Missing Right parenthesis error with `=>` - sql

I am getting the error after writing the below code for a simple insert..select stmnt . I am confused as there seems nothing wrong with syntax .
INSERT INTO dimension_tab(FACT_1_ID,FACT_2_ID,FACT_3_ID,FACT_4_ID,SALES_VALUE)
SELECT TRUNC(DBMS_RANDOM.value(low => 1, high => 3)) AS fact_1_id,
TRUNC(DBMS_RANDOM.value(low => 1, high => 6)) AS fact_2_id,
TRUNC(DBMS_RANDOM.value(low => 1, high => 11)) AS fact_3_id,
TRUNC(DBMS_RANDOM.value(low => 1, high => 11)) AS fact_4_id,
ROUND(DBMS_RANDOM.value(low => 1, high => 100), 2) AS sales_value
FROM dual
CONNECT BY level <= 1000;
COMMIT;


Syntax of DBMS_RANDOM.VALUE is
DBMS_RANDOM.VALUE(
low IN NUMBER,
high IN NUMBER
)
So you can use like this...
INSERT INTO dimension_tab (FACT_1_ID,FACT_2_ID,FACT_3_ID,FACT_4_ID,SALES_VALUE)
SELECT TRUNC(DBMS_RANDOM.value( 1, 3)) AS fact_1_id,
TRUNC(DBMS_RANDOM.value( 1, 6)) AS fact_2_id,
TRUNC(DBMS_RANDOM.value( 1, 11)) AS fact_3_id,
TRUNC(DBMS_RANDOM.value( 1, 11)) AS fact_4_id,
ROUND(DBMS_RANDOM.value( 1, 100), 2) AS sales_value
FROM dual
CONNECT BY LEVEL <= 1000;
COMMIT;


You are using a valid syntax, but as you are using oracle 10g it will not support =>, So you'll have to replace (low => 1, high => 3) with (1, 3).
Try like this,
INSERT INTO dimension_tab
SELECT TRUNC(DBMS_RANDOM.value( 1, 3)) AS fact_1_id,
TRUNC(DBMS_RANDOM.value( 1, 6)) AS fact_2_id,
TRUNC(DBMS_RANDOM.value( 1, 11)) AS fact_3_id,
TRUNC(DBMS_RANDOM.value( 1, 11)) AS fact_4_id,
ROUND(DBMS_RANDOM.value( 1, 100), 2) AS sales_value
FROM dual
CONNECT BY LEVEL <= 1000;

Related

Using .loc to categorize continuous data for range of values

0, 10.65
1, 15.27
2, 15.96
3, 13.49
4, 12.69
5, 7.90
6, 15.96
7, 18.64
8, 21.28
9, 12.69
10, 14.65
11, 12.69
12, 13.49
13, 9.91
14, 10.65
15, 16.29
the code I write is
data2.loc[data2['int_rate'] <= 8.00, 'int_rate'] = "low"
data2.loc[8.00 < data2['int_rate'] <= 30.00, 'int_rate'] = "medium"
data2.loc[15.00 < data2['int_rate'] < 30.00, 'int_rate'] = "high"
In result I get all the value lower than 8.0 as low but no changes to other value.

The answer my problem will be:
data2['int_rate'] = (pd.cut(data2.int_rate, bins=[0, 8.00, 15.00, 30.00], labels=['low', 'medium', 'high']))
above code will implent the low to values lower than 8.00 and high to its respectively.

pandas groupby tuple of different length - ValueError: Values not found in passed level: MultiIndex

