I am trying to make an auctions system but can not figure out the logical conditions for doing so..
Lets say that I have 10 credit
$credit
I have already bet 5 credits on another auction... so I owe 5 from 10 $owe
I thus have 5 available... $available = $credit - $owe (=5)
I bet 3 from available (on a different item)...
I wish to bet again 4 (cancel 3, update to 4), but credit available is now $available - 3 (=2)
Can't find a logical solution.... written in code.
What is the condition for setting a bet???
Made up a matrix with the dependence between variables:
bet available owe lastbet
1 10 10 0
2 9 11 1
3 7 13 2
4 4 16 3
5 0 20 4
6 -5 25 5
7 -11 31 6
8 -18 38 7
9 -26 46 8
10 -35 55 9
11 -45 65 10
Need to translate it into a condition statement.... (the next row would not meet the conditions)
The condition should fail on the 11th row....
Based on the Matrix... I found out that the condition is:
if ($bet <= (($owe + $available) / 2)) {}
Not very intuitive......
Related
I have a table with two columns:
sort_column = A column I use for sorting
value_column = My metric of interest (a positive integer)
Using SQL, I need to create contiguous groups of rows, ordered by sort_column, such that the sum of value_column within each group is the largest possible but staying below 100 (100 not included).
Find below an example of my desired result.
Thanks
sort_column
value_column
desired_result
1
53
1
2
25
1
3
33
2
4
25
2
5
10
2
6
46
3
7
9
3
8
49
4
9
48
4
10
53
5
11
33
5
12
52
6
13
29
6
14
16
6
15
66
7
16
1
7
17
62
8
18
57
9
19
47
10
20
12
10
Ok, so after a few lengthy attempts, I came to the conclusion the task is impossible with pure SQL, because a given value of the desired column depends on previous values of that same column, in a way that cannot be obtained from the first two columns alone, so the problem is impossible to tackle without using a recursive CTE, which BigQuery does not support.
I solved the issue by writing a javascript UDF for the task. It seems to be working fine and produces the expected results.
Many thanks everyone!
In pandas.DataFrame.filter is there a way to use the parameters "like" or "regex" so they support an OR condition. for example:
df.filter(like='bbi', axis=1)
would filter on columns with bbi in their name, but how would I filter on columns containing 'bbi' OR 'abc' ?
A few options that fail:
df.filter(like='bbi' or 'abc', axis=1)
df.filter(like=('bbi' or 'abc'), axis=1)
I would do the below:
Setup:
df=pd.DataFrame(np.random.randint(0,20,20).reshape(5,4),
columns=['abcd','bcde','efgh','bbia'])
print(df)
abcd bcde efgh bbia
0 10 17 2 7
1 7 12 18 9
2 17 7 11 17
3 14 4 2 9
4 15 10 12 11
Solution:
Using df.filter:
df.filter(regex=r'(abc|bbi)')
abcd bbia
0 10 7
1 7 9
2 17 17
3 14 9
4 15 11
Not familiar with the filter command. But you could achieve what you want like this I think:
df[(df['column'].str.contains('bbi', case=False)) | (df['column'].str.contains('abc', case=False))]
Please find the attached screenshot.
Regex search is slower. So we keep regex=False.
Hope this helps.Thank you.
In this dataframe, column key values correspond to integer notation of each song key.
df
track key
0 Last Resort 4
1 Casimir Pulaski Day 8
2 Glass Eyes 8
3 Ohio - Live At Massey Hall 1971 7
4 Ballad of a Thin Man 11
5 Can You Forgive Her? 11
6 The Only Thing 3
7 Goodbye Baby (Baby Goodbye) 4
8 Heart Of Stone 0
9 Ohio 0
10 the gate 2
11 Clampdown 2
12 Cry, Cry, Cry 4
13 What's Happening Brother 8
14 Stupid Girl 11
15 I Don't Wanna Play House 7
16 Inner City Blues (Make Me Wanna Holler) 11
17 The Lonesome Death of Hattie Carroll 4
18 Paint It, Black - (Original Single Mono Version) 5
19 Let Him Run Wild 11
20 Undercover (Of The Night) - Remastered 5
21 Between the Bars 7
22 Like a Rolling Stone 0
23 Once 2
24 Pale Blue Eyes 5
25 The Way You Make Me Feel - 2012 Remaster 1
26 Jeremy 2
27 The Entertainer 7
28 Pressure 9
29 Play With Fire - Mono Version / Remastered 2002 2
30 D-I-V-O-R-C-E 9
31 Big Shot 0
32 What's Going On 1
33 Folsom Prison Blues - Live 0
34 American Woman 1
35 Cocaine Blues - Live 8
36 Jesus, etc. 5
the notation is as follows:
'C' --> 0
'C#'--> 1
'D' --> 2
'Eb'--> 3
'E' --> 4
'F' --> 5
'F#'--> 6
'G' --> 7
'Ab'--> 8
'A' --> 9
'Bb'--> 10
'B' --> 11
what is specific about this notation is that 11 is closer to 0 than 2, for instance.
