concat

Sorry I change my question a bit . I have two table and I want to merge them TERMS_TABLE ID | TERMS 309 | 'hardware' 309 | 'software' TFIDF_TABLE ID | TERMS 309 |'computer,phone,mp3....' Now I want to add TERMS column of TERMS_TABLE to terms column of TFIDF_TABLE like that result should be: NEW_TFIDF_TABLE ID | TERMS 309 |'computer,phone,mp3....,hardware,software' I try this code: Insert into NEW_TFIDF_TABLE SELECT T.ID, T.TERMS ||', '|| TT.TERMS FROM TFIDF_TABLE T INNER JOIN TERMS_TABLE TT ON T.ID=TT.ID but it does not do what I want How can I do that ? Modification: I forgot an issue. If

I am testing performance in a MySQL Server and filling a table with more than 200 million of records. The Stored Procedure is very slow generating the big SQL string. Any help or comment is really welcome. System Info: Database: MySQL 5.6.10 InnoDB database (test). Processor: AMD Phenom II 1090T X6 core, 3910Mhz each core. RAM: 16GB DDR3 1600Mhz CL8. HD: Windows 7 64bits SP1 in SSD, mySQL installed in SSD, logs written in mechanical hard disk. The Stored Procedure creates a INSERT sql query with all the values to be inserted into the table. DELIMITER $$ USE `test`$$ DROP PROCEDURE IF EXISTS

I am quite new to pandas, I am attempting to concatenate a set of dataframes and I am getting this error: ValueError: Plan shapes are not aligned My understanding of .concat() is that it will join where columns are the same, but for those that it can't find it will fill with NA. This doesn't seem to be the case here. Heres the concat statement: dfs = [npo_jun_df, npo_jul_df,npo_may_df,npo_apr_df,npo_feb_df] alpha = pd.concat(dfs) user3805082 In case it helps, I have also hit this error when I tried to concatenate two data frames (and as of the time of writing this is the only related hit I can

在Mysql中两个字符串相加不能用+号，加号是用来做数字相加的，在mysql中要连接字符串需要用CONCAT或者CONCAT_WS函数： Mysql CONCAT函数 语法： CONCAT(str1,str2...) 例如： select OCNCAT('AB','CD') 将输出ABCD 需要注意的是： SELECT CONCAT('abc',NULL)其中有一个字符串为NULL时将输出NULL Mysql 的CONCAT_WS函数 的CONCAT_WS函数()函数, 表示concat with separator,即有分隔符的字符串连接 select concat_ws(',','11','22','33'); 输出: 11,22,33 需注意concat_ws的参数中有null的话，并非都返回null，例如concat_ws(',','ab',NULL)将输出ab Mysql的GROUP_CONCAT()函数 从名字可以看出这个函数是一个聚合函数，在group语句中使用，可以将多行的字符串按分组整合成一个字符串。 语法： GROUP_CONCAT([DISTINCT] expr [,expr ...][ORDER BY {unsigned_integer | col_name | expr} [ASC | DESC] [,col_name ...]][SEPARATOR

1、 concat () 函数 1.1 MySQL的concat函数可以连接一个或者多个字符串 , 如 mysql > select concat ( '10' ); +--------------+ | concat ( '10' ) | +--------------+ | 10 | +--------------+ 1 row in set ( 0.00 sec ) mysql > select concat ( '11' , '22' , '33' ); +------------------------+ | concat ( '11' , '22' , '33' ) | +------------------------+ | 112233 | +------------------------+ 1 row in set ( 0.00 sec ) 而Oracle的concat函数只能连接两个字符串 SQL > select concat ( '11' , '22' ) from dual ; 1.2 MySQL的concat函数在连接字符串的时候，只要其中一个是NULL , 那么将返回NULL mysql > select concat ( '11' , '22' , null ); +------------------------+ | concat ( '11'

What is the fastest method, to add a new value at the beginning of a string? Thor Jacobsen var mystr = "Doe"; mystr = "John " + mystr; Wouldn't this work for you? You could do it this way .. var mystr = 'is my name.'; mystr = mystr.replace (/^/,'John '); console.log(mystr); disclaimer: http://xkcd.com/208/ ES6: let after = 'something after'; let text = `before text ${after}`; chirag you could also do it this way "".concat("x","y") Since the question is about what is the fastest method, I thought I'd throw up add some perf metrics. TL;DR The winner, by a wide margin, is the + operator, and

I am trying to column-bind dataframes and having issue with pandas concat , as ignore_index=True doesn't seem to work: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'], 'B': ['B0', 'B1', 'B2', 'B3'], 'D': ['D0', 'D1', 'D2', 'D3']}, index=[0, 2, 3,4]) df2 = pd.DataFrame({'A1': ['A4', 'A5', 'A6', 'A7'], 'C': ['C4', 'C5', 'C6', 'C7'], 'D2': ['D4', 'D5', 'D6', 'D7']}, index=[ 5, 6, 7,3]) df1 # A B D # 0 A0 B0 D0 # 2 A1 B1 D1 # 3 A2 B2 D2 # 4 A3 B3 D3 df2 # A1 C D2 # 5 A4 C4 D4 # 6 A5 C5 D5 # 7 A6 C6 D6 # 3 A7 C7 D7 dfs = [df1,df2] df = pd.concat( dfs,axis=1,ignore_index=True) print df and the

I have a list of Pandas dataframes that I would like to combine into one Pandas dataframe. I am using Python 2.7.10 and Pandas 0.16.2 I created the list of dataframes from: import pandas as pd dfs = [] sqlall = "select * from mytable" for chunk in pd.read_sql_query(sqlall , cnxn, chunksize=10000): dfs.append(chunk) This returns a list of dataframes type(dfs[0]) Out[6]: pandas.core.frame.DataFrame type(dfs) Out[7]: list len(dfs) Out[8]: 408 Here is some sample data # sample dataframes d1 = pd.DataFrame({'one' : [1., 2., 3., 4.], 'two' : [4., 3., 2., 1.]}) d2 = pd.DataFrame({'one' : [5., 6., 7.,