Python for Data Science Training Program

Introduction To Python

• Installation and Working with Python

• Understanding Python variables

• Python basic Operators

• Understanding the Python blocks.

Python Keyword and Identiers

• Python Keyword and Identiers

• Python Comments, Multiline Comments.

• Python Indentation

• Understating the concepts of Operators
• Arithmetic
• Relational
• Logical
• Assignment
• Membership
• Identity

Introduction To Variables

• Variables, expression condition and function

• Global and Local Variables in Python

• Packing and Unpacking Arguments

• Type Casting in Python

• Byte objects vs. string in Python

• Variable Scope

Python Data Type

• Declaring and using Numeric data types

• Using string data type and string operations

• Understanding Non-numeric data types

• Understanding the concept of Casting and Boolean.

• Strings

• List

• Tuples

• Dictionary

• Sets

Control Structure & Flow

• Statements – if, else, elif

• How to use nested IF and Else in Python

• Loops

• Loops and Control Statements.

• Jumping Statements – Break, Continue, pass

• Looping techniques in Python

• How to use Range function in Loop

• Programs for printing Patterns in Python

• How to use if and else with Loop

• Use of Switch Function in Loop

• Elegant way of Python Iteration

• Generator in Python

• How to use nested Loop in Python

• Use If and Else in for and While Loop

• Examples of Looping with Break and Continue Statement

• How to use IN or NOT IN keyword in Python Loop.

Python Function, Modules and Packages

• Python Syntax

• Function Call

• Return Statement

• Arguments in a function – Required, Default, Positional, Variable-length

• Write an Empty Function in Python –pass statement.

• Lamda/ Anonymous Function

• *args and **kwargs

• Help function in Python

• Scope and Life Time of Variable in Python Function

• Nested Loop in Python Function

• Recursive Function and Its Advantage and Disadvantage

• Organizing python codes using functions

• Organizing python projects into modules

• Importing own module as well as external modules

• Understanding Packages

• Random functions in python

• Programming using functions, modules & external packages

• Map, Filter and Reduce function with Lambda Function

• More example of Python Function

Python Date Time and Calendar

• Day, Month, Year, Today, Weekday

• IsoWeek day

• Date Time

• Time, Hour, Minute, Sec, Microsec

• Time Delta and UTC

• StrfTime, Now

• Time stamp and Date Format

• Month Calendar

• Itermonthdates

• Lots of Example on Python Calendar

• Create 12-month Calendar

• Strftime

• Strptime

• Format Code list of Data, Time and Cal

• Locale’s appropriate date and time

List

• What is List.

• List Creation

• List Length

• List Append

• List Insert

• List Remove

• List Append & Extend using “+” and Keyword

• List Delete

• List related Keyword in Python

• List Revers

• List Sorting

• List having Multiple Reference

• String Split to create a List

• List Indexing

• List Slicing

• List count and Looping

• List Comprehension and Nested Comprehension

Tuple

• What is Tuple

• Tuple Creation

• Accessing Elements in Tuple

• Changing a Tuple

• Tuple Deletion

• Tuple Count

• Tuple Index

• Tuple Membership

• TupleBuilt in Function (Length, Sort)

Dictionary

• Dict Creation

• Dict Access (Accessing Dict Values)

• Dict Get Method

• Dict Add or Modify Elements

• Dict Copy

• Dict From Keys.

• Dict Items

• Dict Keys (Updating, Removing and Iterating)

• Dict Values

• Dict Comprehension

• Default Dictionaries

• Ordered Dictionaries

• Looping Dictionaries

• Dict useful methods (Pop, Pop Item, Str , Update etc.)

Sets

• What is Set

• Set Creation

• Add element to a Set

• Remove elements from a Set

• PythonSet Operations

• Frozen Sets

Strings

• What is Set

• Set Creation

• Add element to a Set

• Remove elements from a Set

• PythonSet Operations

Python Exception Handling

• Python Errors and Built-in-Exceptions

• Exception handing Try, Except and Finally

• Catching Exceptions in Python

• Catching Specic Exception in Python

• Raising Exception

• Try and Finally

Python File Handling

• Opening a File

• Python File Modes

• Closing File

• Writing to a File

• Reading from a File

• Renaming and Deleting Files in Python

• Python Directory and File Management

• List Directories and Files

• Making New Directory

• Changing Directory

Python Database Interaction

• SQL Database connection using

• Creating and searching tables

• Reading and Storing cong information on database

• Programming using database connections

Contacting user Through Emails Using Python

• Installing SMTP Python Module

• Sending Email

• Reading from le and sending emails to all users

Reading an excel

• Working With Excel

• Reading an excel le using Python

• Writing to an excel sheet using Python

• Python| Reading an excel le

• Python | Writing an excel le

• Adjusting Rows and Column using Python

• ArithmeticOperation in Excel le.

