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import matplotlib.pyplot as plt

def myplot(x, y, **kwargs):
    plt.plot(x, y, **kwargs)
    plt.xlabel('X')
    plt.ylabel('Y')
    plt.title('My plot')
    plt.show()

x = [1, 3, 4, 5]

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import numpy as np
import matplotlib.pyplot as plt

n = 100
x = np.arange(n)
plt.plot(x, x, label='linear')
plt.plot(x, 2*x, label='double')
plt.plot(x, x*x, label='square')
plt.plot(x, x**3, label='power')
plt.grid()

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Config your Conky with simple bash script

INTRO

disclaimer

not to be taken seriously!

requirements

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PostgreSQL is Enough

https://www.postgresql.org

https://sive.rs/pg

Background Jobs

• https://github.com/citusdata/pg_cron

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rhoit

#!../venv/bin/python

import pandas as pd
import mlxtend.preprocessing
import mlxtend.frequent_patterns

# 1. Prepare the dataset (list of lists)
dataset = [
    {'Butter', 'Bread', 'Milk'},
    {'Bread', 'Milk'},

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rhoit

#!/usr/bin/python

import argparse
import itertools
import collections


def get_frequent_itemsets(transactions, min_support):
    # Count individual items
    freq = collections.defaultdict(int)

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#!/usr/bin/python

import argparse
import itertools
import collections


sample = [
    ['Butter', 'Bread', 'Milk'],
    ['Bread', 'Milk'],

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