How to remove particular character in a column in ms access table - ms-access

I have a ms access table which has a column named description which contains several records, There is a Space in the records which are of longer lengths, I need to remove the space which is in 26th character. As i am new to access i find difficult to write queries, Any help would be greatly appreciated.
For Example descrption column has few values like this : MOXIFLOXACIN HYDROCHLORDI E/SODIUM CHLORIDE, There is a space between I and E, SO i need to concatenate it like this for all the records
MOXIFLOXACIN HYDROCHLORDIE/SODIUM CHLORIDE

Removing characters can be a difficult concept.
If you want to remove the 26th character, you essentially should take all characters except the 26th character, which is the 25 characters to the left, and all characters higher than 27 to the right.
I'm checking inline if the string is longer than 26 characters, you might also decide to check that in a WHERE clause.
UPDATE myTable
Set MyColumn = Left(MyColumn, 25) & IIF(Len(MyColumn) > 26, Right(MyColumn, Len(MyColumn) - 26), "")

Related

MySQL Invoice numbers range with count

Firstly I want this to be purely done with MySQL query.
I have a series of Invoice numbers
invoice_number
INV001
INV002
INV003
INV004
INV005
001
002
003
006
007
009
010
INVOICE333
INVOICE334
INVOICE335
INVOICE337
INVOICE338
INVOICE339
001INV
002INV
005INV
009INV
I want to output something like this
from_invoice_no to_invoice_no total_invoices
INV001 INV005 5
001 010 7
INVOICE333 INVOICE339 6
001INV 009INV 4
The invoice number pattern cannot be fixed. They can change in future
Please help me to achieve this.
Thanks in advance.
I will first show a general idea how to solve this problem and provide some code which will be ugly, but easily understandable. Then I'll explain what the issues are and how to remedy them.
STEP 1: Deriving the grouping criterion
For the first step, I assume you have the right (privilege) to create an additional column in your table. Let us name it invoice_text. Now, the general idea is to remove all digits from the invoice number so that only the "text pattern" remains. Then we can group by the text pattern.
Assuming that you have already created the column mentioned above, you could do the following:
UPDATE Invoices SET invoice_text = REPLACE(invoice_number, '0', '');
UPDATE Invoices SET invoice_text = REPLACE(invoice_text, '1', '');
UPDATE Invoices SET invoice_text = REPLACE(invoice_text, '2', '');
...
UPDATE Invoices SET invoice_text = REPLACE(invoice_text, '9', '');
After having done that, you will have the pure text pattern without digits in invoice_text and can use that for grouping:
SELECT COUNT(invoice_number) AS total_invoices FROM Invoices
GROUP BY invoice_text
This is nice, but it is not yet what you wanted. It does not show the first and last invoice number for each group.
STEP 2: Deriving the first and last invoice for each group
For this step, create one more column in your table. Let us name it invoice_digits. As the name implies, it is meant to take only the pure invoice number without the "pattern text".
Assuming you have that column, you could do the following:
UPDATE Invoices SET invoice_digits = REPLACE(invoice_number, 'A', '');
UPDATE Invoices SET invoice_digits = REPLACE(invoice_digits, 'B', '');
UPDATE Invoices SET invoice_digits = REPLACE(invoice_digits, 'C', '');
...
UPDATE Invoices SET invoice_digits = REPLACE(invoice_digits, 'Z', '');
Now, you can use that column to get the minimum and maximum invoice number (without "pattern text"):
SELECT
MIN(invoice_digits) AS from_invoice_no,
MAX(invoice_digits) AS to_invoice_no,
COUNT(invoice_number) AS total_invoices
FROM Invoices
GROUP BY invoice_text
Problems and how to solve them
1) According to your question, you want to get the minimum and maximum full invoice number text. The solution above will show only the minimum and maximum invoice number text without the text parts, i.e. only the digits.
We could remedy this by doing a further JOIN, but since I can very well imagine that you won't insist on this :-), and since it won't make the general idea more clear, I am leaving this to you. If you are interested, let us know.
2) It might be difficult to decide what a digit (i.e. what the actual invoice number) is. For example, if you have invoice numbers like INV001, INV002, this will be no problem, but what if you have INV001/001, INV001/002, INV002/003 and so on? In this example, my code would would yield 001001, 001002, 002003 as actual invoice numbers and use that to decide what the minimum and maximum numbers are.
This might not be what you want to do in that case. The only way around this is that you thoroughly think about what you should consider a digit and what not, and to adapt my code accordingly.
3) My code currently uses string comparisons to get the minimum and maximum invoice numbers. This may yield other results than comparing the values as numbers. If you are wondering what that means: Compare '19' to '9' as string, and compare 19 to 9 as number.
If this is a problem, then use MySQL's CAST to convert the text to a number before feeding it to MAX or MIN. But please be aware that this has its own caveats:
If you have very long invoice numbers with so many digits that they don't fit into MySQL's numeric data types, this method will fail. It will also fail if you have defined a character like / to be digits (due to the issues described in 2)) since MySQL can't convert this into a number.
Instead of converting to numbers, you can also pad the values in invoice_digits with leading zeroes, for example using MySQL's LPAD function. This will avoid the problems described above and sort the numbers as expected, even if they include non-digits like /, but you will have to know the maximum length of the digit string in advance.
4) The code is ugly! Do you really have to remove all possible characters from A to Z one by one by doing UPDATE statements to get the digit string?
Actually, it is even worse. I just have assumed that you only have the "text characters" A to Z in your invoices. But there could be any character Unicode defines: Russian or Chinese ones, special characters, in other words: thousands of different characters.
Unfortunately, AFAIK, MySQL still does not provide a REGEX-REPLACE function. I don't see any chance to get this problem solved unless you extend MySQL with an appropriate UDF (user defined function). There are some cool guys out there who have recognized the problem and have added such functions to MySQL. Since recommending libraries seems to be discouraged on SO, just google for "mysql regex replace".
When having extended MySQL that way, you can replace the ugly bunch of UPDATE statements which remove the digits / the text from the invoice number by a single one (using a REGEX, you can replace all digits or all non-digits at once).
For the sake of completeness, you could avoid the many UPDATE statements by doing UPDATE ... SET ... = REPLACE(REPLACE(REPLACE(...))) and thus applying all updates with one statement. But this is even more ugly and error prone, so if you are serious about your problem, you'll really have to extend MySQL by a REGEX-REPLACE.
5) The solution will only work if you have the privilege to create new columns in the table.
This is true for the solution as-is. But I have chosen to go that way solely because it makes the general idea clear and understandable. Instead of adding columns to your original table, you could also create a new table where you store the pure text / digits (this table might be a temporary one).
Furthermore, since MySQL supports grouping by computed values, you don't need additional columns / tables at all. You should decide by yourself what is the best way to go.

