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Read And Plot Data Expectancy in The Python Assignment Solution.


Write a python assignment program to read and plot expectancy.

Requirements and Specifications

Program to read and plot expectancy in python

Source Code

# Your Name

# PA_14

import numpy as np

import matplotlib.pyplot as plt

import re

def build_plot(map):


    Method for building plot from given data dictionary

    :param map: data dictionary

    :return: None


    # getting years values as x-axis

    years = map['Year']

    axes = plt.gca()

    # setting plot view parameters

    axes.set_title('Health Life Expectancy from 2007 to 2017')

    axes.set_xlim(2007, 2017)

    axes.set_ylim(70, 75)



    axes.set_title('Health Life Expectancy from 2007 to 2017')

    # creating graphs for each of country

    plt.plot(np.array(years), np.array(map['Canada']), color="red", linewidth=2, linestyle="-", label='Canada')

    plt.plot(np.array(years), np.array(map['Italy']), color="green", linewidth=2, linestyle="-", label='Italy')

    plt.plot(np.array(years), np.array(map['New Zealand']), color="blue", linewidth=2, linestyle="-", label='New Zealand')

    plt.plot(np.array(years), np.array(map['Spain']), color="black", linewidth=2, linestyle="-", label='Spain')

    # showing legend


    # saving picture as png


    # showing result plot


def read_data(filename):


    Method for reading data from given filename

    :param filename: file to read data from

    :return: dictionary, containing read data


    # result dictionary: maps column name to value list

    result = {}

    # mapping column index to column name

    columns = {}

    # reading csv file

    with open(filename, 'r') as csvfile:

        # reading lines

        lines = csvfile.read().splitlines()

        # removing 'wrong' byte at the beginning of file

        lines[0] = re.sub(r"[^ a-zA-Z,]", "", lines[0])

        # getting headers

        header = lines[0].split(',')

        # processing header values

        for i in range(len(header)):

            columns[i] = header[i]

            result[header[i]] = []

        # parsing line by line and enriching collected data

        for line in lines[1:]:

            parts = line.split(',')

            for i in range(len(parts)):


    return result

if __name__ == '__main__':

    # filename to read data from

    filename = 'HealthyLifeExpectancy.csv'

    # reading data and building plot