Edit: example DataFrame for the original error-message found and posted.
(As I just recognized, the Error does only appear, if the tuple has a certain length. The example is now adapted.)
Original text:
I need to group by tuple of different length.
For the grouping I'm applying a summary_function.
import pandas as pd
def summary_function(df):
value_mean = df['value'].mean()
df1 = pd.DataFrame({'value_mean':[value_mean]
})
return df1
tuple_list = [(1,2,1,1,1,1,1,1,1,1,1,1,1),(2,3,1,1,1,1,1,1,1,1,1,1,1), \
(1,2,1,1,1,1,1,1,1,1,1,1,1), \
(2,3,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1)]
value = [1,2,3,4]
letter = list('abab')
df = pd.DataFrame({'letter':letter, 'tuple':tuple_list, 'value':value})
df
> letter tuple value
>0 a (1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 1
>1 b (2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 2
>2 a (1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 3
>3 b (2, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, ... 4
If I'm using a direct mean() function, the result is how expected:
df.groupby(['letter','tuple']).mean()
> value
>letter tuple
>a (1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 2
>b (2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 2
> (2, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, ...) 4
But if I apply the function. (which I need to use since I have dozens of summaries) The tupel is empty while using the simple
df.groupby(['letter','tuple']).apply(lambda x:summary_function(x))
I get a ValueError:
>ValueError: Values not found in passed level: MultiIndex([(2, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)],
)
It would be awesome to get some ideas on how to solve this.

In your case, do not return the dataframe, return the series.
When you return the series, Pandas will align the series horizontally. For example:
def summary_function(df):
return df['value'].agg(['min','mean','max'])
df.groupby(['letter','tuple']).apply(summary_function)
Output:
value min mean max
letter tuple
a (1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 1.0 2.0 3.0
b (2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) 2.0 2.0 2.0
(2, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1... 4.0 4.0 4.0

The even shorter solution was just to replace "pd.DataFrame" with "pd.Series".
def summary_function(df):
value_mean = df['value'].mean()
df1 = pd.Series({'value_mean':[value_mean]
})
(Inspired by the answer of Quang Hoang)

How much unique data is there, put it all in a table

I would like to query in SQL how many unique values ​​there are and how many rows are there. In Python, I could do it like this. But how do I do this in SQL so that I get the result like at the bottom?
In Python I could do the following
d = {'sellerid': [1, 1, 1, 2, 2, 3, 3, 3], 'modelnumber': [85, 45, 85, 12 ,85, 74, 85, 12]
, 'modelgroup': [2, 3, 2, 1, 2, 3, 2, 1 ]}
df = pd.DataFrame(data=d)
display(df.head(10))
df['Dataframe']='df'
unique_sellerid = df['sellerid'].nunique()
print("unique_sellerid", unique_sellerid)
unique_modelnumber = df['modelnumber'].nunique()
print("unique_modelnumber", unique_modelnumber)
unique_modelgroup = df['modelgroup'].nunique()
print("unique_modelgroup", unique_modelgroup)
total_rows = df.shape[0]
print("total_rows", total_rows)
[OUT]
unique_sellerid 3
unique_modelnumber 4
unique_modelgroup 3
total_rows 8
I want a query like
Here is the dummy table
CREATE TABLE cars (
sellerid INT NOT NULL,
modelnumber INT NOT NULL,
modelgroup INT,
);
INSERT INTO cars
(sellerid , modelnumber, modelgroup )
VALUES
(1, 85, 2),
(1, 45, 3),
(1, 85, 2),
(2, 12, 1),
(2, 85, 2),
(3, 74, 3),
(3, 85, 2),
(3, 12, 1);

You could use the count(distinct column) aggregation function like :
select
count(distinct col1) as nunique_col1,
count(distinct col2) as nunique_col2,
count(1) as nb_rows
from database
Also in pandas, you can also apply the nunique() function on the dataset, rather than doing it on each column: df.nunique()

Oracle SQL error: maximum number of expressions

Could you please help me regarding that issue getting error in Oracle SQL
ORA-01795 maximum number of expressions in a list is 1000
I'm passing value like
and test in (1, 2, 3.....1000)

Try to split your query with multiple in clauses like below
SELECT *
FROM table_name
WHERE test IN (1,2,3,....500)
OR test IN (501, 502, ......1000);

