concat

I'm using the gulp-order module along with the event-streams module and gulp-concat to concatenate javascript files into a single dest file. The gulp-order plugin has worked great for me in other projects where I wanted to concatenate files from the stream in a distinct order. For some reason in this project it is not working properly, and the files in the public/angular/config directory are dispersed amongst the files I specify to concatenate last in the public/js directory. I think this may have something to do with specifying multiply sources ie. the angular and js directories. I tried

I want to group fields but want to show all row of a column called remain : here is current output without grouping: And output with group: And I want This when I group: Here is mysql query: SELECT staff.name, staff.designation_id_designation, staff.status_id_status, Concat_Ws('=', leave_remain.leave_type_id_leave_type, leave_remain.days) AS remain FROM staff INNER JOIN leave_remain ON staff.id_staff = leave_remain.staff_id_staff GROUP BY staff.name use GROUP_CONCAT SELECT staff.name, staff.designation_id_designation, staff.status_id_status, GROUP_CONCAT(Concat_Ws('=', leave_remain.leave_type

I have two dataframes that I would like to concatenate column-wise (axis=1) with an inner join. One of the dataframes has some duplicate indices, but the rows are not duplicates, and I don't want to lose the data from those : df1 = pd.DataFrame([{'a':1,'b':2},{'a':1,'b':3},{'a':2,'b':4}], columns = ['a','b']).set_index('a') df2 = pd.DataFrame([{'a':1,'c':5},{'a':2,'c':6}],columns = ['a','c']).set_index('a') >>> df1 b a 1 2 1 3 2 4 8 9 >>> df2 c a 1 5 2 6 The default concat behavior is to fill missing values with NaNs: >>> pd.concat([df1,df2]) b c a 1 2 NaN 1 3 NaN 2 4 NaN 1 NaN 5 2 NaN 6 I

本文将演示以下6个 Oracle 中的常用字符函数。 函数 功能 ASCII(x) 返回字符x的ASCII码。 CONCAT(x,y) 连接字符串x和y。 INSTR(x, str [,start] [,n) 在x中查找str，可以指定从start开始，也可以指定从第n次开始。 LENGTH(x) 返回x的长度。 LOWER(x) x转换为小写。 UPPER(x) x转换为大写。 下面将结合实例对这些函数进行介绍。 o ASCII () 函数 ：返回字符x的ASCII码。 示例1： SQL> select ascii('A') from dual; ASCII('A') ---------- 65 o CONCAT (x,y)函数：连接字符串x和y。 示例2： SQL> select concat(empno,ename) from emp where deptno=10; CONCAT(EMPNO,ENAME) -------------------------------------------------- 7782CLARK 7839KING 7934MILLER o INSTR(x, str [,start] [,n)函数：在x中查找str，可以指定从start开始，也可以指定从第n次开始。 示例3： SQL> select instr ('ABC123','C1')

EDIT After removing my silly mistake of INTO (I was working with INSERTS and just keep going) the error below is showing. Still not working: Affected rows: 0 [Err] 1093 - You can't specify target table 'tbl' for update in FROM clause I'm trying to create an update where I select all the previous data in the column, add a complementary string and save it as new data. The code is below (with the error) Using only the select, the result: set @id = 3; SELECT tbl_alias.string_id FROM tbl as tbl_alias WHERE id = @id -- the output `3,10,8,9,4,1,7,11,5,2,6,12` I also tried with this query (the output

I have several Dataframes with the same columns that I'd like to merge on their indices only. print df1 out[]: Value ISO Id 200001 8432000000 USD 200230 22588186000 USD 200247 4633000000 USD 200291 1188880000 USD 200418 1779776000 USD print df2 out[]: Value ISO Id 200001 1.309168e+11 USD 200230 5.444096e+10 USD 200247 9.499602e+09 USD 200291 2.089603e+09 USD 200418 3.827251e+09 USD print df3 out[]: Value Id 200001 3.681908 200230 3.408507 200247 4.531866 200291 0.273029 200418 3.521822 I could use pd.concat([df1, df2, df3], axis=1) and get out[]: Value ISO Value ISO Value Id 200001 8432000000