Development
Data Science
Pandas
Pandas and Scikit-learn For Data Analysis & Machine Learning
4.3 (465 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,716 students enrolled

Pandas and Scikit-learn For Data Analysis & Machine Learning

Learn in demand skill Pandas, Sci-kit Learn, Numpy For Data Science & Machine Learning : Seaborn | MatplotLib | Python
4.3 (465 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,716 students enrolled
Created by Ankit Mistry, Data Science & Machine Learning Academy
Last updated 5/2020
English
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Pandas and Scikit-learn For Data Analysis & Machine Learning
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This course includes
  • 17 hours on-demand video
  • 12 articles
  • 21 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Update your resume with one of the in demand skill : Data analysis Pandas
  • Setting up Python in anaconda environment
  • Refresh Python basics with crash course
  • Learn Most demanded python data analysis library : Pandas
  • Three important data structure of pandas : Series, Data Frame, Panel
  • Learn how to analyse one, two and three dimensional data
  • How to group Data for analysis
  • How to deal with Text Data with Pandas Functions
  • Analyse data having multiple level index.
  • Array and Matrix manipulation Library NumPy
  • Master pandas with quizzes.
  • Data Visualization Matplotlib and Seaborn Library
  • Importing data from various different kinds of sources
  • Complete Machine Learning work flow implementation with Scikit-learn
Course content
Expand all 149 lectures 16:50:37
+ – Introduction
6 lectures 15:36

In this video, we will see what is data analysis and why data analysis required. What are option available for analyzing data like R/Python.

What is Data analysis
Preview 05:20
Claim your Free Gift
00:35
Join Online Classroom
00:14

In this video we will learn brief idea about data analysis library pandas. Why pandas kind of library has been created for data analysis. What are features of pandas library.

Introduction to Pandas
Preview 04:22
Course FAQ
Preview 05:02
How to get Certificate
00:03
Pandas
4 questions
+ – Installation and IDE
9 lectures 37:54

In this video we will see 2 different ways to install pandas and python in your local machine.

Different ways of installation
02:59

In this video we will see from where to download anaconda, selection appropriate version, and step by step installation of anaconda distribution on Windows based machine.

Download and Install anaconda + Pandas
Preview 06:09
Troubleshooting : 'conda' is not recognized as an internal or external command
00:10

In this video we will see how to start anaconda prompt, and various  conda utility related  command  for performing various task like

  • update package,

  • install package,

  • remove package.

Anaconda + Conda Command
Preview 07:25
Conda Cheatsheet
00:00
anaconda, conda & pandas Update
00:05

In this video will learn how to start jupyter notebook and jupyter lab.

Walk through of jupyter UI, how to create a cell how to execute a cell and so on

Getting started with Jupyter Lab
12:43
Jupyter Notebook cheatsheet
00:01

In this video we will learn how to import required library like numpy, pandas and Matplotlib into python environment.

Import Library
08:21
Installation
7 questions
+ – Code Download
1 lecture 00:03

Download Python code.

Python Code
00:03
+ – Python Crash Course [Optional]
6 lectures 58:27

Learn what are the different Python related topic we will address in this Python crash course section.

Introduction
01:55

Learn about Python basic data type like numbers float Boolean string. What are the operation we can perform with all those basic data type.

Python Basics - I
14:54
Data types, Numbers, String
5 questions

In this video will learn how to make your life easy by putting all those repetitive task inside looping mechanism available in Python wait for and while loop.

Another thing we will learn how to apply decision making based on mathematical and logical condition in Python.

Python Basics - II
07:35
Loops & Decision making
3 questions

Learn how to create and use to collection type available in a python list and tuples. And what are the different attributes and methods we can apply on a list object.

Lists and tuples
15:26
Lists and tuples
4 questions

Learn another important collection type available in Python dictionary and sets. Methods and attribute associated with dictionary object. In which scenario we need to use the dictionary object.

Dictionary and set
10:40
Dictionary and set
4 questions

In this video, we will learn concept of function in a python, how to create user defined function with parametric argument and without argument. How to use the function as a black box system.

Functions
07:57
Python - 1
10 questions
Python - 2
9 questions
+ – Python Exercises
2 lectures 26:22

Python exercise problem to test your understanding about python language.

Exercise Overview
04:47

Verify solution of above  python problem.