You can try workarounds:
Split single in into several ones:
select ...
from ...
where test in (1, ..., 999) or
test in (1000, ..., 1999) or
...
test in (9000, ..., 9999)
Put values into a (temporary?) table, say TestTable:
select ...
from ...
where test in (select TestField
from TestTable)
Edit: As I can see, the main difficulty is to build such a query. Let's implement it in C#. We are given a collection of ids:
// Test case ids are in [1..43] range
IEnumerable<int> Ids = Enumerable.Range(1, 43);
// Test case: 7, in actual Oracle query you, probably set it to 100 or 1000
int chunkSize = 7;
string fieldName = "test";
string filterText = string.Join(" or " + Environment.NewLine, Ids
.Select((value, index) => new {
value = value,
index = index
})
.GroupBy(item => item.index / chunkSize)
.Select(chunk =>
$"{fieldName} in ({string.Join(", ", chunk.Select(item => item.value))})"));
if (!string.IsNullOrEmpty(filterText))
filterText = $"and \r\n({filterText})";
string sql =
$#"select MyField
from MyTable
where (1 = 1) {filterText}";
Test:
Console.Write(sql);
Outcome:
select MyField
from MyTable
where (1 = 1) and
(test in (1, 2, 3, 4, 5, 6, 7) or
test in (8, 9, 10, 11, 12, 13, 14) or
test in (15, 16, 17, 18, 19, 20, 21) or
test in (22, 23, 24, 25, 26, 27, 28) or
test in (29, 30, 31, 32, 33, 34, 35) or
test in (36, 37, 38, 39, 40, 41, 42) or
test in (43))