GOAL:
given an input_notation = 0, I would like to sort according to closeness to key 0, or 'C'.
you can get closest value by doing:
closest_key = (input_notation -1) % 12
so I would like to sort according to this logic, having on top input_notation values and then closest matches, like so:
8 Heart Of Stone 0
9 Ohio 0
22 Like a Rolling Stone 0
31 Big Shot 0
33 Folsom Prison Blues - Live 0
(...)
I have tried:
v = df[['key']].values
df = df.iloc[np.lexsort(np.abs(v - (input_notation - 1) %12 ).T)]
but this does not work..
any clues?
You can define the closeness firstly and then use argsort with iloc to sort the data frame:
input_notation = 0
# define the closeness or distance
diff = (df.key - input_notation).abs()
closeness = np.minimum(diff, 12 - diff)
# use argsort to calculate the sorting index, and iloc to reorder the data frame
closest_to_input = df.iloc[closeness.argsort(kind='mergesort')]
closest_to_input.head()
# track key
#8 Heart Of Stone 0
#9 Ohio 0
#22 Like a Rolling Stone 0
#31 Big Shot 0
#33 Folsom Prison Blues - Live 0
I need to create a new transport ID based on the cumulative sum of the volume being transported. Let´s say that originally everything was transported in truck A with a capacity of 25. Now I want to assign these items to shipments with truck B (Capacity 15).
The only real constraint is amt shipped cannot exceed capacity.
I can´t post a picture because of the restrictions...but the overall set up would be like this:
Old Trans # Volume New Trans # Cumulative Volume for Trans
1 1
1 9
1 3
1 7
1 4
2 9
2 10
3 8
3 5
3 9
4 4
4 6
4 8
5 9
5 1
5 5
5 8
6 3
6 4
6 3
6 4
6 4
6 7
7 7
7 10
7 4
8 10
8 6
8 7
9 4
9 9
9 6
10 7
10 4
10 1
10 1
10 5
10 2
11 9
11 3
11 9
12 8
12 5
12 9
13 9
Expected output would be that the first three entries would result in a new shipment ID of 1;the next two entries would result in a new shipment ID of 2;and so on... I´ve tried everthing that I know(excluding VBA): Index/lookup/if functions. My VBA skills are very limited though.Any tips?? thanks!
I think I see what you're trying to do here, and just using an IF formula (and inserting a new column to keep track):
In the Columns C and D, insert these formulas in row 3 and copy down (changing 15 for whatever you want your new volume capacity to be):
Column C: =IF(B3+C2<15,B3+C2,B3)
Column D: =IF(B3+C2<15,D2,D2+1)
And for the cells C2 and D2:
C2: = B2
D2: = A2
Is this what you're looking to do?
A simple formula could be written that 'floats' the range totals for each successive load ID.
In the following, I've typed 25 and 15 in D1:E1 and used a custom number format of I\D 0. In this way, the column is identified and the cell can be referenced as a true number load limit. You can hard-code the limits into the formula if you prefer by overwriting D$1 but you will not have a one-size-fits-all formula that can be copied right for alternate load limits as I have in my example..
The formula in D2 is,
=IF(ROW()=2, 1, (SUM(INDEX($B:$B, MATCH(D1, D1:D$1, 0)):$B2)>D$1)+ D1)
Fill right to E2 then down as necessary.
Let's assume we have the following:
A
1 10
2 20
3 30
4 20
5 10
6 30
7 20
8
9
10 =(AVERAGE(A1:A7)
11 4
12 6
I would like to be able to find a way to calculate the Average of A1-A7 into cell A10 while excluding row range defined in A11 and A12. That is, according to the above setup the result should be 20:
((10 + 20 + 30 + 20) / 4) = 20
because if rows 4,5 and 6 are excluded what's left is rows 1,2,3,7 to be averaged.
Two other options:
=AVERAGE(FILTER(A1:A7,ISNA(MATCH(ROW(A1:A7),A11:A12,0))))
=ArrayFormula(AVERAGEIF(MATCH(ROW(A1:A7),A11:A12,0),NA(),A1:A7))
Seems to meet your requirement, though not flexible:
=(sum(A1:A7)-indirect("A"&A11)-indirect("A"&A12))/(count(A1:A7)-2)
Adjust re misunderstanding of requirements:
=(SUM(A1:A7)-SUM(INDIRECT("A"&A11&":A"&A12)))/(COUNT(A1:A7)-A12+A11-1)