I have a varchar column [DB_TIMESTAMP] in a (DB2) table which get data from different sources/environments, This column have different formats in it like:
11/15/2019 11:30:02
11/15/2019 11:22 AM
2019/11/15 11:15 AM
I have to put remarks using CASE in my query to find if there is any row that has 2 hours delay from current DateTime with this column data then mark them pending.
I tried like following, but it need the column with DateTime format which it is not because of different format of data entered in it:
CASE WHEN days (current date) - days(DB_TIMESTAMP))>2
[for checking 2 hours difference]
I think, this column needs to be converted into DateTime then try with above may work, but how:
Please help.
Shamshad Ali
Try Something May it helps:
CASE WHEN DAYS (Replace (CONVERT(nvarchar (500), CURRENT_DATE ,106),' ','-') as current_date)
- DAYS(Replace (CONVERT(nvarchar (500), DB_TIMESTAMP ,106),' ','-') as DB_TIMESTAMP))>2
Related
I have a table that has a series of Columns with data I need to split out. Example below
STATUS#10/16 12:00:00 (CODE)
I've been able to split it easy enough and when I originally tried to set the date on an older dataset it identified it as a date e.g. 16th Oct 2021 However I started to get errors on this date column and trying with different datasets (10/12, 10/13, 10/14) it is not finding the date. I tried the following query code but I'm receiving errors
[STATUS DATE] is split to 10/14, 10/15 etc
#date( Date.Year(DateTime.LocalNow), Date.Month(Text.End([STATUS DATE]), 2), Date.Day(Text.Start([STATUS DATE]),2))
However I'm getting a function error so I tried
Date.From(Date.Day(Text.Start([STATUS DATE]),2) & Date.Month(Text.End([STATUS DATE]),2) & Date.Year(DateTime.LocalNow)
I have also tried to do this from an example column however the query created is looking at the cell value e.g. if 10/14 then 14/10/2021 else if 13/10 then 14/10/2021. This method i feel is prone for error once I include a larger dataset.
Is there anyway I can determine the date value based on mm/dd format? But with year end in mind, make the YYYY be determined by current year unless we move into Jan and then I don't want the Oct, Nov, Dec value showing as 2022.
You don't really show what your original data looks like.
But if it is like:
Source
Then you can use this code in the Add Custom Column dialog:
let
split=Text.SplitAny([STATUS DATE],"#/ "),
mnth = Number.From(split{1}),
dy = Number.From(split{2})
in
#date(Date.Year(DateTime.LocalNow()),mnth,dy)
The Text.SplitAny function lets you input a list of delimiters and the text will split on all of them. So it is relatively simple to extract the month and day values
to create:
Split [STATUS DATE] one more time into [Month] and [Day] column, using the "/" as a separator. Then you don't have to bother with 1 or 2 digit numbers and you can simply use this formula:
#date(Date.Year(DateTime.LocalNow()), [Month], [Day])
DateTime.LocalNow() is a function, so you need to add the brackets.
[Month] and [Day] are numbers already, so you don't need the Date.Month() or Date.Day() functions.
how to separate date and time from datetime column if you have the format as below :
click here to view image
I am trying int(datetime column) for fetching date ; Datetime column - int(datetime column) for fetching time column
Your formula cannot work because your data is a text string (note that it has a letter included) and not a number.
So first convert the string into a "real" time with:
=substitute(a2,"T"," ")
You can then use:
Date: =INT(SUBSTITUTE(A2,"T"," "))
Time: =MOD(SUBSTITUTE(A2,"T"," "),1)
and be sure to format the results as desired:
If your column is formatted true date then use to separate date
=TEXT(A1,"yyyy-mm-dd")
For time
=TEXT(A1,"hh:mm:ss")
If data is in text string or output by TEXT() function then try below functions.
for date =TEXT(FILTERXML("<t><s>"&SUBSTITUTE(A1,"T","</s><s>")&"</s></t>","//s[1]"),"yyyy-mm-dd")
for time =TEXT(FILTERXML("<t><s>"&SUBSTITUTE(A1,"T","</s><s>")&"</s></t>","//s[last()]"),"hh:mm:ss")
For date
=LEFT(A2,FIND("T",A2)-1)
For time
=RIGHT(A2,LEN(A2)-FIND("T",A2))
I am looking to read data from a column in my CSV file.
All of the data in this column are dates. (DD/MM/YYYY).
I want my program to read the Dates column, and if the date is within 3 days of the current date, I want to add variables to all of the values in that row.
Ex.
Date,Name,LaterDate
1/1/19,John Smith, 2/21/19
If I run my program on 2/19/2019, I want an email sent that says "John Smith's case is closing on "2/21/2019".
I understand how to send an email. The part that I get stuck on is:
Reading the CSV column specifically.
If the date is within 3 days,
Assign variables to the values in the ROW,
Use those variables to send a custom email.
I see a lot of "Use Pandas" but I might need the individual steps broken down.
Thank you.
