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An Empirical Study on How the Developers Discussed about Pandas Topics
Software Engineering · Submitted 7 Oct 2022
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim From this empirical study it is possible to understand the preferences of developers in pandas topic by processing their SO posts
The compiled record
The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
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The abstract, sentence by sentence
Pandas is defined as a software library which is used for data analysis in Python programming language. As pandas is a fast, easy and open source data analysis tool, it is rapidly used in different software engineering projects like software development, machine learning, computer vision, natural language processing, robotics, and others. So a huge interests are shown in software developers regarding pandas and a huge number of discussions are now becoming dominant in online developer forums, like Stack Overflow (SO). Such discussions can help to understand the popularity of pandas library and also can help to understand the importance, prevalence, difficulties of pandas topics. The main aim of this research paper is to find the popularity and difficulty of pandas topics. For this regard, SO posts are collected which are related to pandas topic discussions. Topic modeling are done on the textual contents of the posts. We found 26 topics which we further categorized into 5 board categories. We observed that developers discuss variety of pandas topics in SO related to error and excepting handling, visualization, External support, dataframe, and optimization. In addition, a trend chart is generated according to the discussion of topics in a predefined time series. The finding of this paper can provide a path to help the developers, educators and learners. For example, beginner developers can learn most important topics in pandas which are essential for develop any model. Educators can understand the topics which seem hard to learners and can build different tutorials which can make that pandas topic understandable. From this empirical study it is possible to understand the preferences of developers in pandas topic by processing their SO posts
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Pandas is defined as a software library which is used for data analysis in Python programming language. | background 1.00 | 0.04 | 0.01 | asserted 1.00 |
| s1 | As pandas is a fast, easy and open source data analysis tool, it is rapidly used in different software engineering projects like software development, machine learning, computer vision, natural language processing, robotics, and others. | background 1.00 | 0.06 | 0.02 | asserted 1.00 |
| s2 | So a huge interests are shown in software developers regarding pandas and a huge number of discussions are now becoming dominant in online developer forums, like Stack Overflow (SO). | background 1.00 | 0.08 | 0.02 | asserted 1.00 |
| s3 | Such discussions can help to understand the popularity of pandas library and also can help to understand the importance, prevalence, difficulties of pandas topics. | background 0.90 | 0.07 | 0.03 | hedged possibility 0.68 |
| s4 | The main aim of this research paper is to find the popularity and difficulty of pandas topics. | contribution 0.93 | 0.20 | 0.04 | asserted 0.99 |
| s5 | For this regard, SO posts are collected which are related to pandas topic discussions. | method 0.99 | 0.90 | 0.02 | asserted 0.99 |
| s6 | Topic modeling are done on the textual contents of the posts. | method 1.00 | 0.92 | 0.02 | asserted 0.99 |
| s7 | We found 26 topics which we further categorized into 5 board categories. | result 0.96 | 0.97 | 0.08 | asserted 1.00 |
| s8 | We observed that developers discuss variety of pandas topics in SO related to error and excepting handling, visualization, External support, dataframe, and optimization. | result 1.00 | 0.94 | 0.19 | asserted 1.00 |
| s9 | In addition, a trend chart is generated according to the discussion of topics in a predefined time series. | method 0.60 | 0.94 | 0.04 | asserted 0.99 |
| s10 | The finding of this paper can provide a path to help the developers, educators and learners. | interpretation 0.89 | 0.46 | 0.22 | hedged possibility 0.53 |
| s11 | For example, beginner developers can learn most important topics in pandas which are essential for develop any model. | interpretation 0.92 | 0.11 | 0.05 | hedged possibility 0.49 |
| s12 | Educators can understand the topics which seem hard to learners and can build different tutorials which can make that pandas topic understandable. | interpretation 0.90 | 0.10 | 0.06 | asserted 0.51 |
| s13 | From this empirical study it is possible to understand the preferences of developers in pandas topic by processing their SO posts | interpretation 0.72 | 0.75 | 0.39 | hedged possibility 0.96 |
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The paper
Original abstract
Pandas is defined as a software library which is used for data analysis in Python programming language. As pandas is a fast, easy and open source data analysis tool, it is rapidly used in different software engineering projects like software development, machine learning, computer vision, natural language processing, robotics, and others. So a huge interests are shown in software developers regarding pandas and a huge number of discussions are now becoming dominant in online developer forums, like Stack Overflow (SO). Such discussions can help to understand the popularity of pandas library and also can help to understand the importance, prevalence, difficulties of pandas topics. The main aim of this research paper is to find the popularity and difficulty of pandas topics. For this regard, SO posts are collected which are related to pandas topic discussions. Topic modeling are done on the textual contents of the posts. We found 26 topics which we further categorized into 5 board categories. We observed that developers discuss variety of pandas topics in SO related to error and excepting handling, visualization, External support, dataframe, and optimization. In addition, a trend chart is generated according to the discussion of topics in a predefined time series. The finding of this paper can provide a path to help the developers, educators and learners. For example, beginner developers can learn most important topics in pandas which are essential for develop any model. Educators can understand the topics which seem hard to learners and can build different tutorials which can make that pandas topic understandable. From this empirical study it is possible to understand the preferences of developers in pandas topic by processing their SO posts
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