem_Trees (obs=10) label;

  title "First 10 Observations of Neem_Trees Dataset";

  var TreeID Name Scientific_Name Origin Uses Age_Years Height_m Yield_kg;

run;

Output:

First 10 Observations of Neem_Trees Dataset

Obs TreeID Name Scientific_Name Origin Uses Age_Years Height_m Yield_kg
1 1 Indian_Neem Azadirachta_indica India Medicinal 35 15.2 32
2 2 Thai_Neem Azadirachta_siamensis Thailand Medicinal 25 12.5 28
3 3 African_Neem Azadirachta_africana Africa Agriculture 40 16.0 35
4 4 Small_Neem Azadirachta_minor India Ayurvedic 20 8.5 12
5 5 Bitter_Neem Azadirachta_bittera Pakistan Cosmetic 15 7.0 8
6 6 Wild_Neem Azadirachta_wilda Sri Lanka Timber 22 10.0 15
7 7 Temple_Neem Azadirachta_templi India Spiritual 30 14.0 20
8 8 Herbal_Neem Azadirachta_herbalis Myanmar Ayurvedic 28 13.0 25
9 9 Rainy_Neem Azadirachta_rainica Indonesia Agriculture 18 9.0 18
10 10 Bushy_Neem Azadirachta_bushia Sri Lanka Pesticide 26 11.0 22


4.Descriptive Statistics with PROC MEANS

proc means data=Neem_Trees n mean min max std;

  var Age_Years Height_m Yield_kg Max_Temp_Tol Min_Temp_Tol;

  title "Descriptive Statistics of Neem Trees";

run;

Output:

Descriptive Statistics of Neem Trees

The MEANS Procedure

Variable N Mean Minimum Maximum Std Dev
Age_Years
Height_m
Yield_kg
Max_Temp_Tol
Min_Temp_Tol
27
27
27
27
27
26.2962963
11.8925926
23.5185185
43.5555556
6.0000000
15.0000000
7.0000000
8.0000000
38.0000000
2.0000000
42.0000000
17.5000000
40.0000000
50.0000000
10.0000000
6.7528616
2.6944281
8.1635700
3.3320510
1.8810799


5.PROC FREQ: Frequency of Origins and Uses

proc freq data=Neem_Trees;

  tables Origin Uses;

  title "Frequency of Origin and Uses";

run;

Output:

Frequency of Origin and Uses

The FREQ Procedure

Origin Frequency Percent Cumulative
Frequency
Cumulative
Percent
India 9 33.33 9 33.33
Sri Lanka 3 11.11 12 44.44
Pakistan 2 7.41 14 51.85
Bangladesh 1 3.70 15 55.56
Myanmar 2 7.41 17 62.96
Thailand 2 7.41 19 70.37
Africa 3 11.11 22 81.48
Australia 3 11.11 25 92.59
Indonesia 2 7.41 27 100.00


Uses Frequency Percent Cumulative
Frequency
Cumulative
Percent
Medicinal 8 29.63 8 29.63
Cosmetic 4 14.81 12 44.44
Agriculture 4 14.81 16 59.26
Timber 3 11.11 19 70.37
Pesticide 2 7.41 21 77.78
Ayurvedic 4 14.81 25 92.59
Spiritual 2 7.41 27 100.00


6.PROC UNIVARIATE: Detailed Stats on Yield

proc univariate data=Neem_Trees;

  var Yield_kg;

  histogram Yield_kg;

  title "Distribution of Yield in kg";

run;

Output:

Distribution of Yield in kg

The UNIVARIATE Procedure
Variable: Yield_kg

Moments
N 27 Sum Weights 27
Mean 23.5185185 Sum Observations 635
Std Deviation 8.16356997 Variance 66.6438746
Skewness 0.02724644 Kurtosis -0.8234518
Uncorrected SS 16667 Corrected SS 1732.74074
Coeff Variation 34.7112424 Std Error Mean 1.57107977


Basic Statistical Measures
Location Variability
Mean 23.51852 Std Deviation 8.16357
Median 24.00000 Variance 66.64387
Mode 16.00000 Range 32.00000
    Interquartile Range 14.00000

Note: The mode displayed is the smallest of 2 modes with a count of 2.


Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 14.96965 Pr > |t| <.0001
Sign M 13.5 Pr >= |M| <.0001
Signed Rank S 189 Pr >= |S| <.0001


Quantiles (Definition 5)
Level Quantile
100% Max 40
99% 40
95% 35
90% 34
75% Q3 30
50% Median 24
25% Q1 16
10% 13
5% 12
1% 8
0% Min 8


Extreme Observations
Lowest Highest
Value Obs Value Obs
8 5 32 1
12 4 33 19
13 15 34 25
14 18 35 3
15 6 40 11

7.PROC SORT + PROC PRINT: Tallest Trees

proc sort data=Neem_Trees out=Sorted_Height;

  by descending Height_m;

run;


proc print data=Sorted_Height (obs=5);

  title "Top 5 Tallest Neem Trees";

run;

Output:

Top 5 Tallest Neem Trees

Obs TreeID Name Scientific_Name Age_Years Height_m Yield_kg Origin Uses Max_Temp_Tol Min_Temp_Tol
1 11 Giant_Neem Azadirachta_giganta 42 17.5 40 India Timber 49 7
2 3 African_Neem Azadirachta_africana 40 16.0 35 Africa Agriculture 50 8
3 1 Indian_Neem Azadirachta_indica 35 15.2 32 India Medicinal 48 5
4 19 Medicinal_Neem Azadirachta_medica 31 15.0 33 Myanmar Medicinal 46 5
5 20 Sacred_Neem Azadirachta_sacra 35 14.8 31 India Spiritual 44 6


8.PROC SQL: Neem Trees Above Avg Yield

proc sql;

  select Name, Age_Years, Height_m, Yield_kg

  from Neem_Trees

  where Yield_kg > (select avg(Yield_kg) from Neem_Trees);

quit;

Output:

Name Age_Years Height_m Yield_kg
Indian_Neem 35 15.2 32
Thai_Neem 25 12.5 28
African_Neem 40 16 35
Herbal_Neem 28 13 25
Giant_Neem 42 17.5 40
Fertile_Neem 27 13.5 29
Red_Leaf_Neem 25 12 24
Mountain_Neem 29 12.8 26
Medicinal_Neem 31 15 33
Sacred_Neem 35 14.8 31
Windy_Neem 26 12.3 27
Cold_Resist_Neem 30 13 30
High_Altitude_Neem 33 14 34
Eastern_Neem 27 13.2 28


9.PROC TRANSPOSE: Reshape Data

proc transpose data=Neem_Trees out=Neem_Transposed;

  var Age_Years Height_m Yield_kg;

  id Name;

run;

proc print;run;

Output:

Obs _NAME_ Indian_Neem Thai_Neem African_Neem Small_Neem Bitter_Neem Wild_Neem Temple_Neem Herbal_Neem Rainy_Neem Bushy_Neem Giant_Neem Hill_Neem Coastal_Neem Fertile_Neem Desert_Neem Red_Leaf_Neem Mountain_Neem Riverbank_Neem Medicinal_Neem Sacred_Neem Asian_Neem Windy_Neem Urban_Neem Cold_Resist_Neem High_Altitude_Neem Eastern_Neem Dryland_Neem
1 Age_Years 35.0 25.0 40 20.0 15 22 30 28 18 26 42.0 20 21.0 27.0 17.0 25 29.0 22.0 31 35.0 24.0 26.0 20 30 33 27.0 22.0
2 Height_m 15.2 12.5 16 8.5 7 10 14 13 9 11 17.5 10 9.5 13.5 7.8 12 12.8 9.2 15 14.8 11.5 12.3 9 13 14 13.2 9.8
3 Yield_kg 32.0 28.0 35 12.0 8 15 20 25 18 22 40.0 16 19.0 29.0 13.0 24 26.0 14.0 33 31.0 23.0 27.0 16 30 34 28.0 17.0


10.PROC TABULATE: Cross Tab

proc tabulate data=Neem_Trees;

  class Origin Uses;

  var Height_m Yield_kg;

  table Origin, Uses*(Height_m Yield_kg)*(mean std);

  title "Cross-tabulation of Height and Yield by Origin and Uses";

run;

Output:

Cross-tabulation of Height and Yield by Origin and Uses

  Uses
Medicinal Cosmetic Agriculture Timber Pesticide Ayurvedic Spiritual
Height_m Yield_kg Height_m Yield_kg Height_m Yield_kg Height_m Yield_kg Height_m Yield_kg Height_m Yield_kg Height_m Yield_kg
Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std Mean Std
Origin 15.20 . 32.00 . 11.50 2.29 23.00 6.56 9.20 . 14.00 . 17.50 . 40.00 . . . . . 8.50 . 12.00 . 14.40 0.57 25.50 7.78
India
Sri Lanka . . . . . . . . . . . . 10.00 . 15.00 . 11.25 0.35 22.50 0.71 . . . . . . . .
Pakistan . . . . 7.00 . 8.00 . . . . . . . . . . . . . 13.20 . 28.00 . . . . .
Bangladesh 13.00 . 30.00 . . . . . . . . . . . . . . . . . . . . . . . . .
Myanmar 15.00 . 33.00 . . . . . . . . . . . . . . . . . 13.00 . 25.00 . . . . .
Thailand 12.50 . 28.00 . . . . . . . . . 12.30 . 27.00 . . . . . . . . . . . . .
Africa 8.80 1.41 15.00 2.83 . . . . 16.00 . 35.00 . . . . . . . . . . . . . . . . .
Australia 12.00 2.83 25.00 12.73 . . . . . . . . . . . . . . . . 12.80 . 26.00 . . . . .
Indonesia . . . . . . . . 9.25 0.35 18.50 0.71 . . . . . . . . . . . . . . . .


11.PROC REPORT: Grouped View

proc report data=Neem_Trees nowd;

  column Origin Uses Height_m Yield_kg;

  define Origin / group format=originfmt.;

  define Uses / group format=usefmt.;

  define Height_m / analysis mean;

  define Yield_kg / analysis sum;

  title "Grouped Summary Report";

run;

Output:

Grouped Summary Report

Origin Uses Height_m Yield_kg
Africa Agriculture 16 35
  Medicinal 8.8 30
Australia Ayurvedic 12.8 26
  Medicinal 12 50
Bangladesh Medicinal 13 30
India Agriculture 9.2 14
  Ayurvedic 8.5 12
  Cosmetic 11.5 69
  Medicinal 15.2 32
  Spiritual 14.4 51
  Timber 17.5 40
Indonesia Agriculture 9.25 37
Myanmar Ayurvedic 13 25
  Medicinal 15 33
Pakistan Ayurvedic 13.2 28
  Cosmetic 7 8
Sri Lanka Pesticide 11.25 45
  Timber 10 15
Thailand Medicinal 12.5 28
  Timber 12.3 27


12.MACRO: Report for Trees Tolerating High Heat

%macro highheat(thresh);

  proc sql;

    title "Neem Trees Tolerating Temperature Above &thresh °C";

    select TreeID, Name, Max_Temp_Tol

    from Neem_Trees

    where Max_Temp_Tol > &thresh;

  quit;

%mend highheat;


%highheat(45);

Output:

Neem Trees Tolerating Temperature Above 45 °C

TreeID Name Max_Temp_Tol
1 Indian_Neem 48
3 African_Neem 50
9 Rainy_Neem 46
11 Giant_Neem 49
15 Desert_Neem 48
19 Medicinal_Neem 46
26 Eastern_Neem 46
27 Dryland_Neem 47


13.MACRO: Yield Classification

%macro classify_yield;

  data Neem_Trees_Classified;

    set Neem_Trees;

    length Yield_Category $10;

    if Yield_kg < 20 then Yield_Category = "Low";

    else if Yield_kg <= 30 then Yield_Category = "Medium";

    else Yield_Category = "High";

  run;

  proc print;run;


  proc freq data=Neem_Trees_Classified;

    tables Yield_Category;

    title "Yield Classification of Neem Trees";

  run;

%mend classify_yield;


%classify_yield;

Output:

Obs TreeID Name Scientific_Name Age_Years Height_m Yield_kg Origin Uses Max_Temp_Tol Min_Temp_Tol Yield_Category
1 1 Indian_Neem Azadirachta_indica 35 15.2 32 India Medicinal 48 5 High
2 2 Thai_Neem Azadirachta_siamensis 25 12.5 28 Thailand Medicinal 42 10 Medium
3 3 African_Neem Azadirachta_africana 40 16.0 35 Africa Agriculture 50 8 High
4 4 Small_Neem Azadirachta_minor 20 8.5 12 India Ayurvedic 40 4 Low
5 5 Bitter_Neem Azadirachta_bittera 15 7.0 8 Pakistan Cosmetic 38 6 Low
6 6 Wild_Neem Azadirachta_wilda 22 10.0 15 Sri Lanka Timber 45 7 Low
7 7 Temple_Neem Azadirachta_templi 30 14.0 20 India Spiritual 44 5 Medium
8 8 Herbal_Neem Azadirachta_herbalis 28 13.0 25 Myanmar Ayurvedic 43 6 Medium
9 9 Rainy_Neem Azadirachta_rainica 18 9.0 18 Indonesia Agriculture 46 9 Low
10 10 Bushy_Neem Azadirachta_bushia 26 11.0 22 Sri Lanka Pesticide 42 6 Medium
11 11 Giant_Neem Azadirachta_giganta 42 17.5 40 India Timber 49 7 High
12 12 Hill_Neem Azadirachta_hilltop 20 10.0 16 Australia Medicinal 41 5 Low
13 13 Coastal_Neem Azadirachta_coasta 21 9.5 19 Indonesia Agriculture 44 6 Low
14 14 Fertile_Neem Azadirachta_fertila 27 13.5 29 India Cosmetic 45 8 Medium
15 15 Desert_Neem Azadirachta_desserta 17 7.8 13 Africa Medicinal 48 10 Low
16 16 Red_Leaf_Neem Azadirachta_rubra 25 12.0 24 India Cosmetic 43 6 Medium
17 17 Mountain_Neem Azadirachta_montis 29 12.8 26 Australia Ayurvedic 40 4 Medium
18 18 Riverbank_Neem Azadirachta_flumina 22 9.2 14 India Agriculture 41 5 Low
19 19 Medicinal_Neem Azadirachta_medica 31 15.0 33 Myanmar Medicinal 46 5 High
20 20 Sacred_Neem Azadirachta_sacra 35 14.8 31 India Spiritual 44 6 High
21 21 Asian_Neem Azadirachta_asiana 24 11.5 23 Sri Lanka Pesticide 42 5 Medium
22 22 Windy_Neem Azadirachta_winda 26 12.3 27 Thailand Timber 45 6 Medium
23 23 Urban_Neem Azadirachta_urbana 20 9.0 16 India Cosmetic 39 7 Low
24 24 Cold_Resist_Neem Azadirachta_chilla 30 13.0 30 Bangladesh Medicinal 40 2 Medium
25 25 High_Altitude_Neem Azadirachta_altia 33 14.0 34 Australia Medicinal 38 3 High
26 26 Eastern_Neem Azadirachta_eastera 27 13.2 28 Pakistan Ayurvedic 46 6 Medium
27 27 Dryland_Neem Azadirachta_arida 22 9.8 17 Africa Medicinal 47 5 Low

Yield Classification of Neem Trees

The FREQ Procedure

Yield_Category Frequency Percent Cumulative
Frequency
Cumulative
Percent
High 6 22.22 6 22.22
Low 10 37.04 16 59.26
Medium 11 40.74 27 100.00

14.Function Usage Example

data Neem_Trees_Modified;

  set Neem_Trees;

  Tree_Code = substr(Name,1,3) || put(TreeID,z2.);

  Temp_Range = Max_Temp_Tol - Min_Temp_Tol;

run;

proc print;run;

Output:

Obs TreeID Name Scientific_Name Age_Years Height_m Yield_kg Origin Uses Max_Temp_Tol Min_Temp_Tol Tree_Code Temp_Range
1 1 Indian_Neem Azadirachta_indica 35 15.2 32 India Medicinal 48 5 Ind01 43
2 2 Thai_Neem Azadirachta_siamensis 25 12.5 28 Thailand Medicinal 42 10 Tha02 32
3 3 African_Neem Azadirachta_africana 40 16.0 35 Africa Agriculture 50 8 Afr03 42
4 4 Small_Neem Azadirachta_minor 20 8.5 12 India Ayurvedic 40 4 Sma04 36
5 5 Bitter_Neem Azadirachta_bittera 15 7.0 8 Pakistan Cosmetic 38 6 Bit05 32
6 6 Wild_Neem Azadirachta_wilda 22 10.0 15 Sri Lanka Timber 45 7 Wil06 38
7 7 Temple_Neem Azadirachta_templi 30 14.0 20 India Spiritual 44 5 Tem07 39
8 8 Herbal_Neem Azadirachta_herbalis 28 13.0 25 Myanmar Ayurvedic 43 6 Her08 37
9 9 Rainy_Neem Azadirachta_rainica 18 9.0 18 Indonesia Agriculture 46 9 Rai09 37
10 10 Bushy_Neem Azadirachta_bushia 26 11.0 22 Sri Lanka Pesticide 42 6 Bus10 36
11 11 Giant_Neem Azadirachta_giganta 42 17.5 40 India Timber 49 7 Gia11 42
12 12 Hill_Neem Azadirachta_hilltop 20 10.0 16 Australia Medicinal 41 5 Hil12 36
13 13 Coastal_Neem Azadirachta_coasta 21 9.5 19 Indonesia Agriculture 44 6 Coa13 38
14 14 Fertile_Neem Azadirachta_fertila 27 13.5 29 India Cosmetic 45 8 Fer14 37
15 15 Desert_Neem Azadirachta_desserta 17 7.8 13 Africa Medicinal 48 10 Des15 38
16 16 Red_Leaf_Neem Azadirachta_rubra 25 12.0 24 India Cosmetic 43 6 Red16 37
17 17 Mountain_Neem Azadirachta_montis 29 12.8 26 Australia Ayurvedic 40 4 Mou17 36
18 18 Riverbank_Neem Azadirachta_flumina 22 9.2 14 India Agriculture 41 5 Riv18 36
19 19 Medicinal_Neem Azadirachta_medica 31 15.0 33 Myanmar Medicinal 46 5 Med19 41
20 20 Sacred_Neem Azadirachta_sacra 35 14.8 31 India Spiritual 44 6 Sac20 38
21 21 Asian_Neem Azadirachta_asiana 24 11.5 23 Sri Lanka Pesticide 42 5 Asi21 37
22 22 Windy_Neem Azadirachta_winda 26 12.3 27 Thailand Timber 45 6 Win22 39
23 23 Urban_Neem Azadirachta_urbana 20 9.0 16 India Cosmetic 39 7 Urb23 32
24 24 Cold_Resist_Neem Azadirachta_chilla 30 13.0 30 Bangladesh Medicinal 40 2 Col24 38
25 25 High_Altitude_Neem Azadirachta_altia 33 14.0 34 Australia Medicinal 38 3 Hig25 35
26 26 Eastern_Neem Azadirachta_eastera 27 13.2 28 Pakistan Ayurvedic 46 6 Eas26 40
27 27 Dryland_Neem Azadirachta_arida 22 9.8 17 Africa Medicinal 47 5 Dry27 42


15.SQL Join Example: Creating a Lookup Table

data Region_Info;

  input Origin Lookup_Region $15.;

datalines;

1 South_Asia

2 South_Asia

3 South_Asia

4 South_Asia

5 SE_Asia

6 SE_Asia

7 Africa

8 Australia

9 SE_Asia

;

run;

proc print;run;

Output:

Obs Origin Lookup_Region
1 1 South_Asia
2 2 South_Asia
3 3 South_Asia
4 4 South_Asia
5 5 SE_Asia
6 6 SE_Asia
7 7 Africa
8 8 Australia
9 9 SE_Asia


proc sql;

  create table Neem_With_Region as

  select a.*, b.Lookup_Region

  from Neem_Trees a left join Region_Info b

  on a.Origin = b.Origin;

quit;


proc print data=Neem_With_Region (obs=5);

  title "Joined Neem Tree Dataset with Region Info";

run;

Output:
Joined Neem Tree Dataset with Region Info

Obs TreeID Name Scientific_Name Age_Years Height_m Yield_kg Origin Uses Max_Temp_Tol Min_Temp_Tol Lookup_Region
1 23 Urban_Neem Azadirachta_urbana 20 9.0 16 India Cosmetic 39 7 South_Asia
2 7 Temple_Neem Azadirachta_templi 30 14.0 20 India Spiritual 44 5 South_Asia
3 20 Sacred_Neem Azadirachta_sacra 35 14.8 31 India Spiritual 44 6 South_Asia
4 14 Fertile_Neem Azadirachta_fertila 27 13.5 29 India Cosmetic 45 8 South_Asia
5 18 Riverbank_Neem Azadirachta_flumina 22 9.2 14 India Agriculture 41 5 South_Asia






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