Select Data from Date Range Between Two Dates

SQL query to select dates between two dates

you should put those two dates between single quotes like..

select Date, TotalAllowance from Calculation where EmployeeId = 1
             and Date between '2011/02/25' and '2011/02/27'

or can use

select Date, TotalAllowance from Calculation where EmployeeId = 1
             and Date >= '2011/02/25' and Date <= '2011/02/27'

keep in mind that the first date is inclusive, but the second is exclusive, as it effectively is '2011/02/27 00:00:00'

Select data from date range between two dates and times

I've never seen BETWEEN(from,to) as a pattern in an sql query - you're making it look like a function call similar to SUBSTRING(column, index) when it doesn't work like that. Try this:

SELECT * FROM aview 
WHERE 
  startDate BETWEEN CONVERT(datetime, '2017-11-25 11:27:00.000', 121) AND CONVERT(datetime, '2018-11-25 11:27:00.000', 121) OR 
  leftdate BETWEEN CONVERT(datetime, '2017-11-25 11:27:00.000', 121) AND CONVERT(datetime, '2018-11-25 11:27:00.000', 121) OR 
  start_Date <= CONVERT(datetime, '2017-11-25 11:27:00.000', 121) AND left_dept_date >= CONVERT(datetime, '2018-11-25 11:27:00.000', 121)

There's no syntax error with this query (see http://sqlfiddle.com/#!6/9eecb7db59d16c80417c72d1e1f4fbf1/16114 ) when the columns are proper dates, so the only thing left is a flaw in the view code, doing a bum conversion of data - for example if your view is converting a string of "12/31/2017" into a date, but doing it as if it was "dd/mm/yyyy", or perhaps converting a "2107-12-31" with a typo in the year, into a smalldatetime type that doesn't support years beyond 2079

See https://docs.microsoft.com/en-us/sql/t-sql/language-elements/between-transact-sql

Select data between a date/time range

You need to update the date format:

select * from hockey_stats 
where game_date between '2012-03-11 00:00:00' and '2012-05-11 23:59:00' 
order by game_date desc;

Get all dates between two dates in SQL Server

My first suggestion would be use your calendar table, if you don't have one, then create one. They are very useful. Your query is then as simple as:

DECLARE @MinDate DATE = '20140101',
        @MaxDate DATE = '20140106';

SELECT  Date
FROM    dbo.Calendar
WHERE   Date >= @MinDate
AND     Date < @MaxDate;

If you don't want to, or can't create a calendar table you can still do this on the fly without a recursive CTE:

DECLARE @MinDate DATE = '20140101',
        @MaxDate DATE = '20140106';

SELECT  TOP (DATEDIFF(DAY, @MinDate, @MaxDate) + 1)
        Date = DATEADD(DAY, ROW_NUMBER() OVER(ORDER BY a.object_id) - 1, @MinDate)
FROM    sys.all_objects a
        CROSS JOIN sys.all_objects b;

For further reading on this see:

• Generate a set or sequence without loops – part 1
• Generate a set or sequence without loops – part 2
• Generate a set or sequence without loops – part 3

With regard to then using this sequence of dates in a cursor, I would really recommend you find another way. There is usually a set based alternative that will perform much better.

So with your data:

  date   | it_cd | qty 
24-04-14 |  i-1  | 10 
26-04-14 |  i-1  | 20

To get the quantity on 28-04-2014 (which I gather is your requirement), you don't actually need any of the above, you can simply use:

SELECT  TOP 1 date, it_cd, qty 
FROM    T
WHERE   it_cd = 'i-1'
AND     Date <= '20140428'
ORDER BY Date DESC;

If you don't want it for a particular item:

SELECT  date, it_cd, qty 
FROM    (   SELECT  date, 
                    it_cd, 
                    qty, 
                    RowNumber = ROW_NUMBER() OVER(PARTITION BY ic_id 
                                                    ORDER BY date DESC)
            FROM    T
            WHERE   Date  <= '20140428'
        ) T
WHERE   RowNumber = 1;

Select DataFrame rows between two dates

There are two possible solutions:

• Use a boolean mask, then use df.loc[mask]
• Set the date column as a DatetimeIndex, then use df[start_date : end_date]

---

Using a boolean mask:

Ensure df['date'] is a Series with dtype datetime64[ns]:

df['date'] = pd.to_datetime(df['date'])  

Make a boolean mask. start_date and end_date can be datetime.datetimes,
np.datetime64s, pd.Timestamps, or even datetime strings:

#greater than the start date and smaller than the end date
mask = (df['date'] > start_date) & (df['date'] <= end_date)

Select the sub-DataFrame:

df.loc[mask]

or re-assign to df

df = df.loc[mask]

---

For example,

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.random((200,3)))
df['date'] = pd.date_range('2000-1-1', periods=200, freq='D')
mask = (df['date'] > '2000-6-1') & (df['date'] <= '2000-6-10')
print(df.loc[mask])

yields

            0         1         2       date
153  0.208875  0.727656  0.037787 2000-06-02
154  0.750800  0.776498  0.237716 2000-06-03
155  0.812008  0.127338  0.397240 2000-06-04
156  0.639937  0.207359  0.533527 2000-06-05
157  0.416998  0.845658  0.872826 2000-06-06
158  0.440069  0.338690  0.847545 2000-06-07
159  0.202354  0.624833  0.740254 2000-06-08
160  0.465746  0.080888  0.155452 2000-06-09
161  0.858232  0.190321  0.432574 2000-06-10

---

Using a DatetimeIndex:

If you are going to do a lot of selections by date, it may be quicker to set the
date column as the index first. Then you can select rows by date using
df.loc[start_date:end_date].

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.random((200,3)))
df['date'] = pd.date_range('2000-1-1', periods=200, freq='D')
df = df.set_index(['date'])
print(df.loc['2000-6-1':'2000-6-10'])

yields

                   0         1         2
date                                    
2000-06-01  0.040457  0.326594  0.492136    # <- includes start_date
2000-06-02  0.279323  0.877446  0.464523
2000-06-03  0.328068  0.837669  0.608559
2000-06-04  0.107959  0.678297  0.517435
2000-06-05  0.131555  0.418380  0.025725
2000-06-06  0.999961  0.619517  0.206108
2000-06-07  0.129270  0.024533  0.154769
2000-06-08  0.441010  0.741781  0.470402
2000-06-09  0.682101  0.375660  0.009916
2000-06-10  0.754488  0.352293  0.339337

While Python list indexing, e.g. seq[start:end] includes start but not end, in contrast, Pandas df.loc[start_date : end_date] includes both end-points in the result if they are in the index. Neither start_date nor end_date has to be in the index however.

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Also note that pd.read_csv has a parse_dates parameter which you could use to parse the date column as datetime64s. Thus, if you use parse_dates, you would not need to use df['date'] = pd.to_datetime(df['date']).

Query to select data between two dates with the format m/d/yyyy

This solution provides CONVERT_IMPLICIT operation for your condition in predicate

SELECT * 
FROM xxx 
WHERE CAST(dates AS date) BETWEEN '1/1/2013' and '1/2/2013'

OR

SELECT * 
FROM xxx 
WHERE CONVERT(date, dates, 101) BETWEEN '1/1/2013' and '1/2/2013'

Demo on SQLFiddle

Get DAYs of data between two dates from a date range

try it:

DECLARE @DateSearch1 DATETIME='2017-03-13'
DECLARE @DateSearch2 DATETIME='2017-09-25'
SELECT *,DATEDIFF(DAY,r.dat1,r.dat2) daysOfRange
FROM
(
SELECT  BillID ,
        CASE WHEN FromDate<@DateSearch1 THEN @DateSearch1 ELSE FromDate END AS dat1,
        CASE WHEN ToDate>@DateSearch2 THEN @DateSearch2 ELSE ToDate END AS dat2
FROM    Bills

WHERE   ( FromDate >= @DateSearch1
          AND FromDate <= @DateSearch2
        )
        AND ( ToDate >= @DateSearch1
              AND ToDate <= @DateSearch2
            ))r

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