From a52a4234132d0df4ea280c0f773ed88aabb0227c Mon Sep 17 00:00:00 2001 From: Marcin Date: Mon, 13 May 2019 20:08:00 +0200 Subject: [PATCH] Added more queries --- R/bad_proj_analytics.Rmd | 91 +++++++++++++++++++++++++++++++++++---- R/bad_proj_analytics.pdf | Bin 175904 -> 190094 bytes SQL files/10.sql | 9 ++++ SQL files/8.sql | 43 ++++++++++++++++++ SQL files/9.sql | 5 +++ 5 files changed, 139 insertions(+), 9 deletions(-) create mode 100644 SQL files/10.sql create mode 100644 SQL files/8.sql create mode 100644 SQL files/9.sql diff --git a/R/bad_proj_analytics.Rmd b/R/bad_proj_analytics.Rmd index a1e9905..36d3bd1 100644 --- a/R/bad_proj_analytics.Rmd +++ b/R/bad_proj_analytics.Rmd @@ -1,10 +1,12 @@ --- -title: "BAD_Proj_Analytics" +title: "BAD_Analytics_Project" author: "Marcin Kostrzewski" date: "13/05/2019" output: pdf_document --- +Raport został wygenerowany przy użyciu danych udostępnionych przez [Departament Transportu Stanów Zjednoczonych](https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236) + ```{r, echo=FALSE} con <- DBI::dbConnect(odbc::odbc(), driver = "SQL Server", @@ -15,7 +17,7 @@ con <- DBI::dbConnect(odbc::odbc(), port = 5432) ``` -## Jakie było średnie opóźnienie przylotu? +# Jakie było średnie opóźnienie przylotu? ```{sql, connection=con, tab.cap = NA} SELECT CAST(AVG(arr_delay) AS NUMERIC(30,3)) AS 'Average delay (minutes)' @@ -23,7 +25,7 @@ FROM Flight_delays WHERE arr_delay IS NOT NULL; ``` -## Jakie było maksymalne opóźnienie przylotu? +# Jakie było maksymalne opóźnienie przylotu? ```{sql, connection=con, tab.cap = NA} SELECT CAST(MAX(arr_delay)/60 AS NUMERIC(30,3)) AS 'Max delay (hours)' @@ -31,7 +33,7 @@ FROM Flight_delays WHERE arr_delay IS NOT NULL; ``` -## Który lot miał największe opóźnienie przylotu? +# Który lot miał największe opóźnienie przylotu? ```{sql, connection=con, tab.cap = NA} SELECT carrier AS 'Carrier', @@ -45,7 +47,7 @@ WHERE arr_delay = (SELECT MAX(arr_delay) WHERE arr_delay IS NOT NULL); ``` -## Które dni tygodnia są najgorsze do podróżowania? +# Które dni tygodnia są najgorsze do podróżowania? ```{sql, connection=con, tab.cap = NA} SELECT CASE WHEN day_of_week = 1 THEN 'Monday' @@ -62,7 +64,7 @@ GROUP BY day_of_week ORDER BY AVG(arr_delay) DESC; ``` -## Które linie lotnicze latające z San Francisco (SFO) mają najmniejsze opóźnienia przylotu? +# Które linie lotnicze latające z San Francisco (SFO) mają najmniejsze opóźnienia przylotu? ```{sql, connection=con, tab.cap = NA} SELECT F1.carrier AS 'Carrier', @@ -78,7 +80,7 @@ ORDER BY "Delay (minutes)" ASC; *Pojawiające się w tabeli wartości ujemne oznaczają, że średnio samoloty lądowały wcześniej, niż przewidziano, czyli były przyśpieszone.