First things first, you need to read all the values of the csv file and store it in a variable (old_df). Then you need to save all the dates in the Series (dates). Next we create an empty DataFrame with the same columns. From here we create a simple for loop for each date in dates and it's index i. Turn date into a datetime object from the datetime library. Then we subtract amount of days between the current date and date. Take the absolute value of days so we always get a positive amount of days. Then add the index of that particular date in old_df to new_df.
import pandas as pd
from datetime import datetime
old_df = pd.read_csv('example.csv')
dates = old_df['LaterDate']
new_df = pd.DataFrame(columns=['Date', 'Name', 'LaterDate'])
for i, date in enumerate(dates):
date = datetime.strptime(date, '%m/%d/%y')
days = (datetime.now() - date).days
if abs(days) <= 3:
new_df = new_df.append(old_df.loc[i, :])
print(new_df)
I have a table containing several columns of which one is a date/time field. I am trying to get a count of instances per day using the following
=COUNTIFS(Table4[Data],"Apple",Table4[Date],(CONCATENATE(V4,"*")))
Data Date Comp Date Count
Apple 6/12/18 1:00 PM 6/12/18 12:00 AM 0
Apple 6/12/18 7:00 AM
Orange 6/12/18 1:30 PM
Apple 6/11/18 11:23 AM
From my understanding of all the moving parts here I should be checking to see if "Apple" exists in the data column and then if "6/12/18" with any amount or type of characters after it exists. If both are true I will then get a count + 1 leaving me with a value of 2 in the above example.
What I actually get however is a 0 unless I match the time portion of date the data to be exactly the same and then removed the wildcard ,"*" from the equation.
Am I doing something wrong or can the wildcard not be used to accomplish what I am trying?
Thanks!
I think you should set your criteria properly.
If you add an additional column next to your Date that contains calculates the integer value of your date using INT() and format the display as DATE (m/d/yyyy) you should then be able to use the following COUNTIFS formula
=COUNTIFS(Table4[Data], "Apple", Table4[Date], "=6/12/18")
See the explanatory video from their Office' support site: https://support.office.com/en-us/article/countifs-function-dda3dc6e-f74e-4aee-88bc-aa8c2a866842
If your [Date] column is a datetime or smalldatetime, you can work with it using CONVERT function, depending on how you want to group.
For example, if you don't care about the time to do the group, you could use the next query:
SELECT CONVERT(varchar,[Date],103), [Data], COUNT(*)
FROM [test_delete].[dbo].[Table1]
GROUP BY CONVERT(varchar,[Date],103), [Data]
This should result in something like this:
[Date] [Data] [Count]
11/06/2018 Apple 1
12/06/2018 Apple 2
12/06/2018 Orange 1
Hope this helps you
If your dates are stored as dates instead of text, use the following:
=COUNTIFS(Table4[Data],"Apple",Table4[Date],">="&V4,Table4[Date],"<"&V4+1)
I have imported an excel sheet where the date1 is 4/1/16 date2 is 5/29/14 and date3 is 5/2/14. However, when I import the sheet into SAS and do PROC PRINT gives the first 2 variable columns as "42461" and "41788" while the date3 is 05/02/2014.
I need these date formats consistent b/c I am doing a Cox regression with PROC PHREG.
Any thoughts about how to make these dates consistent?
Thanks!
This probably depends on how the data is represented in Excel and how it is imported into SAS. First, are the formats the same in Excel? The first two are being imported as a number. The second as a string.
In Excel, you can format the column using a date format. Perhaps your import method will recognize this. You can also define another column as a string, using the text(<whatever>, "YYYY-MM-DD") to convert to a string in that format.
Alternatively, you can import all as numbers and then add the value to 1899-12-31. That is the base date for Excel. This makes more sense if you think of "1" as being 1900-01-01.
Because your column had mixed numeric (date) and character values SAS imported the field as character. So the actual dates got imported as the text version of the actual number that Excel stores for dates. The ones that look like date strings in SAS are the fields that were strings in Excel also.
Or if in your case one of the three columns was all valid dates then SAS imported it as a number and assigned a date format to it so there is nothing to fix for that column.
The best way to fix it is to make sure that all of the values in the date column are either real dates or empty cells. Then PROC IMPORT will be able to make the right guess at how to import it.
Once you have the strings in SAS and you want to try to fix them then you need to decide which strings look like integers and which should be treated as date strings.
So you might just check if they have any non-digit characters and assume those are the ones that are date strings instead of numbers. For the ones that look like integers just adjust the number to account for the fact that Excel numbers dates from 1900 and SAS numbers them from 1960.
data want ;
set have ;
if missing(exel_string) then date=.;
else if notdigit(trim(excel_string)) then date=input(excel_string,anydtdte32.);
else date=input(excel_string,32.) + '01JAN1900'd -2 ;
format date yymmdd10. ;
run;
You might wonder why the minus 2? It is because Excel starts from 1 instead of 0 and also because Excel thinks 1900 was a leap year. Here are the Excel date numbers for some key dates and a little SAS program to convert them. Try it.
data excel_dates;
input datestr :$10. excel_num :comma32. #1 sas_num :yymmdd10. ;
diff = sas_num - excel_num ;
format _numeric_ comma14. ;
sasdate1 = excel_num - 21916;
sasdate2 = excel_num + '01JAN1900'd -2 ;
format sasdate: yymmdd10.;
cards;
1900-01-01 1
1900-02-28 59
1900-03-01 61
1960-01-01 21,916
2018-01-01 43,101
;