SQL RegEx to handle comma separated IDs

I have a string that denotes which users are allowed to access something. For instance, if user 1, user 2, and user 3 could access it, the accessibility column would contain 1,2,3. If only user 1 could access it, it would only be 1 and so forth.
I know I can't do a simple CONTAINS clause because searching for 1 could return true for 14,2,3. How would I get a regex to accommodate when there is a comma on both sides, on one side, or neither of the ID number?
Here is a sample of what I'm trying to do
DataID: 1
Accessibility: "1,2,3,4,5"
Data: "secret stuff"
DataID: 2
Accessibility: "5,6,7,8,9"
Data: "more secret stuff"
I need to tell the regex to search for a number and to make sure its at the beginning of the string and the end of the string if it has no commas around it, is at the beginning of the string if it only has a comma after it, is at the end of a string if it only has a comma before it, or if it commas on both sides that's fine because it's in the middle of the string.
I know what I need to do, but don't know how to achieve it. Thanks.
First, you have a really bad data structure for several reasons:
The proper way to store lists in SQL is using tables, not strings.
The proper way to store integers in SQL is as integers, not strings.
Ids should be defined with a proper foreign key relationship, which you cannot do when the id is stored in a string.
Sometimes, we are stuck with other people's bad design decisions. That is, we are unable to create a proper junction table, with one column for the DataId and each user who has access to it.
In that situation, you can use the find_in_set() functionality in MySQL. This does not require a regular expression. You can just write:
where find_in_set($user, accessibility) > 0
Since A-Z, 0-9, and underscore are considered word boundaries, you could generalize like this:
-- word-bound DataID, e.g. 1 becomes \b1\b
SELECT '\b' || DataID || '\b' AS DataID_Bound FROM USER
WHERE REGEX_LIKE(DataID_Bound, Accessibility)
That way it doesn't matter if there is a comma leading, trailing, or if it's a sole occupant of the search subject. But it deffinitely cannot match 14 or 21, etc. \b1\b will only match solo 1, \b14\b will only match whole word 14, etc.

