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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; 4. Unit Wise syllabus ; Joining, Merging and Concatenation. Unit 2: Database Query using SQL 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  Download, install and configure browser.