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

翻译：Pandas被定义为Python编程语言中用于数据分析的软件库。作为一种快速、简便且开源的数据分析工具，Pandas已被广泛应用于软件开发、机器学习、计算机视觉、自然语言处理、机器人技术等各类软件工程项目中。因此，软件开发者对Pandas表现出极大兴趣，相关讨论在Stack Overflow（SO）等在线开发者论坛中日益占据主导地位。这些讨论有助于了解Pandas库的流行程度，也能帮助理解Pandas主题的重要性、普遍性和难点。本研究论文的主要目的是探究Pandas主题的流行度和难度。为此，我们收集了SO上与Pandas主题讨论相关的帖子，并对帖子的文本内容进行了主题建模。我们发现了26个主题，并将其进一步归纳为5个大类。观察到开发者在SO上讨论了多种Pandas主题，涉及错误与异常处理、可视化、外部支持、数据框及优化。此外，根据预定义时间序列中的讨论趋势生成了趋势图。本文的研究结果可为开发者、教育者和学习者提供指导路径。例如，初学者可以学习构建任何模型必备的关键Pandas主题；教育者可了解学习者认为困难的主题，并编写相关教程以使其易于理解。通过这项实证研究，可以通过处理开发者的SO帖子来把握其对Pandas主题的偏好。