Solutions
21:35
+ – Numpy
8 lectures 01:37:49

In this video learn how to create numpy array with varieties of different ways like array method, arange, linspace, random, eye, ones and zeros. Learn about what are the attributes and method you can apply on this numpy array.

Creating NumPy array
16:10

In this video learn about what is indexing in numpy array and how to select single element or a set of element with slicing plus what are the operations you can perform on top of numpy array.

Numpy indexing and selection, Functions
16:11
Some more Numpy Functions
Preview 12:29
Linear algebra with NumPy
10:10
List vs NumPy Array
11:16
Views vs Copy - Numpy Array
08:20
Insert, Append and Delete NumPy array
10:34
Split, Concatenate, Tile and Repeat array
12:39
NumPy
10 questions
+ – Series : Pandas
11 lectures 01:08:52
Series
00:06

Learn basic introduction about series data type available in Pandas library.

Introduction to Series
02:54

Learn how to create series Data type with String, float,  numbers, list, Boolean, Dictionary data object.

Create Series from Python Object
11:44

Learn how to create series data type from the comma separated file, .CSV file. read_ csv() 

Create Series from CSV file
08:58
Create Series Object
4 questions

Values, index, dtype

Series attributes & methods
12:39
Series attributes & methods
5 questions

In this video we will learn about, instead of simple number base indexing how to use custom label based indexing in a series data type of Pandas.

Label indexing
Preview 04:36
Label indexing
2 questions

Learn one of the very important parameter 'inplace' while doing any kind of modifications to series object and how to sort values and index of series object.

inplace parameter, sort_values & sort_index
07:50
inplace parameter, sort_values & sort_index
2 questions

Learn how to get meta information associated to series object with Python built in functions max, min, sort, list, dict etc...

Apply Python built in function on Series
03:00

Learn how to extract single value, multiple value or range of value based on bracket notation and slicing notation.

Extract Value from Series
06:24
Extract Value from Series
4 questions

Learn how to count frequency of each value with value_count method on series data type of pandas.

.value_counts() Method
01:48

Learn how to invoke function on every single value of series  with apply function and map value with map function.

.apply() and .map() method
08:53
.apply() and .map() method
2 questions
Series
8 questions
+ – Data Frame : Pandas
21 lectures 02:17:40

Learn one of the very important core Data structure available in a Pandas library which represent two dimensional tabular data which is the common way of representing records based data withdata frame object.

Introduction to Data Frame
04:10

In this video we will learn how to create a data frame object from varieties of different ways like random generation of data or reading comma separated file and put all those data into data frame object.

Create Data Frame - random data + from File
10:31

Learn different attributes and methods we can apply on data frame object to get some meta information about object.

Data frame attributes and methods
11:34

Learn how to add new column to existing data frame object.

Adding new column
04:09

Learn how to select one column or more than one column from the data frame object with bracket notation.

Select one or more than one column
Processing..
Broadcasting operation
04:16

Learn how to delete particular rows and column of data frame object based on index number and column name respectively.

Drop missing row or column
Preview 08:10
Filtering Data with one condition
10:26
Filtering Data with multiple condition
06:44

Learn .isin() method to filter the data from Data frame object.

Filtering Data with .isin() method
05:41

Learn how to use

.between() Method to filter the data from Data frame object.

Filtering Data with .between() method
03:49

Learn how to get unique sets of values and total number of unique values in a particular column of data frame object.

unique() & nunique() method
04:43

Learn how to use sort_values method to sort the column.

sorting values
Preview 09:22

Learn how to sort index of data frame object and inplace parameter to do permanent modification in original data frame object.

sort index and inplace parameter
04:50

Learn how to extract rows of values based on label indexing and number based indexing.

.loc() and .iloc() method
14:08

Learn how to extract rows with .ix() method.

.ix() method
04:07

Learn how to change the data type of individual column of data frame object to optimally represent data frame in a memory and better way to do further analysis on the data.

.astype() method - optimize memory requirement
07:57

Learn how to make different column as a index column of data frame object.

set_index() : change index column
04:18

Learn how to apply custom function veet apply method on a one single column of data frame object.

.apply() method on single column
05:42

Learn how to apply custom function on  than one column of data frame object.

.apply() method on multiple column
08:09

Learn how to fetch random record from whole data sets.

