CBSE Class 12 Informatics Practices Syllabus 2020 2021 available in Pdf for free download. The latest syllabus for Class 12 Informatics Practices have been issued by CBSE based on which Grade 12 students will have to prepare for examinations by CBSE, NCERT and KVS in Standard 12. The latest CBSE syllabus has been used to design NCERT book for Class 12 Informatics Practices based on which exams for Grade 12 Informatics Practices will be conducted. Refer to MCQ Questions for Class 12 Informatics Practices with answers and also download more latest study material for all subjects
Informatics Practices Class 12 CBSE Syllabus
Class 12 Informatics Practices students should refer to the following curriculum for NCERT Class 12 Informatics Practices. These CBSE NCERT KVS Syllabus for Grade 12 Informatics Practices will be very useful for preparing for upcoming exams and help you to score good marks
Informatics Practices CBSE Syllabus Class 12
CBSE Class 12 Informatics Practices Core Syllabus 2020 2021. Students must always refer to the latest syllabus issued by CBSE before starting studies. Download the latest syllabus for 2020 2021 released by CBSE to plan your studies as per the latest syllabus and guidelines issued by CBSE NCERT. The syllabus, weightage of chapters, blue print of question papers and the design of question papers is issued every year for the benefit of students. Access and download syllabus for all subjects here.
Unit 1: Data Handling using Pandas and Data Visualization
Data Handling using Pandas -I
Introduction to Python libraries- Pandas, Matplotlib.
Data structures in Pandas - Series and Data Frames.
Series: Creation of Series from – ndarray, dictionary, scalar value; mathematical operations; Head and Tail functions; Selection, Indexing and Slicing.
Data Frames: creation - from dictionary of Series, list of dictionaries, Text/CSV files; display; iteration;
Operations on rows and columns: add, select, delete, rename; Head and Tail functions; Indexing using Labels, Boolean Indexing; Joining, Merging and Concatenation.
Importing/Exporting Data between CSV files and Data Frames.
Data handling using Pandas – II
Descriptive Statistics: max, min, count, sum, mean, median, mode, quartile, Standard deviation, variance.
DataFrame operations: Aggregation, group by, Sorting, Deleting and Renaming Index, Pivoting.
Handling missing values – dropping and filling.
Importing/Exporting Data between MySQL database and Pandas.
Data Visualization
Purpose of plotting; drawing and saving following types of plots using Matplotlib – line plot, bar graph, histogram, pie chart, frequency polygon, box plot and scatter plot.
Customizing plots: color, style (dashed, dotted), width; adding label, title, and legend in plots.
Unit 2: Database Query using SQL
Math functions: POWER (), ROUND (), MOD ().
Text functions: UCASE ()/UPPER (), LCASE ()/LOWER (), MID ()/SUBSTRING ()/SUBSTR (),LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT (*).
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