• Play with Workbook, Sheets and Cells in Excel using Python

• Creating and Removing Sheets

• Formatting the Excel File Data

• More example of Python Function

Complete Understanding of OS Module of Python

• Check Dirs. (exist or not)

• How to split path and extension

• How to get user prole detail

• Get the path of Desktop, Documents, Downloads etc.

• Handle the File System Organization using OS

• How to get any les and folder’s details using OS

Statistics

• Categorical Data

• Numerical Data

• Mean

• Median

• Mode

• Outliers

• Range

• Interquartile range

• Correlation

• Standard Deviation

• Variance

• Box plot

Pandas

• Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les

• How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function

• Using the Excel File class to read multiple sheets More Mapping, Filling

• Nonvalue’s

• Exploring the Data Plotting, Correlations, and Histograms

• Getting statistical information about the data Analysis Concepts, Handle the None Values

• Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

• Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

• Applying formulas on the columns Basic Grouping, Concepts of Aggre

• gate Function

• Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)

• Under sting the Properties of Pivot Table in Pandas Advanced Reading

• CSVs/HTML, Binning, Categorical Data

• Exporting the results to Excel Joins:

• Python | Pandas Data Frame Inner Join

• Under sting the properties of Data Frame Left Join (Left Outer Join)

• Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

• Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

• Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data

• Pandas | How to Group Data How to apply Lambda / Function on Data

• Frame

• Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

NumPy

• Introduction to NumPy: Numerical Python

• Importing NumPy and Its Properties

• NumPy Arrays

• Creating an Array from a CSV

• Operations an Array from a CSV

• Operations with NumPy Arrays

• Two-Dimensional Array

• Selecting Elements from 1-D Array

• Selecting Elements from 2-D Array

• Logical Operation with Arrays

• Indexing NumPy elements using conditionals

• NumPy’s Mean and Axis

• NumPy’s Mode, Median and Sum Function

• NumPy’s Sort Function and More

MatPlotLib

• Bar Chart using Python MatPlotLib

• Column Chart using Python MatPlotLib

• Pie Chart using Python MatPlotLib

• Area Chart using Python MatPlotLib

• Scatter Plot Chart using Python MatPlotLib

• Play with Charts Properties Using MatPlotLib

• Export the Chart as Image

• Understanding plt. subplots () notation

• Legend Alignment of Chart using MatPlotLib

• Create Charts as Image

• Other Useful Properties of Charts.

• Complete Understanding of Histograms

• Plotting Different Charts, Labels, and Labels Alignment etc.

Introduction to Seaborn

• Introduction to Seaborn

• Making a scatter plot with lists

• Making a count plot with a list

• Using Pandas with seaborn

• Tidy vs Untidy data

• Making a count plot with a Dataframe

• Adding a third variable with hue

• Hue and scattera plots

• Hue and count plots

Visualizing Two Quantitative Variables

• Introduction to relational plots and subplots

• Creating subplots with col and row

• Customizing scatters plots

• Changing the size of scatter plot points

• Changing the style of scatter plot points

• Introduction to line plots

• Interpreting line plots

• Visualizing standard deviation with line plots

• Plotting subgroups in line plots

Visualizing a Categorical and a Quantitative Variable

• Current plots and bar plots

• Count plots

• Bar plot with percentages

• Customizing bar plots

• Box plots

• Create and interpret a box plot

• Omitting outliers

• Adjusting the whisk

• Point plots

• Customizing points plots

• Point plot with subgroups

Customizing Seaborn Plots

• Changing plot style and colour

• Changing style and palette

• Changing the scale

• Using a custom palette

• Adding titles and labels: Part 1

• Face Grids vs. Axes Subplots

• Adding a title to a face Grid object

• Adding title and labels: Part 2

• Adding a title and axis labels

• Rotating x-tics labels

• Putting it all together

• Box plot with subgroups

• Bar plot with subgroups and subplots

• Well done! What’s next