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Pandas Part-4| iteration| Operations on rows and columns-add, select, delete, rename| CBSE 2020
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A new session with new syllabus is here.
This is the Fourth Part of Python Pandas...
More valuable content is on the way....
In this video we are covering the below syllabus by CBSE for 2020-21 students
Visit Playlist for more....
CBSE Syllabus fot 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.
Follow me on fb @pythonspark
This is the Fourth Part of Python Pandas...
More valuable content is on the way....
In this video we are covering the below syllabus by CBSE for 2020-21 students
Visit Playlist for more....
CBSE Syllabus fot 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.
Follow me on fb @pythonspark
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Pandas Part-4| iteration| Operations on rows and columns-add, select, delete, rename| CBSE 2020
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