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BSE Syllabus for Pandas...

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.

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