Informatics Practices – 065
Unit 3: Data Handling using NumPy
Data and its purpose, importance of data, structured and unstructured data, data processing
cycle, basic statistical methods for understanding data – mean, median, mode, standard
deviation and variance.
Introduction to NumPy library, NumPy arrays and their advantage, creation of NumPy arrays;
indexing, slicing, and iteration; concatenating and splitting array
Arithmetic operations on one Dimensional and two Dimensional arrays.
Calculating max, min, count, sum, mean, median, mode, standard deviation, variance on
Unit 4: Database concepts and the Structured Query Language
DROP TABLE, ALTER TABLE.
, UPDATE, DELETE
5.2 Numpy Program
To create an array of 1D containing numeric values 0 to 9.
To create a NumPy array with all values as 0.
To extract values at odd numbered position from a NumPy array.
To create a 1-D array having 12 elements using arange(). Now, convert this array into a 2-D
array with size 4X3.
To perform basic arithmetic operations on 1D and 2D array .
5.3 Data Management: SQL Commands
To delete the details of a student in the above table.
To increase marks by 5% for those students who have Rno more than 20.
To add a new column email in the above table with appropriate data type.
To add the email ids of each student in the previously created email column.