Introduction to Pandas – Panel data structure, Series, Data Frame, indices, datatypes of columns, sorting, copying.
Indexing and selecting data:
Different choices for indexing, Attribute access, slicing, selection by label, selection by position, selection by callable, Boolean indexing.
MultiIndex and advanced indexing,
Merge, join, concatenate and compare Data Frames Reshaping and pivot tables
Working with text data Working with missing data
Grouping:
Splitting an object into groups, Iterating through groups, Selecting a group, Aggregation, Transformation, Filtration.
Time series / date functionality,
Time deltas, Plotting, Handling large datasets
Course outcome (Course Skill Set)
At the end of the course the student will be able to:
1. Perform operations on data structure and data manipulation
2. Develop solutions using matrix method
3. Manage and maintain large data base
Assessment Details (both CIE and SEE)
Continuous internal Examination (CIE)
Three Tests (preferably in MCQ pattern with 20 questions) each of 20 Marks (duration 01 hour)
1. First test at the end of 5th week of the semester
2. Second test at the end of the 10th week of the semester
3. Third test at the end of the 15th week of the semester
Two assignments each of 10 Marks
1. First assignment at the end of 4th week of the semester
2. Second assignment at the end of 9th week of the semester
Quiz/Group discussion/Seminar, any two of three suitably planned to attain the COs and POs for 20 Marks (duration 01 hours)
The sum of total marks of three tests, two assignments, and quiz /seminar/ group discussion will be out of 100 marks and shall be scaled down to 50 marks
Semester End Examinations (SEE)
Suggested Learning Resources:
Books
1. Pandas documentation at https://pandas.pydata.org/pandas-docs/stable/
2. Wes McKinney, Python for Data Analysis, 2ed., O’Reilly Media, 2017.
3. Matt Harrison, Learning the Pandas Library, 2016