Download Udemy – Crash Course: Data Analysis using Pandas in python 2023-11

Description

Crash Course: Data Analysis using Pandas in Python. This course will follow the following structure

Part 1: Getting Started with Python

• This section explains how to install the Aanconda distribution and write the first code
• Additionally, walking on the Spyder platform

Part 2: Work on the data

• P02 01A Running SQL in Python
• P02 01 Understanding data n Add comments in code
• P02 02 Know the contents of the data
• P02 03A Missing Value Diagnosis n Treatment Part 1
• P02 03B Introduction to Jupyter IDE
• P02 03C Missing numerical value with average n date missing value treatment
• P02 03D Create a copy of a dataframe n drop a record based on the missing value of a specific field
• P02 03E Replace missing value with median or mode
• P02 04 Data filtering n keeping multiple columns in the data
• P02 05 Use iloc to filter data
• P02 06 Numeric variable analysis with group by n Transfer results
• P02 07 Number of frequency distribution n percent including missing percent
• P02 08 An introduction to the substring n function

Part 3: Working on multiple datasets

• P03 01 Create Dataframe in execution Append concatenate dataframe
• P03 02 Integration of DataFrames
• P03 03 Remove full or column duplicates Sort data frame Keep first last max min
• P03 04 get row for maximum value of each column in easy way n then via idxmax
• P03 05 Use idxmax iterrows forloop to solve a complex question
• P03 06 Create derived fields using numeric fields
• P03 07 Cross Tab Analysis n Place the result in another data transfer result
• P03 08 variable extraction based on character field
• P03 09 variable extraction based on the date field
• P03 10 The first day of the last day of the same day of the last n months

Section 4: Data visualization and some commonly used terminology

• P04 01 n-bar histogram chart in Jupyter and Spyder
• P04 02 Line chart Pie chart Box chart
• P04 03 Review of some thin Python software
• P04 04 Scope A global scope local scope variable
• P04 05 Range Object
• P04 06 Casting or conversion variable type n cutting thread
• P04 07 lambda function n drop columns from pandas dataframe

Section 5: Some statistical methods and other advanced cases

• P05 01 Simple diagnosis of outliers n treatment
• P05 02 Creating a report in Excel format
• P05 03 Create pivot table in pandas data frame
• P05 04 Renaming the columns of a dataframe
• P05 05 Read write attached data in SQLlite database
• P05 06 Write code execution report
• P05 07 Linear regression using Python
• P05 08 Chi-square test of independence

What you will learn in Crash Course: Data Analysis using Pandas in python

This course is suitable for people who

• Anyone interested in using Python for data analysis
• Professional data analysis
• People who want to migrate from other platforms like SAS to Python
• data scientist

Details of the Crash Course: Data Analysis using Pandas in Python

• Publisher: Udemy
• teacher: Gopal Prasad Malakar
• Training level: beginner to advanced
• Training duration: 4 hours and 10 minutes
• Number of courses: 41

Headlines of Crash Course: Data Analysis using Pandas in Python

Crash Course prerequisites: Data Analysis using Pandas in python

• The course will train everything from scratch and in a simplified manner for data analysis purposes
• The course is less about Python programming and more about using different packages for data analysis purposes.

Course images

Sample video of the course

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 1 GB

Download part 4 – 0.1 GB

File(s) password: www.downloadly.ir

Size

3.16 GB