Trying to run an update on the following result set:
Row# ProductRankID ProductID ProductCategoryID ProductTypeID Rank Score
1 3 11266 9 80 0 765
2 14 25880 9 80 0 656
3 12 25864 9 80 0 547
4 7 11252 9 80 0 457
5 8 25719 9 80 0 456
6 4 13425 9 80 0 456
7 11 25677 9 80 0 456
8 9 25716 9 80 0 432
9 15 25714 9 80 0 324
10 13 13589 9 80 0 234
11 20 25803 9 80 0 234
12 17 25715 9 80 0 213
13 5 21269 9 80 0 154
14 10 25867 9 80 0 123
15 16 25676 9 80 0 123
16 22 17861 9 80 0 67
17 19 13534 9 80 0 55
18 23 13659 9 80 0 54
19 29 13658 9 80 0 34
20 21 13591 9 80 0 32
21 6 11249 9 80 0 23
22 18 11253 9 80 0 12
23 28 11253 9 87 0 65
24 27 13664 9 87 0 45
25 25 13658 9 87 0 14
26 26 13657 9 87 0 13
27 24 13659 9 87 0 13
28 30 11252 9 87 0 12
29 2 12345 11 80 0 324
I want the "Rank" column to be set 1...2..3..4 etc based on each row. Then on change of the ProductCategoryID + ProductTypeID, I want it to reset to 1...2...3...4 etc.
So the results should look something like:
Row# ProductRankID ProductID ProductCategoryID ProductTypeID Rank Score
1 3 11266 9 80 1 765
2 14 25880 9 80 2 656
3 12 25864 9 80 3 547
4 7 11252 9 80 4 457
5 8 25719 9 80 5 456
6 4 13425 9 80 6 456
7 11 25677 9 80 7 456
8 9 25716 9 80 8 432
9 15 25714 9 80 9 324
10 13 13589 9 80 10 234
11 20 25803 9 80 11 234
12 17 25715 9 80 12 213
13 5 21269 9 80 13 154
23 28 11253 9 87 1 65
24 27 13664 9 87 2 45
25 25 13658 9 87 3 14
26 26 13657 9 87 4 13
27 24 13659 9 87 5 13
28 30 11252 9 87 6 12
29 2 12345 11 80 1 324
Hope that makes some sense?
Thanks,
Richie
If you want a select:
select t.*,
row_number() over (partition by ProductCategoryID, ProductTypeID
order by score desc, productid
) as new_rank
from t;
If you want an update, use a CTE:
with toupdate as (
select t.*,
row_number() over (partition by ProductCategoryID, ProductTypeID
order by score desc, productid
) as new_rank
from t
)
update toupdate
set rank = new_rank;
Related
I have a data frame like the following:
days movements count
0 0 0 2777
1 0 1 51
2 0 2 2
3 1 0 6279
4 1 1 200
5 1 2 7
6 1 3 3
7 2 0 5609
8 2 1 110
9 2 2 32
10 2 3 4
11 3 0 4109
12 3 1 118
13 3 2 101
14 3 3 8
15 3 4 3
16 3 6 1
17 4 0 3034
18 4 1 129
19 4 2 109
20 4 3 6
21 4 4 2
22 4 5 2
23 5 0 2288
24 5 1 131
25 5 2 131
26 5 3 9
27 5 4 2
28 5 5 1
29 6 0 1918
30 6 1 139
31 6 2 109
32 6 3 13
33 6 4 1
34 6 5 1
35 7 0 1442
36 7 1 109
37 7 2 153
38 7 3 13
39 7 4 10
40 7 5 1
41 8 0 1085
42 8 1 76
43 8 2 111
44 8 3 13
45 8 4 7
46 8 7 1
47 9 0 845
48 9 1 81
49 9 2 86
50 9 3 8
51 9 4 8
52 10 0 646
53 10 1 70
54 10 2 83
55 10 3 1
56 10 4 2
57 10 5 1
58 10 6 1
This shows that for example on day 0, I have 2777 entries with 0 movements, 51 entries with 1 movement, 2 entries with 2 movements. I want to plot it as bar graph for every day and show the entries count for all movements. In order to do it, I thought I would transform the data to something like below and then plot a bar graph.
days 0 1 2 3 4 5 6 7
0 2777 51 2
1 6279 200 7 3
2 5609 110 32 4
3 4109 118 101 8 3
4 3034 129 109 6 2 2
5 2288 131 131 9 2 1
6 1918 139 109 13 1 1
7 1442 109 153 13 10 1
8 1085 76 111 13 7 1
9 845 81 86 8 8
10 646 70 83 1 2 1 1
I am not getting an idea of how should I achieve this? I have thousands of lines of data so doing it by hand does not make sense. Can someone guide me how to rearrange the data or if there is a quick way to plot the bar graph using matplotlib straight from the actual data frame that would be even better. Thanks for the help.