* -## Jaka część linii lotniczych ma regularne opóźnienia, tj. jej lot ma średnio co najmniej 10 min. opóźnienia? +# Jaka część linii lotniczych ma regularne opóźnienia, tj. jej lot ma średnio co najmniej 10 min. opóźnienia? ```{sql, connection=con, tab.cap = NA, echo=FALSE} SELECT (SELECT COUNT(*) @@ -96,8 +98,9 @@ SELECT (SELECT COUNT(*) GROUP BY carrier) AS T) AS FLOAT) AS 'Part of continuous delays'; ``` -## Jak opóźnienia wylotów wpływają na opóźnienia przylotów? -```{r, con, echo=FALSE} +# Jak opóźnienia wylotów wpływają na opóźnienia przylotów? + +```{r, connection=con, tab.cap = NA} data <- DBI::dbGetQuery(con, "SELECT dep_delay, arr_delay FROM Flight_delays @@ -107,3 +110,73 @@ library(knitr) res <- cor(data, use = "all", method = "pearson") kable(res[2:2]) ``` + +# Która linia lotnicza miała największy wzrost (w wartościach bezwzględnych) średniego opóźnienia przylotów w ostatnim tygodniu miesiąca, tj. między 1-23 a 24-31 lipca? + +```{sql, connection=con, tab.cap = NA, max.print = NA} +SET NOCOUNT ON +DECLARE @1_23avg TABLE +( + carrier VARCHAR(50), + avg FLOAT +); + +INSERT INTO @1_23avg +SELECT carrier, + AVG(avg1) AS 'avg1A' +FROM (SELECT carrier, + AVG(arr_delay) AS 'avg1' + FROM Flight_delays + WHERE month = 7 + GROUP BY carrier, day_of_month + HAVING day_of_month BETWEEN 1 AND 23) AS T1 +GROUP BY carrier; + + +DECLARE @24_31avg TABLE +( + carrier VARCHAR(50), + avg FLOAT +); + +INSERT INTO @24_31avg +SELECT carrier, + AVG(avg2) AS 'avg2A' +FROM (SELECT carrier, + AVG(arr_delay) AS 'avg2' + FROM Flight_delays + WHERE month = 7 + GROUP BY carrier, day_of_month + HAVING day_of_month BETWEEN 24 AND 31) AS T2 +GROUP BY carrier; +SET NOCOUNT OFF; +SELECT T1.carrier AS 'Carrier', + T1.avg-T2.avg AS 'Delay growth' +FROM @1_23avg T1 INNER JOIN @24_31avg T2 + ON T1.carrier = T2.carrier +ORDER BY T1.avg-T2.avg DESC; +``` + +# Które linie lotnicze latają zarówno na trasie SFO → PDX (Portland), jak i SFO → EUG (Eugene)? + +```{sql, connection=con, tab.cap = NA} +SELECT DISTINCT carrier AS 'Carrier' +FROM Flight_delays +WHERE origin LIKE 'SFO' + AND + (dest IN ('PDX', 'EUG')) +``` + +# Jak najszybciej dostać się z Chicago do Stanfordu, zakładając wylot po 14:00 czasu lokalnego? + +```{sql, connection=con, tab.cap = NA} +SELECT origin AS 'Origin', + dest AS 'Destination', + AVG(arr_delay) AS 'Delay' +FROM Flight_delays +WHERE origin IN ('MDW', 'ORD') + AND dest IN ('SFO', 'SJC', 'OAK') + AND