DataScience Task2 - Python

import numpy as np
import pandas as pd

def findMaxPrimeNum(array):
  return array[array % 2 == 0].max()
# Test1
print(findMaxPrimeNum(np.arange(0, 99, 3)))

def findZeroPrefixMax(array):
  return array[list(filter(lambda i: array[i + 1] == 0 and array[i] != 0, range(0, array.size - 1)))].max()
# Test2
array = np.array([6, 2, 0, 3, 0, 0, 5, 7, 0])
print(findZeroPrefixMax(array))

def getSuperDuperRepeatArray(array):
  return np.repeat(array, array)
# Test3
print(getSuperDuperRepeatArray(np.array([0, 1, 2, 3, 4, 5])))

def getPolyderPolynomValueOfX(vector, x):
  return np.polyval(np.polyder(np.poly(vector)), x)
# Test4
print(getPolyderPolynomValueOfX(np.array([3, 4, 7]), 1))

def isEqualSumColumnsAndTables(array):
  return np.all(array.sum(axis=0) == array.sum(axis=1))
# Test5
print(isEqualSumColumnsAndTables(np.array([[1, 1], [1, 1]])))

def getCorrectDataFrame(dataFrame):
  return dataFrame.where(dataFrame != None, 0)
# Test 6
print(getCorrectDataFrame(
  pd.read_csv('road_data.csv',
  sep = ',', header = 0, names =
  ['cars', 'accidents', 'vodka', 'crime', 'income', 'retail']
)))

def getFilteredDataFrame(dataFrame):
  return dataFrame[
  (dataFrame.accidents > 150) &
  ((dataFrame.vodka > 10) | (dataFrame.crime > 1000))
  ].sort_values('accidents', ascending=0)
# Test 7
print(getFilteredDataFrame(pd.read_csv('road_data.csv',
  sep = ',', header = 0, names =
  ['cars', 'accidents', 'vodka', 'crime', 'income', 'retail']
)))