370.ASTRONAUT PERFORMANCE & SPACE MISSION ANALYTICS USING SAS

ASTRONAUT PERFORMANCE & SPACE MISSION ANALYTICS USING SAS

HERE IN THIS PROJECT WE USED THESE SAS STATEMENTS --PROC SQL | PROC MEANS | PROC SORT | PROC SGPLOT | MACROS | MDY | INTNX | INTCK | MERGE | APPEND | SET | TRANSPOSE

1. Why Astronaut Data Analytics Matters

Modern space agencies such as NASA, ESA, ISRO, Roscosmos and SpaceX manage billions of dollars of missions.

Each astronaut is a high-value human asset. Their:

• Mission count
• Space exposure
• Age
• Success rate
• Fatigue
• Flight history

must be continuously analyzed to ensure:

1. Crew safety
2. Optimal mission selection
3. Training effectiveness
4. Mission success

SAS is used in aerospace organizations because it can:

• Merge flight logs
• Calculate exposure time
• Rank crew members
• Predict performance
• Create mission dashboards

This project simulates how NASA or ISRO would track astronaut performance using SAS.

2. Creating Astronaut Master Dataset

This Astronaut Analytics project is not just about space data. It is a complete enterprise-level SAS training model that teaches how real organizations (NASA, ISRO, SpaceX, ESA) analyze human performance, operational risk, and mission efficiency using SAS.

You are learning how raw data becomes management decisions.

data astronauts_raw;

    format First_Mission Last_Mission date9.;

    input Name $ Country $ Missions Total_Hours_in_Space Age Success_Rate First_Mission :date9. Last_Mission :date9.;

    datalines;

John_USA USA 6 1240 45 92 01JAN2010 15DEC2024

Maria_RUS Russia 7 1400 48 95 10FEB2008 20NOV2024

Ravi_IND India 4 800 38 88 05MAR2015 01JUN2024

Li_CHN China 5 900 40 90 20APR2013 10OCT2024

Akira_JPN Japan 3 620 36 85 11MAY2017 15AUG2024

Tom_USA USA 8 1600 50 97 01JAN2005 30DEC2024

Elena_RUS Russia 6 1300 46 93 01JUN2011 20DEC2024

Ahmed_UAE UAE 2 300 34 80 10MAR2021 05APR2024

Paul_FRA France 4 700 39 87 12JUL2016 01SEP2024

Mark_USA USA 5 1000 42 90 02FEB2014 18DEC2024

Sun_CHN China 6 1200 44 94 01JAN2012 22DEC2024

Anita_IND India 3 500 35 82 15JUN2018 30SEP2024

Leo_ITA Italy 4 750 41 89 10APR2016 10OCT2024

Carlos_ESP Spain 3 620 37 86 01MAR2017 12SEP2024

James_USA USA 7 1450 49 96 01JAN2007 31DEC2024

Ivan_RUS Russia 5 1100 43 91 01APR2012 15NOV2024

;

run;

proc print data=astronauts_raw;

run;

OUTPUT:

Obs	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate
1	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92
2	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95
3	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88
4	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90
5	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85
6	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97
7	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93
8	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80
9	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87
10	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90
11	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94
12	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82
13	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89
14	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86
15	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96
16	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91

3. Creating Space Exposure Dates using INTNX & MDY

data astronauts_dates;

    set astronauts_raw;

    Mission_Start = intnx('month', First_Mission, 0, 'b');

    Mission_End   = intnx('month', Last_Mission, 0, 'e');

    Mission_Year  = year(First_Mission);

    format Mission_Start Mission_End date9.;

run;

proc print data=astronauts_dates;

run;

OUTPUT:

Obs	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year
1	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010
2	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008
3	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015
4	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013
5	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017
6	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005
7	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011
8	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021
9	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016
10	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014
11	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012
12	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018
13	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016
14	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017
15	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007
16	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012

4. Experience Duration Using INTCK

data astronauts_exp;

    set astronauts_dates;

    Years_of_Service = intck('year', First_Mission, Last_Mission);

run;

proc print data=astronauts_exp;

run;

OUTPUT:

Obs	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service
1	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14
2	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16
3	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9
4	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11
5	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7
6	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19
7	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13
8	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3
9	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8
10	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10
11	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12
12	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6
13	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8
14	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7
15	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17
16	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12

5. Macro for Performance Classification

%macro classify;

data astronauts_ranked;

    set astronauts_exp;

    if Success_Rate >= 95 then Success_Level = "ELITE";

    else if Success_Rate >= 90 then Success_Level = "HIGH";

    else if Success_Rate >= 85 then Success_Level = "MEDIUM";

    else Success_Level = "LOW";

run;

proc print data=astronauts_ranked;

run;

%mend;

%classify;

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service
1	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14
2	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16
3	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9
4	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11
5	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7
6	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19
7	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13
8	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3
9	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8
10	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10
11	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12
12	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6
13	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8
14	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7
15	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17
16	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12

6. Sorting Astronauts by Space Hours

proc sort data=astronauts_ranked out=astronauts_sorted;

    by descending Total_Hours_in_Space;

run;

proc print data=astronauts_sorted;

run;

Space agencies always want the most experienced astronauts at the top.

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service
1	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19
2	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17
3	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16
4	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13
5	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14
6	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12
7	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12
8	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10
9	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11
10	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9
11	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8
12	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8
13	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7
14	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7
15	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6
16	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3

7. PROC SQL – Mission Analytics

proc sql;

    create table country_stats as

    select Country,

           count(Name) as Astronauts,

           avg(Total_Hours_in_Space) as Avg_Hours,

           avg(Success_Rate) as Avg_Success

    from astronauts_sorted

    group by Country;

quit;

proc print data=country_stats;

run;

This shows how each country performs in space.

OUTPUT:

Obs	Country	Astronauts	Avg_Hours	Avg_Success
1	China	2	1050.00	92.00
2	France	1	700.00	87.00
3	India	2	650.00	85.00
4	Italy	1	750.00	89.00
5	Japan	1	620.00	85.00
6	Russia	3	1266.67	93.00
7	Spain	1	620.00	86.00
8	UAE	1	300.00	80.00
9	USA	4	1322.50	93.75

8. PROC MEANS – Performance Summary

proc means data=astronauts_sorted mean min max;

    var Total_Hours_in_Space Missions Age Success_Rate;

run;

OUTPUT:

The MEANS Procedure

Variable	Mean	Minimum	Maximum
Total_Hours_in_Space Missions Age Success_Rate	967.5000000 4.8750000 41.6875000 89.6875000	300.0000000 2.0000000 34.0000000 80.0000000	1600.00 8.0000000 50.0000000 97.0000000

NASA would use this to track:

·       Crew fatigue

·       Average experience knowing

·       Age distributions

9. PROC SGPLOT – Visual Performance Dashboard

proc sgplot data=astronauts_sorted;

    vbar Name / response=Total_Hours_in_Space;

    title "Astronaut Space Experience Comparison";

run;

OUTPUT:

proc sgplot data=astronauts_sorted;

    scatter x=Age y=Success_Rate;

    title "Age vs Mission Success";

run;

This helps identify optimal astronaut age vs performance.

OUTPUT:

10. TRANSPOSE – Convert Data for Reports

proc transpose data=astronauts_sorted out=hours_wide;

    id Name;

    var Total_Hours_in_Space;

run;

proc print data=hours_wide;

run;

Now every astronaut becomes a column for reporting.

OUTPUT:

Obs	_NAME_	Tom_USA	James_US	Maria_RU	Elena_RU	John_USA	Sun_CHN	Ivan_RUS	Mark_USA	Li_CHN	Ravi_IND	Leo_ITA	Paul_FRA	Akira_JP	Carlos_E	Anita_IN	Ahmed_UA
1	Total_Hours_in_Space	1600	1450	1400	1300	1240	1200	1100	1000	900	800	750	700	620	620	500	300

11. MERGE – Combine Country Statistics

proc sort data=astronauts_sorted; by Country; run;

proc print data=astronauts_sorted;

run;

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service
1	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12
2	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11
3	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8
4	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9
5	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6
6	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8
7	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7
8	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16
9	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13
10	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12
11	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7
12	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3
13	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19
14	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17
15	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14
16	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10

proc sort data=country_stats; by Country; run;

proc print data=country_stats;

run;