crs_dep_time>1400 +GROUP BY origin, dest +ORDER BY AVG(arr_delay) DESC; +``` diff --git a/R/bad_proj_analytics.pdf b/R/bad_proj_analytics.pdf index d0807c9c2623d414dfa7a111f4492138f75f874a..13701b395ae2cc8eba2b430deb7bbaba266830a2 100644 GIT binary patch delta 157471 zcmZU4Q*@wh%x!Jkw(Y5H+nn0QTTE@+Q`^>5Q=3!UHqZC3bI#SDt6b#bSy@?o=h;aL zw&3EX;87`+#U&Y8nK;yN@WCgj^)`j}P_8k;z)xrn~Rbkf2m_!Zk#Ek6X*ne2)|a@=fjhS07n%m7JyB z(dF41LT$hnxOgDVa8Symuyh=Fei0s`Q@?tU6Go|qOt(Xhx-EgBU`E{>kDS$gCDFr#M;2wuL6_w^Yr;%Z~%QCKKA>m(D8JZq8=4Db(cuoPI%%!z~z%$lCDl9kc z#5&r?RAk6D?(1%)aTZJP&!rScLfx22y_ae>-?ktX`*S-y-5G*@SMK_nu54>@mYoi6 zT^^Xj*f~a&G$!O=eF7oJ7{}HKs~(`~`dUNKA+5iVcWHjhewyp7JQ_&r!K)chhYPhv z6(7)IEyR#1st3cqK%y_ze;GmML<55klC=IcP1k2{d*HWkY%{I{67Nl2_S>2p6UBeO zOfcjJX+zz`SuO_>epgL!6C?|0Hg-J0DlGtNENmfHPGD&}!o=cvPR&G?(h^DGVR0oD 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ztAn(eL98I=e?cWXJ0}n~H;4(Ogup0mYijo|gXzD2VjyikCT?+Ic2*HlZc!02R!$BU zPH|3Ac2PD?4rWnNE-p@C0nq=QqKo{$tvd@F3+O+sJK+qc5`+Sp@6HC5Ff{mpZ>bnF zDBRyaOuq;0zzxo-W(S%;i$7d&Lz zpX?teoief)svm@+Y>(8yRIuyaKnO1-j8|Wa#GRzSnLXYsF#d;hFAt1e!;f^{;Ok;8 zl!-Zjcr;OXWo z>0Cqnx%IA>D2PRc-|`=M#L21400 +GROUP BY origin, dest +ORDER BY AVG(arr_delay) DESC; \ No newline at end of file diff --git a/SQL files/8.sql b/SQL files/8.sql new file mode 100644 index 0000000..ee96968 --- /dev/null +++ b/SQL files/8.sql @@ -0,0 +1,43 @@ +--Average delays between 1 and 23 per carrier +DECLARE @1_23avg TABLE +( + carrier VARCHAR(50), + avg FLOAT +) + +INSERT INTO @1_23avg +SELECT carrier, + AVG(avg1) AS 'avg1A' +FROM (SELECT carrier, + AVG(arr_delay) AS 'avg1' + FROM Flight_delays + WHERE month = 7 + GROUP BY carrier, day_of_month + HAVING day_of_month BETWEEN 1 AND 23) AS T1 +GROUP BY carrier; + + +--Average delays between 24 and 31 per carrier +DECLARE @24_31avg TABLE +( + carrier VARCHAR(50), + avg FLOAT +) + +INSERT INTO @24_31avg +SELECT carrier, + AVG(avg2) AS 'avg2A' +FROM (SELECT carrier, + AVG(arr_delay) AS 'avg2' + FROM Flight_delays + WHERE month = 7 + GROUP BY carrier, day_of_month + HAVING day_of_month BETWEEN 24 AND 31) AS T2 +GROUP BY carrier; + +--Final SELECT +SELECT T1.carrier AS 'Carrier', + T1.avg-T2.avg AS 'Delay growth' +FROM @1_23avg T1 INNER JOIN @24_31avg T2 + ON T1.carrier = T2.carrier +ORDER BY T1.avg-T2.avg DESC; \ No newline at end of file diff --git a/SQL files/9.sql b/SQL files/9.sql new file mode 100644 index 0000000..bf79e4d --- /dev/null +++ b/SQL files/9.sql @@ -0,0 +1,5 @@ +SELECT DISTINCT carrier AS 'Carrier' +FROM Flight_delays +WHERE origin LIKE 'SFO' + AND + (dest IN ('PDX', 'EUG'))