I have a SQL table with below values
dozen1 dozen2 dozen3 dozen4 dozen5 dozen6
----------------------------------------------
10 27 40 46 49 58
2 11 34 37 32 50
3 4 29 36 45 55
14 32 33 36 44 52
20 11 36 38 47 53
1 5 11 16 20 55
2 18 31 42 51 52
5 11 22 24 51 53
1 3 11 17 34 45
I need count the quantity of results by number, sample :
Number 10 appears 1 time
Number 2 appears 2 times
Result:
Dozen Times
--------------
10 1
2 2
....
How do this in a SQL query?
If you want to count the number of occurrences of distinct numbers in all columns:
select dozen, count(*) as times
from my_table
cross join unnest(array[dozen1, dozen2, dozen3, dozen4, dozen5, dozen6]) u(dozen)
group by 1
order by 1;
dozen | times
-------+-------
1 | 2
2 | 2
3 | 2
4 | 1
5 | 2
etc...
I want to find abnormal values and replace them with corresponding day of next week.
year week day v1 v2
2001 1 1 46 9999
2001 1 2 60 9335
2001 1 3 9999 9318
2001 1 4 47 9999
2001 1 5 57 9373
2001 1 6 9999 9384
2001 1 7 72 9444
2001 2 1 75 73
2001 2 2 74 63
2001 2 3 79 377
2001 2 4 70 361
2001 2 5 75 73
2001 2 6 77 64
2001 2 7 76 57
I could carry out column by column,code as follows:
index_row=df[df['v1']==9999].index
for i in index_row:
df['v1'][i]=df['v1'][i+7] # i+7 is the index of next week
How to element-wise the whole dataframe? Such as pd.applymap.
How get the columns number(name) and row number base on conditional seiving values?
The target df I want as follows:
( * indicated modified values and the next week values)
year week day v1 v2
2001 1 1 46 *73
2001 1 2 60 9335
2001 1 3 *79 9318
2001 1 4 47 *361
2001 1 5 57 9373
2001 1 6 *77 9384
2001 1 7 72 9444
2001 2 1 75 *73
2001 2 2 74 63
2001 2 3 *79 377
2001 2 4 70 *361
2001 2 5 75 73
2001 2 6 *77 64
2001 2 7 76 57
create d1 with set_index on columns ['year', 'week', 'day']
create d2 with same index as d1 except, subtract 1 from week
mask with other
cols = ['year', 'week', 'day']
d1 = df.set_index(cols)
d2 = df.assign(week=df.week - 1).set_index(cols)
d1.mask(d1.eq(9999), d2).reset_index()
year week day v1 v2
0 2001 1 1 46 73
1 2001 1 2 60 9335
2 2001 1 3 79 9318
3 2001 1 4 47 361
4 2001 1 5 57 9373
5 2001 1 6 77 9384
6 2001 1 7 72 9444
7 2001 2 1 75 73
8 2001 2 2 74 63
9 2001 2 3 79 377
10 2001 2 4 70 361
11 2001 2 5 75 73
12 2001 2 6 77 64
13 2001 2 7 76 57
old answer
One approach is to setup d1 with index of ['year', 'week', 'day'] and manipulate that to shift a week. Then mask it for equal to 9999 and fillna
d1 = df.set_index(['year', 'week', 'day'])
s1 = d1.unstack(['year', 'day']).shift(-1).stack(['year', 'day']).swaplevel(0, 1)
d1.mask(d1==9999).fillna(s1).reset_index()
year week day v1 v2
0 2001 1 1 46.0 73.0
1 2001 1 2 60.0 9335.0
2 2001 1 3 79.0 9318.0
3 2001 1 4 47.0 361.0
4 2001 1 5 57.0 9373.0
5 2001 1 6 77.0 9384.0
6 2001 1 7 72.0 9444.0
7 2001 2 1 75.0 73.0
8 2001 2 2 74.0 63.0
9 2001 2 3 79.0 377.0
10 2001 2 4 70.0 361.0
11 2001 2 5 75.0 73.0
12 2001 2 6 77.0 64.0
13 2001 2 7 76.0 57.0
You can working with DatetimeIndex, set value by mask with shifted rows:
a = df['year'].astype(str).add('-').add(df['week'].astype(str))
.add('-').add(df['day'].sub(1).astype(str))
#http://strftime.org/
df.index = pd.to_datetime(a, format='%Y-%U-%w')
df2 = df.shift(-1,freq='7D')
df = df.mask(df.eq(9999), df2).reset_index(drop=True)
print (df)
year week day v1 v2
0 2001 1 1 46 73
1 2001 1 2 60 9335
2 2001 1 3 79 9318
3 2001 1 4 47 361
4 2001 1 5 57 9373
5 2001 1 6 77 9384
6 2001 1 7 72 9444
7 2001 2 1 75 73
8 2001 2 2 74 63
9 2001 2 3 79 377
10 2001 2 4 70 361
11 2001 2 5 75 73
12 2001 2 6 77 64
13 2001 2 7 76 57
How can I return in column4 the smallest number from column3 based on column1?
