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## Informatics Practices – 065

### Class XI – Topics Reduced / Revised

CBSE has revised to reduced the syllabus for Informatics Practices (IP) students for class XI and XII, keeping in mind the situation being created due to covid19.

#### 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
NumPy arrays.

#### Unit 4: Database concepts and the Structured Query Language

• Foreign key.
• 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.

### Class XII – Topics Reduced / Revised

#### Unit-1 Data handling using Pandas – II

• Descriptive Statistics: max, min, count, sum, mean, median, mode, quartile, Standard
deviation, variance.
• Data Frame 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
• pie chart, frequency polygon, box plot and scatter plot.
• color, style (dashed, dotted), width, etc

#### 4. Unit Wise syllabus

• Joining, Merging and Concatenation.

#### Practical

• Create a data frame based on ecommerce data and generate descriptive statistics
(mean, median, mode, quartile, and variance)
• Create a data frame for examination result and display row labels, column labels data
types of each column and the dimensions
• Filter out rows based on different criteria such as duplicate rows.
• Find the sum of each column, or find the column with the lowest mean.
• Locate the 3 largest values in a data frame.
• Subtract the mean of a row from each element of the row in a Data Frame.
• Replace all negative values in a data frame with a 0.
• Replace all missing values in a data frame with a 999.
• Importing and exporting data between pandas and CSV file
• Importing and exporting data between pandas and MySQL database
• 5.3 Data Management
• Create a new table (order ID, customer Name, and order Date) by joining two tables
(orderID, customer ID, and order Date) and (customer ID, customer Name, contact
Name, country).
• Create a foreign key in one of the two tables mentioned above
• Create a new table (name, date of birth) by joining two tables (student id, name) and
(student id, date of birth).

#### 5.4 Introduction to Computer Networks 