Python Assignment Help in Australia

What is Python? 

Python is  a high-level, general purpose computer programming language. It has some unique features such as

• It is a very powerful programming language.
• Python is a object-oriented programme.
• It is
• Python is an open source programming language.
• It can be used for writing quick scripts, stand alone programs and large application prototypes.

Python Assignment Help

Many universities offer Python as part of the study  curriculum. As one might know, assignments are part of every course and act as the testing factor in order to determine the amount of course understood. Python assignments are ought to be done by students pursuing the course. The same come with a lot of challenges like –

• Lack of subject knowledge
• Lack of programming skills
• Unable to understand the assignment clearly
• Lack of time
• Lack of research skills

Career Opportunities 

There are many career opportunities and our experts for Python Assignment Help Australia have noted a few below –

• Programming Expert
• Data Analyst
• Programmer
• Data Scientist
• Software Engineer etc.

The following images depicts the salary range –

Python Programming Assignment 1  

Following is a python sample question solved by our python programming expert –

This exercise is based on a subset of the data collected by the Open University as part of their learning analytics project

The data you need to work on is a file called studentInfo.csv (attached at the end of this section) and which contains the

following fields:-

• code_module – an identification code for a module on which the student is registered.
• code_presentation – the identification code of the presentation during which the student is registered on the module.
• id_student – a unique identification number for the student.
• gender – the student’s gender.
• region – identifies the geographic region, where the student lived while taking the module- presentation.
• highest_education – highest student education level on entry to the module presentation.
• imd_band – specifies the Index of Multiple Deprivation band of the place where the student lived during the module-presentation.
• age_band – band of the student’s age.
• num_of_prev_attempts – the number times the student has attempted this module.
• studied_credits – the total number of credits for the modules the student is currently studying.
• disability – indicates whether the student has declared a disability.
• final_result – student’s final result in the module-presentation.

Your task is to analyse this file with the aim of trying to understand the factors that determine a students final result. Note that you should work on just this one file and do not need to use any of the other datasets collected. Specifically you need to (allocated marks in brackets):

• Summarise and visualise the data. (20%)
• Prepare the dataset for analysis (data cleansing, choose appropriate features to model) etc.. (20%)
• Choose appropriate models for the problem and build, run and evaluate these. You should aim to explore 2 to 3 models, ranging from the basic to the more advanced. (40%)
• Present and interpret the results of your models and relate these to the given problem. (20%)

The work needs to be presented as a 10-page (approximately) report in either PDF or Jupyter notebook format, and should include all the Python code used and developed.

Python Homework Answer –  

Please note, the following is only a preview and not the complete answer –

1. Introduction

This exercise is based on a subset of the data collected by the Open University as part of their learning analytics project. The data set selected contains information about the results of the tests taken by the students. The goal is to analyse the data with the aim of trying to understand the factors that determine a student’s final result. The analysis is done using Python scripting language.

2. Data Setup & Exploration

The data is provided in a CSV format and the file name is studentInfo.csv. A sample data in the file looks like below.

The dataset contains 12 columns and ~32k rows. To load the data into Python environment ‘Pandas’ package is used.

Programming Assignment Help Sample 2

Paper money has been serving the purpose of legal tender for more than thirty decades. However, with the advances in technologies and innovation in fintech solutions, there are non-conventional mode available in the market. Countries like Singapore, Netherlands, France and Sweden account for more than 50% of their transactions as cashless whereas India still does little more than only 2% of her transactions in non-cash (Business Today, 2016). With the objective of moving to cashless economy, curtail the shadow economy and remove the fake currency from market, the Prime Minister, Government of India announced on November 8, 2016 that the higher currency notes of Rs. 500 and Rs. 1000 would not be legal tender anymore from the midnight. The effect of demonetisation brought disruption to the various sector including the banking sector. The move to go towards cashless economy by going digital, has brought a drastic change in the payment systems like ATM Transactions, Mobile Payments, POS, NEFT Transfers, RTGS payment systems etc. It is important to assess how these payment systems have been disrupted after the announcement was made. The demonetisation also had some negative effect on economy for short-term and it is important to assess whether the benefits were worth the cost.

Objective

Impact of demonetisation on the economy (GDP, SME businesses, Sentiment on the Government Policy,

Online payments, Banking industry)

• Use text mining to assess the sentiment of public on digital transactions in general. Do sentiment

analysis at aspect level. Demonetisation is just one of the aspects.

• Role of macro-economic factors (Demonetization, Infrastructure, Literacy etc.)
• Use forecasting to predict the impact of demonetisation on growth of digital transactions (Optional in

part-1).

• Analyzing patterns in various payment modes and how is it affecting the cashless economy objective

(Optional in part-1).

• Analyse the impact of one payment mode on another (Optional in part-1).

Data source

• Social Media (Twitter, News websites, Leaders’ speeches, etc.)
• https://www.npci.org.in/statistics
• Period of analysis: Apr 15 to Mar 18 (3 years data)

Answer

A study on the changes in no of electronics transaction and transaction amount is depicts that a notable fall in the electronics transaction in term of both no and amount and after the demonetization a considerable hike in electronics transfer is found to be noted.

A small table with the four financial year justify the statement –  

A plot (Fig.-1) between the no of transaction through out the three financial year revealed that during the demonetization the no of electronics transaction is considerably fall from the last year and after the demonetization a great hike in electronics transaction is notable from the figure.

Python Assignment Online – Topics

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1. Payroll Shuffle
2. Hurricane Animation
3. String
4. Dictionary
5. Lambda Operator
6. Slots
7. Meta Class
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9. Namespaces
10. Othello Game and many more…

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