{"id":55829,"date":"2023-08-28T16:08:20","date_gmt":"2023-08-28T16:08:20","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/ccs346-exploratory-data-analysis-syllabus-for-csbs-2021-regulation-professional-elective-i\/"},"modified":"2023-08-28T16:08:20","modified_gmt":"2023-08-28T16:08:20","slug":"ccs346-exploratory-data-analysis-syllabus-for-csbs-2021-regulation-professional-elective-i","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/ccs346-exploratory-data-analysis-syllabus-for-csbs-2021-regulation-professional-elective-i\/","title":{"rendered":"CCS346: Exploratory Data Analysis syllabus for CS&BS 2021 regulation (Professional Elective-I)"},"content":{"rendered":"

Exploratory Data Analysis detailed syllabus for Computer Science & Business Systems (CS&BS) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the CS&BS students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Computer Science & Business Systems 5th Sem scheme and its subjects, do visit CS&BS 5th Sem 2021 regulation scheme<\/a>. For Professional Elective-I scheme and its subjects refer to CS&BS Professional Elective-I syllabus scheme<\/a>. The detailed syllabus of exploratory data analysis is as follows. <\/p>\n

Course Objectives:<\/h4>\n

Download the iStudy App for all syllabus and other updates.<\/a>
\"Get<\/a><\/h4>\n

Unit I<\/h4>\n

EXPLORATORY DATA ANALYSIS
\nEDA fundamentals – Understanding data science – Significance of EDA – Making sense of data -Comparing EDA with classical and Bayesian analysis – Software tools for EDA – Visual Aids for EDA- Data transformation techniques-merging database, reshaping and pivoting, Transformation techniques.\n<\/p>\n

Unit II<\/h4>\n

EDA USING PYTHON
\nData Manipulation using Pandas – Pandas Objects – Data Indexing and Selection – Operating on Data – Handling Missing Data – Hierarchical Indexing – Combining datasets – Concat, Append, Merge and Join – Aggregation and grouping – Pivot Tables – Vectorized String Operations.\n<\/p>\n

Unit III<\/h4>\n

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Unit IV<\/h4>\n

BIVARIATE ANALYSIS
\nRelationships between Two Variables – Percentage Tables – Analysing Contingency Tables -Handling Several Batches – Scatterplots and Resistant Lines.\n<\/p>\n

Unit V<\/h4>\n

MULTIVARIATE AND TIME SERIES ANALYSIS
\nIntroducing a Third Variable – Causal Explanations – Three-Variable Contingency Tables and Beyond – Fundamentals of TSA – Characteristics of time series data – Data Cleaning – Timebased indexing – Visualizing – Grouping – Resampling.\n<\/p>\n

Practical Exercises<\/h4>\n
    \n
  1. Install the data Analysis and Visualization tool: R\/ Python \/Tableau Public\/ Power BI.<\/li>\n
  2. Perform exploratory data analysis (EDA) with datasets like email data set. Export all your emails as a dataset, import them inside a pandas data frame, visualize them and get different insights from the data.<\/li>\n
  3. Working with Numpy arrays, Pandas data frames , Basic plots using Matplotlib.<\/li>\n
  4. Explore various variable and row filters in R for cleaning data. Apply various plot features in R on sample data sets and visualize.<\/li>\n
  5. Perform Time Series Analysis and apply the various visualization techniques.<\/li>\n
  6. Perform Data Analysis and representation on a Map using various Map data sets with Mouse Rollover effect, user interaction, etc..<\/li>\n
  7. Build cartographic visualization for multiple datasets involving various countries of the world; states and districts in India etc.<\/li>\n
  8. Perform EDA on Wine Quality Data Set.<\/li>\n
  9. Use a case study on a data set and apply the various EDA and visualization techniques and present an analysis report.<\/li>\n<\/ol>\n

    Course Outcomes:<\/h4>\n

    Download the iStudy App for all syllabus and other updates.<\/a>
    \"Get<\/a><\/h4>\n

    Text Books:<\/h4>\n
      \n
    1. Suresh Kumar Mukhiya, Usman Ahmed, \u201cHands-On Exploratory Data Analysis with Python\u201d, Packt Publishing, 2020. (Unit 1)<\/li>\n
    2. Jake Vander Plas, “Python Data Science Handbook: Essential Tools for Working with Data”, First Edition, O Reilly, 2017. (Unit 2)<\/li>\n
    3. Catherine Marsh, Jane Elliott, \u201cExploring Data: An Introduction to Data Analysis for Social Scientists\u201d, Wiley Publications, 2nd Edition, 2008. (Unit 3,4,5)<\/li>\n<\/ol>\n

      Reference Books:<\/h4>\n
        \n
      1. Eric Pimpler, Data Visualization and Exploration with R, GeoSpatial Training service, 2017.<\/li>\n
      2. Claus O. Wilke, \u201cFundamentals of Data Visualization\u201d, O\u2019reilly publications, 2019.<\/li>\n
      3. Matthew O. Ward, Georges Grinstein, Daniel Keim, \u201cInteractive Data Visualization: Foundations, Techniques, and Applications\u201d, 2nd Edition, CRC press, 2015.<\/li>\n<\/li>\n<\/ol>\n

        For detailed syllabus of all the other subjects of Computer Science & Business Systems 5th Sem, visit CS&BS 5th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n

        For all Computer Science & Business Systems results, visit Anna University CS&BS all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"

        Exploratory Data Analysis detailed syllabus for Computer Science & Business Systems (CS&BS) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the CS&BS […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[146],"tags":[],"class_list":["post-55829","post","type-post","status-publish","format-standard","hentry","category-csbs"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/55829","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=55829"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/55829\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=55829"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=55829"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=55829"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}