Delete all characters before and after quotation marks

I have a CSV file, which has two columns and 4500 rows. In one column, I have several phrases that are surrounded in quotation marks. I need to delete all the text that comes before and after the quotations marks.
For example:
How would you say "Hello, my Friend" when speaking outside?
should become "Hello, my Friend"
I also have several rows that have the word NULL in the second column. I need these rows deleted in full.
What's the best way of doing something like this? I have been looking at regular expressions, but I'm not sure if they are flexible enough to do what I want to do, or how you would use them on a CSV file (I need the table structure to remain).
EDIT:
1) At the moment I am just using Apple Numbers, but I know that wont don't it, so I am happy to any suggestions. It must support Kanji characters.
2) I have removed all the NULL rows, so that is no longer needed (I simply added a column of numbers, sorted the table so all the NULLs were together, deleted them and the sorted back by the column of numbers).
Find a text editor that supports regular expression search and replace.
Something like this would match ,NULL in the second column: ^.*,NULL.*$. Replace it with "DELETEMEDELETEME" to mark the line, or as an empty string or find a way to have it match on `\n' or '\r' to catch the line break and remove the entire line completely.
Stripping out parts of the quoted string might work like this:
^(.*,){n}(.*)(\".\")(.*)(,.*)$ replaced with \1\3\5 where n is the number of columns preceding the one you want to edit. Repeat (.*,) if that's not available. It will depend on the regex flavor of your tool.

MySQL Regex - Find where there are 10 numbers in a row in a field

I need to find records where there are 10 numbers in a row in the field. e.g. 1234567890, 8884265555 etc. The field will contain text as well so I need to see if any 10-digit strings exist anywhere within the field.
I have got this far...
SELECT * FROM `comments` WHERE detail REGEXP '[0-9]{10}'
My that returns where there 10 numbers anywhere in the field instead of all in a row. I am trying to detect phone numbers. Thanks!
The regular expression [0-9]{10} does imply that ten digits in a row (only) should be matched. So, your issue must be elsewhere.

VBA Trim() function truncating text oddly!

I'm trying to trim extraneous white space at the end of a memo field in MS Access. I've tried doing it a number of ways:
1) an update query with the field being updated to Trim([fieldname]). For some reason, that doesn't do anything. The whitespace is still there.
2) an update using a Macro function in which the field contents are passed as a String and then processed using the Trim() function and passed back. This one is really bizarre, in that it seems to truncate the text in the field at completely random places (different for each record). Sometimes 366 characters, sometimes 312, sometimes 280.
3) same as above but with RTrim()
How can I possibly be messing up such a simple function?! Any help much appreciated. Would like to keep my hair.
-Sam
According to this article:
Both Text and Memo data types store only the characters entered in a field; space characters for unused positions in the field aren't stored.
As hypoxide suggested, they may not in fact be spaces
Edit
I suspect that the last character in the field is a carriage return or linefeed character. If this is the case, then Trim (or any variations of Trim - RTrim\LTrim) won't work since they only remove space characters. As 'onedaywhen' suggested in the comment, try using the ASC function to determine the actual character code of the last character in the memo field. You can use something like the following in a query to do this:
ASC(Right(MyFieldName,1))
Compare the result of the query to the Character Set to determine the actual character that ends the memo field. (Space = 32, Linefeed = 10, Carriage Return = 13).
You may have to test the last character and if it is a linefeed or carriage return remove the character and then apply the trim function to the rest of the string.
This may date me, but does Access have different character types for fixed vs. variable lengths? in SQL, CHAR(10) will always by 10 chars long, padded if necessary, while VARCHAR(10) will be 'the' size up to 10. Truncating a CHAR(10) will just put the blanks back.