What you'll learn
Initial Analysis of the data using methods or attributes like: Shape, info( ), describe( )etc.
Sort values, unique values, index, mean, reset index, rename column
Data type change for a column/series, Subsetting
Logical OR, Logical AND, isin( ), not isin( )
String methods: copy( ), upper( ), lower( ), title( ), replace( ), split( )
Handling of missing values: isna( ), dropna( ), isna( )
Summary statistics of a numerical column: describe( ), std( ), var( ), boxDescription( )
Linspace( )
Slicing using loc and iloc
groupby, query( ), division of values of a column/series by values in another column/series
MatDescriptionlib: Descriptionting basic graphs, customizations (marker size, line width, xlabel, ylabel, title)
Subplopts, subDescriptions with same Y-axis, subDescriptions with same X-axis
MatDescriptionlib: histogram, bargraph, boxDescription, scatter Description
MatDescriptionlib: style sheets, saving Description/figures
Description
This course will help you to learn and understand Data exploration in python and basic Descriptions of MatDescriptionlib for better visualization of the dataset.
The python version used in this course is 3.8.5
This course is designed for students who have zero to basic knowledge of Python. All the methods, attributes, Descriptions, graphs, customizations are explained from scratch.
The first part of the course mainly focuses on data analysis and will help you to understand functions/methods that you may need to use to explore your dataset in its entirety.
Further, some part focuses on cleansing as well like handling duplicate and missing values.
The structure for the Data exploration (first part) is:-
Initial Analysis of the data using methods or attributes like: Shape, info( ), describe( )etc.
Sort values, unique values, index, mean, reset index, rename column
Data type change for a column/series, Subsetting
Logical OR, Logical AND, isin( ), not isin( )
String methods: copy( ), upper( ), lower( ), title( ), replace( ), split( )
Handling of missing values: isna( ), dropna( ), isna( )
Summary statistics of a numerical column: describe( ), std( ), var( ), boxDescription( )
Linspace( )
Slicing using loc and iloc
groupby, query( ), division of values of a column/series by values in another column/series
The second part mainly focuses on Descriptions/graphs of MatDescriptionlib:-
MatDescriptionlib: Descriptionting basic graphs, customizations (marker size, line width, xlabel, ylabel, title)
Subplopts, subDescriptions with same Y-axis, subDescriptions with same X-axis
MatDescriptionlib: histogram, bargraph, boxDescription, scatter Description
MatDescriptionlib: style sheets, saving Description/figures

Homepage

https://www.udemy.com/course/python-bootcamp-data-exploration-and-matDescriptionlib-Descriptions/

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