• Journal of The Korean Association of Information Education
• /
• v.22 no.1
• /
• pp.53-60
• /
• 2018

In this study we have developed a Python education program that can be applied to students who have studied block-based coding. We have developed a Python education program based on the extracted the learners' level of block-based coding by analyzing the programs and the textbooks. We extracted the grammar of the block-based coding and constructed the curriculum. Then, the Python education program was composed by 16 hours. After reviewing the appropriateness of the education program through expert validation, it was concluded that the developed Python education program is suitable for applying to learners of block-based coding. We expect that proposed program will be effectively applied as basic resources to learn script coding in class.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.141-148
• /
• 2021

The mainstream tool for software education for elementary students is Educational Programming Language. It is essential for upper graders to advance from EPL to text based programming language. However, many students experience difficulty in adopting to this change since Python is run in English. Python is an actively used TPL. This study focuses on developing an education program to facilitate learning Python for Korean speaking students. We have extracted the necessary reserved words needed for data analysis in Python. Then we replaced the extracted words into Korean terms that could be understood in elementary level. The replaced terms were matched on one-to-one correspondence with reserved words used in Python. This devised program would assist students in experiencing data analysis with Python. We expect that this education program will be applied effectively as a basic resource to learn TPL.

• The Pure and Applied Mathematics
• /
• v.29 no.1
• /
• pp.93-102
• /
• 2022

The impact of programming languages in the research sector has helped lot of researchers to broaden their view and extend their work without any limitation. More importantly, even the complex problems can be solved in no matter of time while converting them into a programming language. This convenience provides upper hand for the researchers as it places them in a comfort zone where they can work without much stress. With this context, we have converted the research problems in Topology into programming language with the help of Python. In this paper, we have developed a Python program to find the weaker form of closed sets namely alpha closed set, semi closed set, pre closed set, beta closed set and regular closed set.

• International journal of advanced smart convergence
• /
• v.11 no.4
• /
• pp.68-80
• /
• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of Veterinary Clinics
• /
• v.28 no.4
• /
• pp.446-448
• /
• 2011

A 1-year-old, male, captive born Burmese Python (Python molurus bivittatus) presented with cloudiness of the left eye after ecdysis. Based on physical examination and history, subspectacular abscess was diagnosed. The causative microorganism was identified as a methicillin-resistant Staphylococcus aureus (MRSA). MRSA is a zoonotic problem of high concern and is a risk in public health and veterinary medicine. To our limited knowledge, this is the first reported case of MRSA infection in snakes.

• International journal of advanced smart convergence
• /
• v.11 no.1
• /
• pp.11-18
• /
• 2022

Securities and investment services have and use large data. Investors started to invest through their own analysis methods. There are 22 major securities and investment companies in Korea and only 6 companies support open API. Python is effective for requesting and receiving, analyzing text data from open API. Daishin Securities Co. is the only open API that officially supports Python, and eBest Investment & Securities Co. unofficially supports Python. There are two important differences between CYBOS plus of Daishin Securities Co. and xingAPI of eBest Investment & Securities Co. First, we must log in to CYBOS plus to access the server of Daishin Securities Co. And the python program does not require a logon. However, to receive data using xingAPI, users log on in an individual Python program. Second, CYBOS plus receives data in a Request/Reply method, and zingAPI receives data through events. It can be thought that these points will show a difference in response time. Response time is important to users who use open APIs. Data were measured from August 5, 2021, to February 3, 2022. For each measurement, 15 repeated measurements were taken to obtain 420 measurements. To increase the accuracy of the study, both APIs were measured alternately under same conditions. A paired t-test was performed to test the hypothesis that the null hypothesis is there was no difference in means. The p-value is 0.2961, we do not reject null hypothesis. Therefore, we can see that there is no significant difference between means. From the boxplot, we can see that the distribution of the response time of eBest is more spread out than that of Cybos, and the position of the center is slightly lower. CYBOS plus has no restrictions on Python programming, but xingAPI has some limits because it indirectly supports Python programming. For example, there is a limit to receiving more than one current price.

• Genomics & Informatics
• /
• v.21 no.1
• /
• pp.14.1-14.4
• /
• 2023

OncoPrint, the plot to visualize an overview of genetic variants in sequencing data, has been widely used in the field of cancer genomics. However, still, there have been no Python libraries capable to generate OncoPrint yet, a big hassle to plot OncoPrints within Python-based genetic variants analysis pipelines. This paper introduces a new Python package PyOncoPrint, which can be easily used to plot OncoPrints in Python. The package is based on the existing widely used scientific plotting library Matplotlib, the resulting plots are easy to be adjusted for various needs.

• Journal of Industrial Convergence
• /
• v.18 no.5
• /
• pp.97-101
• /
• 2020

This study intended to analyze effects of education of python through meta-analysis. The researcher selected five primary studies reporting statistical data after implementing education of python in elementary classroom settings. Three research questions were stated. What is the total effect size of education of python? What are effect sizes of publication type, dependent variable, and etc.? What are results of meta-regression analysis by grade level, period, and etc.? Findings are as follows. The overall effect size was .598, which is medium. For categorical variables, the effect size of peer-reviewed journal articles was larger than theses. The effect size of affective domain was larger than student achievement and cognitive domain. For meta-regression analysis, education of python was more effective as the period and duration of the program increased. Finally, discussions and recommendations including qualitative investigation on affective domain and program management considering characteristics were presented regarding research findings.

• International Journal of Advanced Culture Technology
• /
• v.9 no.1
• /
• pp.203-209
• /
• 2021

When carrying out computer programming, the process of checking and correcting errors in the source code is essential work for the completion of the program. Non-computer majors who are learning programming for the first time receive feedback from instructors to correct errors that occur when writing the source code. However, in a learning environment where the time for the learner to practice alone is long, such as an online learning environment, the learner starts to feel many difficulties in solving program errors by himself/herself. Therefore, training on how to check and correct errors after writing the program source code is necessary. In this paper, various types of errors that can occur in a Python program were described, the errors were classified into simple errors and complex errors according to the characteristics of the errors, and the distributions of errors by Python grammar category were analyzed. In addition, a coding learning process to refer error lists was designed to present a coding learning method that enables learners to solve program errors by themselves.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.271-274
• /
• 2019

In this paper, we proposed a detailed address acquisition scheme for automatically collecting data of a web page in a frame that is difficult to access by a general web access method. Using the Python language and the Beautiful Soup library, which can utilize the proposed address resolution technique and the HTML selector, we were able to automatically collect all the bulletin board text data written in several pages. By using the proposed method, we can collect large amount of data automatically by Python web scraping program for web pages of any form of address, and we expect that it can be used for big data analysis.