1 100 1
2 100 1
1 101 2
1 102 4
2 200 19
3 200 19
16 200 19
18 200 19
19 200 19
20 200 19
3 301 28
6 301 28
3 302 29
3 310 30
4 400 31
4 410 32
4 420 33
5 500 34
7 500 34
5 510 35
6 510 35
5 520 36
6 610 37
7 700 38
7 701 39
8 701 39
8 800 40
8 802 41
Thank you!
Join to a subquery that calculates the minimums for each col1:
select a.col1, a.col2, a.col3, mcol3
from mytable a
join (select col1, min(col3) mcol3 from mytable group by col1) b
on b.col1 = a.col1
See SQLFiddle, showing this output from your sample data:
1 100 1 1
2 100 1 1
1 101 2 1
1 102 4 1
2 200 19 1
3 200 19 19
16 200 19 19
18 200 19 19
19 200 19 19
20 200 19 19
3 301 28 19
6 301 28 28
3 302 29 19
3 310 30 19
4 400 31 31
4 410 32 31
4 420 33 31
5 500 34 34
7 500 34 34
5 510 35 34
6 510 35 28
5 520 36 34
6 610 37 28
7 700 38 34
7 701 39 34
8 701 39 39
8 800 40 39
8 802 41 39
I detect mouse wheel scroll using PointerWheelChanged event at WinRT. I use PointerPoint.Properties.MouseWheelDelta to detect amount and direction of scroll:
PointerPoint mousePosition = e.GetCurrentPoint(_control);
var delta = mousePosition.Properties.MouseWheelDelta;
Nowadays there are devices which emulate mouse scroll (touchpad or touch mice etc).
They tend to issue tens or hundreds (sic!) PointerWheelChanged events per "scroll". Legacy mouse wheel issues one event per wheel click which has delta of +-120 units.
I need to do some heavy processing as soon as user scrolls to some position.
Is there a way to understand that "new" scroll is complete?
FYI Here is a mouse wheel deltas for a single finger flick with Microsoft TouchMouse (sorry for the amount, I just want to illustrate the problem).
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EDIT:
Now I do this hack but it is far from perfect
// interval between mouse deltas
private readonly TimeSpan _wheelDeltaThrottleInterval = TimeSpan.FromMilliseconds(8);
// interval to wait until scroll is complete
private readonly TimeSpan _wheelDeltaCompleteInterval = TimeSpan.FromMilliseconds(600);
// create smart wheel handler
IObservable<PointerPoint> pointerWheelObservable =
System.Reactive.Linq.Observable
.FromEventPattern<PointerEventHandler, PointerRoutedEventArgs>(
handler => _control.PointerWheelChanged += handler,
handler => _control.PointerWheelChanged -= handler)
.Select(eventPattern =>
{
PointerRoutedEventArgs e = eventPattern.EventArgs;
PointerPoint mousePosition = e.GetCurrentPoint(_control);
return mousePosition;
})
.Where(mousePosition => Math.Abs(mousePosition.Properties.MouseWheelDelta) > MouseWheelDeltaThreshold);
// subscribe to wheel changes
pointerWheelObservable
.Throttle(_wheelDeltaThrottleInterval)
.ObserveOnDispatcher()
.Subscribe(
OnPointerWheelChanged,
Logger.TrackException);
pointerWheelObservable
.Throttle(_wheelDeltaCompleteInterval)
.Subscribe(
OnPointerWheelCompleted,
Logger.TrackException);
EDIT2 GestureRecognizer class does not help
See this great blog post regarding Windws 8 manipulations handling.
http://blogs.msdn.com/b/windowsappdev/archive/2012/07/02/modernizing-input-in-windows-8.aspx
Unfortunately after my experiments I see GestureRecognizer is not able to detect mouse wheel events flood is over. It fires ManipulationCompleted event after each call of .ProcessMouseWheelEvent()
You can use Reactive Extension library and throttle on the WheelChangedEvent, that way you would always get the last notification for the specified throttle time period
Use GestureRecognizer for a better low level detection of manipulations including mouse whell.
All inputs (mouse, touch, pen, etc.) are included here and supported better than traditional manipulation events. (they don't support single touch rotation, mouse scroller, etc.)
http://code.msdn.microsoft.com/windowsapps/Input-Windows-8-gestures-62c6689b#content
This is much more efficient, flexible and safer than implementing everything from scratch.