5 day moving average of all items - mysql
below is my MYSQL table structure
ticker
_date
open
high
low
close
volume
below is sample data
ALMOND-I,2012-03-27,373.5000,395.0000,373.5000,380.2500,10
ALMOND-I,2012-03-31,391.0000,391.0000,386.0000,387.0000,5
ALMOND-I,2012-04-03,378.5000,386.0000,364.5000,378.5000,14
ALMOND-I,2012-04-11,380.0000,389.5000,370.7500,380.0000,3
ALMOND-I,2012-04-12,391.0000,391.0000,370.2500,380.7500,2
ALMOND-I,2012-04-16,392.0000,392.0000,392.0000,392.0000,1
ALMOND-I,2012-04-18,380.2500,380.2500,380.2500,380.2500,1
ALMOND-I,2012-05-02,371.0000,393.5000,371.0000,381.5000,6
ALMOND-I,2012-05-15,393.0000,393.0000,393.0000,393.0000,1
ALMOND-I,2012-05-21,416.7500,417.0000,393.0000,398.5000,10
ALMOND-I,2012-05-22,410.5000,410.5000,410.5000,410.5000,1
ALMOND-I,2012-05-30,435.2500,435.2500,435.2500,435.2500,1
ALUMINIUM-I,2012-05-22,110.8000,110.9500,110.2500,110.7000,4939
ALUMINIUM-I,2012-05-23,110.9000,111.4500,110.7500,111.2500,6996
ALUMINIUM-I,2012-05-24,111.0000,111.4500,109.9000,110.4500,7111
ALUMINIUM-I,2012-05-25,110.4500,110.6000,109.4000,109.7000,5020
ALUMINIUM-I,2012-05-26,109.6000,109.8500,109.6000,109.8000,116
ALUMINIUM-I,2012-05-28,109.4000,110.3000,109.3500,110.1500,2614
ALUMINIUM-I,2012-05-29,110.4500,111.0500,110.3000,110.8500,3956
ALUMINIUM-I,2012-05-30,110.9000,111.0500,110.1000,110.9500,5208
ALUMINIUM-I,2012-05-31,110.9500,111.7500,110.7500,111.3500,3553
ALUMINIUM-I,2012-06-01,111.1500,111.3000,108.7000,108.8500,7532
ALUMINIUM-I,2012-06-02,108.8000,108.8000,108.1000,108.2500,555
GOLD-I,2012-05-21,29018.0000,29174.0000,28956.0000,29035.0000,33330
GOLD-I,2012-05-22,29068.0000,29190.0000,28827.0000,29087.0000,45281
GOLD-I,2012-05-23,29026.0000,29084.0000,28831.0000,28969.0000,50523
GOLD-I,2012-05-24,29020.0000,29102.0000,28854.0000,28880.0000,45170
GOLD-I,2012-05-25,28841.0000,28937.0000,28748.0000,28902.0000,32176
GOLD-I,2012-05-26,28964.0000,28964.0000,28918.0000,28925.0000,1427
GOLD-I,2012-05-28,28901.0000,29055.0000,28882.0000,28965.0000,17158
GOLD-I,2012-05-29,28994.0000,29135.0000,28819.0000,28859.0000,39300
GOLD-I,2012-05-30,28845.0000,29154.0000,28755.0000,29117.0000,38733
GOLD-I,2012-05-31,29120.0000,29198.0000,29005.0000,29148.0000,22810
GOLD-I,2012-06-01,29130.0000,29871.0000,28765.0000,29724.0000,4753
GOLD-I,2012-06-02,29745.0000,29929.0000,29740.0000,29866.0000,337
SILVER-I,2012-05-21,54525.0000,54805.0000,53865.0000,54130.0000,66128
SILVER-I,2012-05-22,54187.0000,55119.0000,53873.0000,54392.0000,78147
SILVER-I,2012-05-23,54250.0000,54250.0000,53320.0000,53818.0000,87066
SILVER-I,2012-05-24,53999.0000,54785.0000,53980.0000,54317.0000,74940
SILVER-I,2012-05-25,54250.0000,54500.0000,53882.0000,54426.0000,61457
SILVER-I,2012-05-26,54481.0000,54535.0000,54465.0000,54479.0000,1535
SILVER-I,2012-05-28,54533.0000,54867.0000,54302.0000,54351.0000,33566
SILVER-I,2012-05-29,54448.0000,54885.0000,53790.0000,53964.0000,82448
SILVER-I,2012-05-30,53900.0000,54578.0000,53560.0000,54483.0000,87322
SILVER-I,2012-05-31,54377.0000,54465.0000,53820.0000,54110.0000,72225
SILVER-I,2012-06-01,54002.0000,54682.0000,52813.0000,54445.0000,107052
SILVER-I,2012-06-02,54530.0000,54610.0000,54451.0000,54487.0000,2371
WHEAT-I,2010-07-22,1276.9000,1276.9000,1228.2000,1247.9000,3
WHEAT-I,2010-07-23,1258.0000,1258.0000,1258.0000,1258.0000,2
WHEAT-I,2010-07-29,1245.0000,1245.0000,1245.0000,1245.0000,1
WHEAT-I,2010-07-30,1235.0000,1235.0000,1235.0000,1235.0000,1
WHEAT-I,2010-08-02,1245.0000,1245.0000,1240.0000,1242.5000,2
WHEAT-I,2010-08-04,1220.0000,1220.0000,1220.0000,1220.0000,1
WHEAT-I,2010-08-05,1240.0000,1240.0000,1232.0000,1237.3000,3
WHEAT-I,2011-03-19,1218.9000,1218.9000,1218.9000,1218.9000,1
WHEAT-I,2011-03-21,1182.3000,1182.3000,1182.3000,1182.3000,1
WHEAT-I,2011-03-25,1151.5000,1151.5000,1151.5000,1151.5000,2
WHEAT-I,2011-04-19,1160.0000,1160.0000,1149.5000,1152.3000,4