Postgresql Crosstab with Array row_name

I have the following SQL statement. The inner query ('SELECT ARRAY...ORDER BY 1,2') works correctly and gives the correct totals for each row_name. When I run the crosstab, the result is incorrect. Changing the 'ORDER BY' in the innner query doesn't seem to change its result, but changes the outer query result. I have verified the types match for crosstab(text,text) for column headings.
SELECT
ct.row_name[1:2] AS zonenumber,
sum(ct.amount1) AS "sumEmploymentamount",
sum(ct.amount3) AS "sumExport_Consumersamount"
FROM output.crosstab('
SELECT
ARRAY[
zonenumber::text,
comTypes.commodity_type_name::text,
year_run::text
] as row_name,
tab.activity_type_id as attribute,
amount as value
FROM
output.all_zonalmakeuse_3 tab,
output.activity_numbers actNums,
output.activity_types actTypes,
output.commodity_numbers comNums,
output.commodity_types comTypes
WHERE
scenario = ''S03'' AND year_run = ''2005'' AND
amount != ''-Infinity'' AND moru = ''M'' AND
actNums.activity_type_id = ActTypes.activity_type_id AND
tab.activity = actNums.activitynumber AND
comNums.commodity_type_id = comTypes.commodity_type_id AND
tab.commodity = comNums.commoditynumber AND
(
comTypes.commodity_type_name =''Financial''OR
comNums.commodity = ''Financial'' OR
comTypes.commodity_type_name =''Goods''OR
comNums.commodity = ''Goods''
) AND
(
actTypes.activity_type_name =''Employment'' OR
actNums.activity = ''Employment'' OR
actTypes.activity_type_name =''Export Consumers'' OR
actNums.activity = ''Export Consumers''
)
ORDER BY 1,2
'::text, '
SELECT activity_type_id AS activity
FROM output.activity_types
WHERE activity_type_id = 1 OR activity_type_id = 3
'::text
) ct (row_name text[], amount1 double precision, amount3 double precision)
GROUP BY ct.row_name[1:2]
ORDER BY ct.row_name[1:2]::text;
Tables
CREATE TABLE activity_numbers
("activitynumber" int, "activity" varchar(46), "activity_type_id" int)
;
INSERT INTO activity_numbers
("activitynumber", "activity", "activity_type_id")
VALUES
(0, '"AI01AgMinMan"', 1),
(1, '"AI02AgMinProd"', 1),
(2, '"AI03ConMan"', 1),
(3, '"AI04ConProd"', 1),
(4, '"AI05MfgMan"', 1),
(5, '"AI06MfgProd"', 1),
(6, '"AI07TCUMan"', 1),
(7, '"AI08TCUProd"', 1),
(8, '"AI09Whole"', 1),
(9, '"AI10Retail"', 1),
(10, '"AI11FIRE"', 1),
(11, '"AI12PTSci"', 1),
(12, '"AI13ManServ"', 1),
(13, '"AI14PBSOff"', 1),
(14, '"AI15PBSRet"', 1),
(15, '"AI16PSInd"', 1),
(16, '"AI17Religion"', 1),
(17, '"AI18BSOnsite"', 1),
(18, '"AI19PSOnsite"', 1);
CREATE TABLE activity_types
("activity_type_id" int, "activity_type_name" varchar(18))
;
INSERT INTO activity_types
("activity_type_id", "activity_type_name")
VALUES
(1, '"Employment"'),
(2, '"Households"'),
(3, '"Export Consumers"')
;
CREATE TABLE commodity_numbers
("commoditynumber" int, "commodity" varchar(29), "commodity_type_id" int)
;
INSERT INTO commodity_numbers
("commoditynumber", "commodity", "commodity_type_id")
VALUES
(0, '"CG01AgMinDirection"', 1),
(1, '"CG02AgMinOutput"', 1),
(2, '"CG03ConDirection"', 1),
(3, '"CG04ConOutput"', 1),
(4, '"CG05MfgDirection"', 1),
(5, '"CG06MfgOutput"', 1),
(6, '"CS07TCUDirection"', 2),
(7, '"CS08TCUOutput"', 2),
(8, '"CS09WsOutput"', 2),
(9, '"CS10RetailOutput"', 2),
(10, '"CS11FIREOutput"', 2),
(11, '"CS13OthServOutput"', 2),
(12, '"CS14HealthOutput"', 2),
(13, '"CS15GSEdOutput"', 2),
(14, '"CS16HiEdOutput"', 2),
(15, '"CS17GovOutput"', 2),
(16, '"CF18TaxReceipts"', 4),
(17, '"CF19GovSupReceipts"', 4),
(18, '"CF20InvestReceipts"', 4),
(19, '"CF21ReturnInvestReceipts"', 4),
(20, '"CF22CapitalTransferReceipts"', 4)
;
CREATE TABLE commodity_types
("commodity_type_id" int, "commodity_type_name" varchar(23))
;
INSERT INTO commodity_types
("commodity_type_id", "commodity_type_name")