Fetch random sample
04:54
+ – Pandas Exercise
3 lectures 34:31

Pandas exercise problem to test your understanding about Pandas DataFrame object.

Exercise Overview : Google App store dataset
03:25
Pandas Exercise Solution - I
16:12
Pandas Exercise Solution - II
14:54
+ – Panel : Pandas
1 lecture 03:47

Learn panel data type available in a Pandas library to represent three dimensional data.

Warning - Panel Data type
03:47
Requirements
  • Windows/Linux/MAC machine
  • Basic idea about Programming concepts
Description

JOIN OTHER 30,000 SUCCESSFUL STUDENTS WHO HAVE ALREADY ENROLLED & MASTERED PYTHON & PANDAS SKILLS (DATA ANALYSIS LIBRARY) WITH ONE OF MY BEST SELLING, TOP RATED COURSE.

Student Testimonial :

Great going, ankit is good at explanation of data processing stuff. i bought many of his course related to python and machine learning. - Jay

Every concept is clearly explained and the tutor of this course replies to every question asked in Q&A section. - Mukka Akshay

It was very good session. The instructor has enough knowledge and able to make me understand clearly. Thank you Ankit! - Bibek Baniya

This is an amazing course if you want to understand the extent of the power of Pandas. - Venkat Raj

It's one of the best course !!! Most of the topics has been covered and explained up to the expectation - Ankur SIngh

it is a good match with what i was looking for, the instructor is quite knowledgeable. - Shivi Dhir

This class is not too fast or too slow, the way he teaches is perfect. - Frankie Y

It is excellent -  Rakhshee Misbah

good experience - Weiting

-----------------------------------------------------------------------------------------------------------

Update : New section on Data visualization library  Matplotlib and Seaborn added.

Update : New section on Numpy Library get added.

-----------------------------------------------------------------------------------------------------------

If you want to master most in-demand data analysis library pandas, carry on reading.

Hi, I am Ankit, one of the Best Selling author on Udemy, taught various courses on Data Science, Python, Pandas, PySpark, Model Deployment.

By the end of this course, you will able to apply all majority of Data analysis function on various different datasets with built in function available in pandas. Analysis techniques like exploratory data analysis, data transformation, data wrangling, time series data analysis, analysis through visualization and many more. Carry on reading to know more about course.

The era of Microsoft Excel is going to be over, so would you like to learn the next generation one of the most powerful data processing tool and in demand skill required for data analyst, data scientist and data engineer.

Then this course is for you, welcome to the course on data analysis with python's most powerful data processing library Pandas.


Why this course?

Data scientist is one of the hottest skill of 21st century and many organisation are switching their project from Excel to Pandas the advanced Data analysis tool .

This course is basically design to get you started with Pandas library  at beginner level,  covering majority of important concepts of data processing data analysis and a Pandas library and make you feel confident about data processing task with Pandas at advanced level.

What is this course?

This course covers

  • Basics of Pandas library

  • Python crash course for any of you want refresh basic concept of python

  • Python anaconda and Pandas installation

  • Detail understanding about two important data structure available in a Pandas library

  • Series data type

  • Data frame data type

  • How you can group the data for better analysis

  • How to use Pandas for text processing

  • How to visualize the data with Pandas inbuilt visualization tool

  • Multilevel index in Pandas.

  • Time series analysis

  • Numerical Python : NumPy Library

  • Matplotlib and Seaborn for Data visualization

  • Machine Learning Theoretical background

  • Complete end to end Machine Learning Model implementation with Scikit-learn API

    • (from Importing Data to Splitting data, Fitting data and Evaluating Data) & How to Improve Machine Learning Model

  • Importing Data from various different kind of file

You will get following after enrolling in this course.

  • 150+ HD quality video lecture

  • 16+ hours of content

  • Discussion forum to resolve your query.

  • quizzes to to test your understanding

This course is still in a draft mode. I am still adding more and more content, quiz, projects related to data processing with different functionalities of Pandas. So stay tuned and enroll now.

Regards

Ankit Mistry

Who this course is for:
  • Beginner Python developer who is curious about Data Science, Not for experienced Data Scientist
  • Anyone who want to make career in Data Science, Data analytics
  • Anyone wants to learn data analysis with python language
  • Excel user who wants to enhance data analysis skills.