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tiniest-analytics | simple cross-platform C analytics for games | Analytics library

 by   Pintea C++ Version: 1.1 License: MIT

 by   Pintea C++ Version: 1.1 License: MIT

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kandi X-RAY | tiniest-analytics Summary

tiniest-analytics is a C++ library typically used in Analytics, React Native, Raspberry Pi applications. tiniest-analytics has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
VERY simple cross-platform C++ analytics for games (using Google Analytics)
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Quality
Quality
Security
Security
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kandi-support Support

  • tiniest-analytics has a low active ecosystem.
  • It has 92 star(s) with 14 fork(s). There are 6 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 2 open issues and 2 have been closed. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of tiniest-analytics is 1.1
tiniest-analytics Support
Best in #Analytics
Average in #Analytics
tiniest-analytics Support
Best in #Analytics
Average in #Analytics

quality kandi Quality

  • tiniest-analytics has no bugs reported.
tiniest-analytics Quality
Best in #Analytics
Average in #Analytics
tiniest-analytics Quality
Best in #Analytics
Average in #Analytics

securitySecurity

  • tiniest-analytics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tiniest-analytics Security
Best in #Analytics
Average in #Analytics
tiniest-analytics Security
Best in #Analytics
Average in #Analytics

license License

  • tiniest-analytics is licensed under the MIT License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
tiniest-analytics License
Best in #Analytics
Average in #Analytics
tiniest-analytics License
Best in #Analytics
Average in #Analytics

buildReuse

  • tiniest-analytics releases are available to install and integrate.
tiniest-analytics Reuse
Best in #Analytics
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tiniest-analytics Reuse
Best in #Analytics
Average in #Analytics
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tiniest-analytics Key Features

VERY simple cross-platform C++ analytics for games (using Google Analytics)

tiniest-analytics Examples and Code Snippets

No Code Snippets are available at this moment for tiniest-analytics.

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Community Discussions

Trending Discussions on Analytics
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Trending Discussions on Analytics

QUESTION

Lottery analysis for learning

Asked 2022-Mar-31 at 15:00

I'm trying to learn how to use the pandas library.

For the data source, I use the lottery combinations draws so far.

One of many tasks I'm trying to solve is to count the frequency of pairs of numbers in combinations.

I create a data frame from the list like this:

list = [
    [13, 14, 28, 30, 31, 37, 39],
    [7, 10, 12, 16, 21, 22, 33],
    ...,
    [1, 2, 7, 15, 25, 31, 33],
    [3, 6, 18, 21, 31, 34, 39]
]

df = pd.DataFrame(list)
print(df.head())

Output:

.   0   1   2   3   4   5   6
0   9  11  12  18  20  26  35
1  10  13  15  20  21  25  35
2   1   8  17  21  22  27  34
3  10  13  17  18  21  29  37
4   5   8  12  17  19  21  37

For example, as a result I want to get the sum of how much time tuples of two or three numbers appear together in combinations:

Pair  : Found n time in all combinations
9,23  : 33
11,32 : 26

Can you give me some directions or example how to solve this task, please?

ANSWER

Answered 2022-Mar-12 at 15:09

Here is a simple solution using just modules from the standard library:

from itertools import combinations
from collections import Counter

draws = [
    [13, 14, 28, 30, 31, 37, 39],
    [7, 10, 12, 16, 21, 22, 33],
    [1, 2, 7, 15, 25, 31, 33],
    [3, 6, 18, 21, 31, 34, 39]
]

duos = Counter()
trios = Counter()

for draw in draws:
    duos.update(combinations(draw, 2))
    trios.update(combinations(draw, 3))

print('Top 5 duos')
for x in duos.most_common(5):
    print(f'{x[0]}: {x[1]}')

print()

print('Top 5 trios')
for x in trios.most_common(5):
    print(f'{x[0]}: {x[1]}')

The code snippet above will result in the following output:

Top 5 duos
(31, 39): 2
(7, 33): 2
(13, 14): 1
(13, 28): 1
(13, 30): 1

Top 5 trios
(13, 14, 28): 1
(13, 14, 30): 1
(13, 14, 31): 1
(13, 14, 37): 1
(13, 14, 39): 1

And here is a slightly more elegant version:

from itertools import combinations
from collections import Counter

draws = [
    [13, 14, 28, 30, 31, 37, 39],
    [7, 10, 12, 16, 21, 22, 33],
    [1, 2, 7, 15, 25, 31, 33],
    [3, 6, 18, 21, 31, 34, 39]
]

counters = [Counter() for _ in range(3)]

for n, counter in enumerate(counters, 2):
    for draw in draws:
        counter.update(combinations(draw, n))

    print(f'Top 10 combos of {n} numbers')

    for combo, count in counter.most_common(10):
        print(' '.join((f'{_:2d}' for _ in combo)), count, sep=': ')

    print()

Which will give us the following output:

Top 10 combos of 2 numbers
31 39: 2
 7 33: 2
13 14: 1
13 28: 1
13 30: 1
13 31: 1
13 37: 1
13 39: 1
14 28: 1
14 30: 1

Top 10 combos of 3 numbers
13 14 28: 1
13 14 30: 1
13 14 31: 1
13 14 37: 1
13 14 39: 1
13 28 30: 1
13 28 31: 1
13 28 37: 1
13 28 39: 1
13 30 31: 1

Top 10 combos of 4 numbers
13 14 28 30: 1
13 14 28 31: 1
13 14 28 37: 1
13 14 28 39: 1
13 14 30 31: 1
13 14 30 37: 1
13 14 30 39: 1
13 14 31 37: 1
13 14 31 39: 1
13 14 37 39: 1

Source https://stackoverflow.com/questions/71449837

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tiniest-analytics

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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