OUTPUT:

Obs	Country	Astronauts	Avg_Hours	Avg_Success
1	China	2	1050.00	92.00
2	France	1	700.00	87.00
3	India	2	650.00	85.00
4	Italy	1	750.00	89.00
5	Japan	1	620.00	85.00
6	Russia	3	1266.67	93.00
7	Spain	1	620.00	86.00
8	UAE	1	300.00	80.00
9	USA	4	1322.50	93.75

data final_astronauts;

    merge astronauts_sorted country_stats;

    by Country;

run;

proc print data=final_astronauts;

run;

Now every astronaut also carries national performance metrics.

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service	Astronauts	Avg_Hours	Avg_Success
1	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12	2	1050.00	92.00
2	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11	2	1050.00	92.00
3	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8	1	700.00	87.00
4	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9	2	650.00	85.00
5	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6	2	650.00	85.00
6	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8	1	750.00	89.00
7	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7	1	620.00	85.00
8	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16	3	1266.67	93.00
9	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13	3	1266.67	93.00
10	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12	3	1266.67	93.00
11	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7	1	620.00	86.00
12	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3	1	300.00	80.00
13	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19	4	1322.50	93.75
14	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17	4	1322.50	93.75
15	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14	4	1322.50	93.75
16	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10	4	1322.50	93.75

12. APPEND – Add New Astronauts

data new_astronaut;

    input Name $ Country $ Missions Total_Hours_in_Space Age Success_Rate;

    datalines;

Neil_USA USA 2 350 34 85

;

run;

proc print data=new_astronaut;

run;

OUTPUT:

Obs	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate
1	Neil_USA	USA	2	350	34	85

proc append base=final_astronauts 

            data=new_astronaut force;

run;

proc print data=final_astronauts;

run;

This simulates onboarding of new astronauts.

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service	Astronauts	Avg_Hours	Avg_Success
1	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12	2	1050.00	92.00
2	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11	2	1050.00	92.00
3	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8	1	700.00	87.00
4	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9	2	650.00	85.00
5	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6	2	650.00	85.00
6	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8	1	750.00	89.00
7	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7	1	620.00	85.00
8	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16	3	1266.67	93.00
9	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13	3	1266.67	93.00
10	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12	3	1266.67	93.00
11	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7	1	620.00	86.00
12	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3	1	300.00	80.00
13	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19	4	1322.50	93.75
14	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17	4	1322.50	93.75
15	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14	4	1322.50	93.75
16	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10	4	1322.50	93.75
17		.	.	Neil_USA	USA	2	350	34	85	.	.	.	.	.	.	.

13. SET – Combine Old and New Records

data all_astronauts;

    set final_astronauts

        new_astronaut;

run;

proc print data=all_astronauts;

run;

OUTPUT:

Obs	SUCCESS_LEVEL	First_Mission	Last_Mission	Name	Country	Missions	Total_Hours_in_Space	Age	Success_Rate	Mission_Start	Mission_End	Mission_Year	Years_of_Service	Astronauts	Avg_Hours	Avg_Success
1	HIGH	01JAN2012	22DEC2024	Sun_CHN	China	6	1200	44	94	01JAN2012	31DEC2024	2012	12	2	1050.00	92.00
2	HIGH	20APR2013	10OCT2024	Li_CHN	China	5	900	40	90	01APR2013	31OCT2024	2013	11	2	1050.00	92.00
3	MEDIUM	12JUL2016	01SEP2024	Paul_FRA	France	4	700	39	87	01JUL2016	30SEP2024	2016	8	1	700.00	87.00
4	MEDIUM	05MAR2015	01JUN2024	Ravi_IND	India	4	800	38	88	01MAR2015	30JUN2024	2015	9	2	650.00	85.00
5	LOW	15JUN2018	30SEP2024	Anita_IN	India	3	500	35	82	01JUN2018	30SEP2024	2018	6	2	650.00	85.00
6	MEDIUM	10APR2016	10OCT2024	Leo_ITA	Italy	4	750	41	89	01APR2016	31OCT2024	2016	8	1	750.00	89.00
7	MEDIUM	11MAY2017	15AUG2024	Akira_JP	Japan	3	620	36	85	01MAY2017	31AUG2024	2017	7	1	620.00	85.00
8	ELITE	10FEB2008	20NOV2024	Maria_RU	Russia	7	1400	48	95	01FEB2008	30NOV2024	2008	16	3	1266.67	93.00
9	HIGH	01JUN2011	20DEC2024	Elena_RU	Russia	6	1300	46	93	01JUN2011	31DEC2024	2011	13	3	1266.67	93.00
10	HIGH	01APR2012	15NOV2024	Ivan_RUS	Russia	5	1100	43	91	01APR2012	30NOV2024	2012	12	3	1266.67	93.00
11	MEDIUM	01MAR2017	12SEP2024	Carlos_E	Spain	3	620	37	86	01MAR2017	30SEP2024	2017	7	1	620.00	86.00
12	LOW	10MAR2021	05APR2024	Ahmed_UA	UAE	2	300	34	80	01MAR2021	30APR2024	2021	3	1	300.00	80.00
13	ELITE	01JAN2005	30DEC2024	Tom_USA	USA	8	1600	50	97	01JAN2005	31DEC2024	2005	19	4	1322.50	93.75
14	ELITE	01JAN2007	31DEC2024	James_US	USA	7	1450	49	96	01JAN2007	31DEC2024	2007	17	4	1322.50	93.75
15	HIGH	01JAN2010	15DEC2024	John_USA	USA	6	1240	45	92	01JAN2010	31DEC2024	2010	14	4	1322.50	93.75
16	HIGH	02FEB2014	18DEC2024	Mark_USA	USA	5	1000	42	90	01FEB2014	31DEC2024	2014	10	4	1322.50	93.75
17		.	.	Neil_USA	USA	2	350	34	85	.	.	.	.	.	.	.
18		.	.	Neil_USA	USA	2	350	34	85	.	.	.	.	.	.	.

 

14. What This Project Simulates in Real Life

This project mirrors how:

·       NASA tracks crew readiness

·       ISRO tracks Gaganyaan astronauts

·       ESA evaluates international partners

·       SpaceX picks long-duration crews

1. DATA  ENGINEERING SKILLS YOU LEARN

We learned how to build structured datasets from scratch using SAS.

You practiced:

Skill	What it means in real life
DATA Step	Creating astronaut master records
SET	Combining multiple astronaut tables
APPEND	Adding new astronauts
MERGE	Linking astronaut data with country stats
TRANSPOSE	Converting rows to columns for reporting

These are the same techniques used in:

·       Clinical trials

·       Banking risk systems

·       Aerospace crew management

·       HR analytics

We are no longer just “writing SAS” — we are building data pipelines.ENGINEERING SKILLS We LEARN

We learned how to build structured datasets from scratch using SAS.

We practiced:

Skill	What it means in real life
DATA Step	Creating astronaut master records
SET	Combining multiple astronaut tables
APPEND	Adding new astronauts
MERGE	Linking astronaut data with country stats
TRANSPOSE	Converting rows to columns for reporting

These are the same techniques used in:

·       Clinical trials

·       Banking risk systems

·       Aerospace crew management

·       HR analytics

2. DATE AND TIME ANALYTICS (MOST IMPORTANT)

Space agencies depend heavily on time calculations.

We learned how to use:

Function	What you did
MDY	Created proper calendar dates
INTNX	Calculated mission start and end dates
INTCK	Measured years of service in space

This is exactly how:

·       NASA tracks astronaut service

·       Pharma companies track drug exposure

·       Banks track account age

We now know how to handle time-based analytics, which is one of the most in-demand SAS skills.

About the Author:

SAS Learning Hub is a data analytics and SAS programming platform focused on clinical, financial, and real-world data analysis. The content is created by professionals with academic training in Pharmaceutics and hands-on experience in Base SAS, PROC SQL, Macros, SDTM, and ADaM, providing practical and industry-relevant SAS learning resources.

Disclaimer:

The datasets and analysis in this article are created for educational and demonstration purposes only. They do not represent astronaut data.

Our Mission:

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