VALUES
(1, '"Goods"'),
(4, '"Financial"')
;
CREATE TABLE all_zonalmakeuse_3
("year_run" int, "scenario" varchar(6), "activity" int, "zonenumber" int, "commodity" int, "moru" varchar(3), "amount" numeric, "activity_type_id" int, "commodity_type_id" int)
;
INSERT INTO all_zonalmakeuse_3
("year_run", "scenario", "activity", "zonenumber", "commodity", "moru", "amount", "activity_type_id", "commodity_type_id")
VALUES
(2005, '"C11a"', 0, 1, 0, '"M"', 1752708.30900861, 1, 1),
(2005, '"C11a"', 0, 3, 0, '"M"', 2785972.97039016, 1, 1),
(2005, '"C11a"', 0, 4, 0, '"M"', 3847879.45910403, 1, 1),
(2005, '"C11a"', 1, 1, 1, '"M"', 26154618.3893068, 1, 1),
(2005, '"C11a"', 1, 3, 1, '"M"', 1663.49609248196, 1, 1),
(2005, '"C11a"', 1, 4, 1, '"M"', 91727.9065950723, 1, 1),
(2005, '"C11a"', 1, 1, 5, '"M"', 855899.319689473, 1, 1),
(2005, '"C11a"', 1, 3, 5, '"M"', 54.4372375336784, 1, 1),
(2005, '"C11a"', 1, 4, 5, '"M"', 3001.75868302327, 1, 1),
(2005, '"C11a"', 2, 1, 2, '"M"', 150885191.664482, 1, 1),
(2005, '"C11a"', 2, 2, 2, '"M"', 99242746.1181359, 1, 1),
(2005, '"C11a"', 2, 3, 2, '"M"', 90993266.1879518, 1, 1),
(2005, '"C11a"', 2, 4, 2, '"M"', 60169908.2975819, 1, 1),
(2005, '"C11a"', 3, 1, 3, '"M"', 642982844.104623, 1, 1),
(2005, '"C11a"', 3, 2, 3, '"M"', 421379496.576106, 1, 1),
(2005, '"C11a"', 3, 3, 3, '"M"', 592125233.320609, 1, 1),
(2005, '"C11a"', 3, 4, 3, '"M"', 400206994.693349, 1, 1),
(2005, '"C11a"', 4, 1, 4, '"M"', 449206658.578704, 1, 1),
(2005, '"C11a"', 4, 2, 4, '"M"', 103823580.173348, 1, 1),
(2005, '"C11a"', 4, 3, 4, '"M"', 181300924.388112, 1, 1),
(2005, '"C11a"', 4, 4, 4, '"M"', 143113096.547075, 1, 1),
(2005, '"C11a"', 5, 1, 1, '"M"', 83889.8852772168, 1, 1),
(2005, '"C11a"', 5, 2, 1, '"M"', 25716.5837854808, 1, 1),
(2005, '"C11a"', 5, 3, 1, '"M"', 10243.7021847824, 1, 1),
(2005, '"C11a"', 5, 4, 1, '"M"', 22406.3296935502, 1, 1),
(2005, '"C11a"', 5, 1, 5, '"M"', 408669650.696034, 1, 1),
(2005, '"C11a"', 5, 2, 5, '"M"', 125278360.769936, 1, 1),
(2005, '"C11a"', 5, 3, 5, '"M"', 49902204.2985933, 1, 1),
(2005, '"C11a"', 5, 4, 5, '"M"', 109152455.018677, 1, 1),
(2005, '"C11a"', 5, 1, 20, '"M"', 161822.743734245, 1, 4),
(2005, '"C11a"', 5, 2, 20, '"M"', 49607.031096612, 1, 4),
(2005, '"C11a"', 5, 3, 20, '"M"', 19759.998336631, 1, 4),
(2005, '"C11a"', 5, 4, 20, '"M"', 43221.5842952059, 1, 4),
(2005, '"C11a"', 7, 1, 1, '"M"', 122316.017730318, 1, 1),
(2005, '"C11a"', 7, 2, 1, '"M"', 20514.5008361246, 1, 1),
(2005, '"C11a"', 7, 3, 1, '"M"', 8431.33094615992, 1, 1),
(2005, '"C11a"', 7, 4, 1, '"M"', 75842.631567318, 1, 1),
(2005, '"C11a"', 13, 1, 5, '"M"', 1195626.97941868, 1, 1),
(2005, '"C11a"', 13, 2, 5, '"M"', 567002.352487648, 1, 1),
(2005, '"C11a"', 13, 3, 5, '"M"', 1104908.87426762, 1, 1),
(2005, '"C11a"', 13, 4, 5, '"M"', 1071325.74253601, 1, 1),
(2005, '"C11a"', 17, 1, 1, '"M"', 751648.370711072, 1, 1),
(2005, '"C11a"', 17, 2, 1, '"M"', 340439.936040081, 1, 1),
(2005, '"C11a"', 17, 3, 1, '"M"', 800477.767008582, 1, 1),
(2005, '"C11a"', 17, 4, 1, '"M"', 489745.223392316, 1, 1),
(2005, '"C11a"', 17, 1, 20, '"M"', 3154907.39011312, 1, 4),
(2005, '"C11a"', 17, 2, 20, '"M"', 1428934.74123601, 1, 4),
(2005, '"C11a"', 17, 3, 20, '"M"', 3359859.9041298, 1, 4),
(2005, '"C11a"', 17, 4, 20, '"M"', 2055616.54193613, 1, 4),
(2005, '"C11a"', 18, 1, 20, '"M"', 2088003.66854949, 1, 4),
(2005, '"C11a"', 18, 2, 20, '"M"', 1310122.52506653, 1, 4),
(2005, '"C11a"', 18, 3, 20, '"M"', 1481450.29636847, 1, 4),
(2005, '"C11a"', 18, 4, 20, '"M"', 3035710.53213605, 1, 4)
;
I have manipulated the query in several ways (changed type casting, order by, etc), but always get incorrect values. The row and column headers are at least consistently correct.