WHEAT-I,2011-04-28,1170.0000,1195.0000,1170.0000,1182.5000,4
ZINC-I,2012-05-21,103.8000,104.7500,103.8000,104.7000,13197
ZINC-I,2012-05-22,104.7000,105.6000,104.3000,105.5000,14996
ZINC-I,2012-05-23,105.3500,105.4500,104.5000,105.0000,16656
ZINC-I,2012-05-24,104.8000,105.3000,104.2000,104.6500,12688
ZINC-I,2012-05-25,104.6000,105.3000,104.1500,104.9500,12523
ZINC-I,2012-05-26,104.9000,105.0000,104.8000,104.9500,215
ZINC-I,2012-05-28,105.0000,105.5500,104.9000,105.2500,7387
ZINC-I,2012-05-29,105.6000,106.7000,105.4000,106.6000,14092
ZINC-I,2012-05-30,106.3000,106.5000,105.4500,106.3000,11983
ZINC-I,2012-05-31,106.0500,107.4000,105.7500,107.1500,5936
ZINC-I,2012-06-01,105.6500,105.7500,103.7000,104.6500,15231
ZINC-I,2012-06-02,104.5500,104.6500,104.2500,104.4000,551
i want to calculate moving average CLOSE of each item for last 5 dates
example for zinc average ClOSE on 2012-06-02 would be (104.4000+104.6500+107.1500+106.3000+106.6000)/5=105.82
i wrote a query
SELECT x.ticker , AVG( x.close), x._date
FROM
(
SELECT t.ticker , t.close,t._date
FROM mcx_eod_data t
ORDER BY t._date DESC
) x
GROUP BY x.ticker
it gives me average for i think the entire close from start to end of the particular ticker
so i did some Research and added limit statement and modified my query
SELECT x.ticker , AVG( x.close), x._date
FROM
(
SELECT t.ticker , t.close,t._date
FROM mcx_eod_data t
ORDER BY t._date DESC limit 5
) x
GROUP BY x.ticker
but now it fetches data for only 5 tickers
i want to achieve is average of close of last 5 dates for all tickers
Replace the order and limit with a where clause:
WHERE t._date >= DATE_SUB(NOW(), INTERVAL 5 DAY)
Related
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You will have to find out which date is the previous date This can be done using this statement: SELECT MAX(inserted_on) FROM tbl_stockpricemaster WHERE inserted_on < DATE(NOW()) So, changing your query to this should solve your problem: SELECT * FROM tbl_stockpricemaster AS sm WHERE DATE(sm.inserted_on)=(SELECT MAX(inserted_on) FROM tbl_stockpricemaster WHERE inserted_on < DATE(NOW()) ) AND sm.stock_keyvalue='positive' GROUP BY sm.stock_id ORDER BY sm.stock_difprice DESC LIMIT 5;
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One general approach for get the total monsters killed by each user on the latest X days and make a score calculation like the one you propose on the commentaries can be like this:
SET #daysOnHistory = X; -- Where X should be an integer positive number (like 10).
SELECT
nickname,
SUM(bestia1) AS total_bestia1_killed,
SUM(bestia2) AS total_bestia2_killed,
SUM(bestia3) AS total_bestia3_killed,
SUM(bestia4) AS total_bestia4_killed,
SUM(bestia5) AS total_bestia5_killed,
SUM(bestia1 + bestia2 + bestia3 + bestia4 + bestia5) AS total_monsters_killed,
SUM(bestia1 + 2 * bestia2 + 3 * bestia3 + 4 * bestia4 + 5 * bestia5) AS total_score
FROM
reporte
WHERE
fecha >= DATE_ADD(DATE(NOW()), INTERVAL -#daysOnHistory DAY)
GROUP BY
nickname
ORDER BY
total_score DESC
Now, if you want the same calculation but only taking into account the days of the current week (assuming a week starts on Monday), you need to replace the previous WHERE clause by next one:
WHERE
fecha >= DATE_ADD(DATE(NOW()), INTERVAL -WEEKDAY(NOW()) DAY)
Even more, if you want all the same, but only taking into account the days of the current month, you need to replace the WHERE clause by:
WHERE
MONTH(fecha) = MONTH(NOW())
For evaluate the statistics on the days of the current year, you need to replace the WHERE clause by:
WHERE
YEAR(fecha) = YEAR(NOW())
And finally, for evaluation on a specific range of days you can use, for example:
WHERE
DATE(fecha) BETWEEN CAST("2018-10-15" AS DATE) AND CAST('2018-11-10' AS DATE)
I hope this guide will help you and clarify your outlook.
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