Python for Data Analysis: Step-By-Step with Projects

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Just Into Data

9:57:38

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01.01-introduction.mp4

04:02

01.02-course overview.mp4

05:31

02.01-setting up python environment.mp4

07:19

02.02-overview of data types numeric define variables.mp4

08:19

02.03-strings common functions and methods.mp4

14:31

02.04-lists tuples sets dictionaries booleans.mp4

13:56

02.05-if statements loops.mp4

19:11

02.06-define functions use packages.mp4

15:11

02.07-lambda functions conditional expressions.mp4

15:04

03.01-pandas data structures overview.mp4

14:32

03.02-loading data.mp4

08:00

03.03-previewing data.mp4

06:30

03.04-pandas data types overview.mp4

17:43

03.05-exporting data.mp4

06:32

04.01-combining datasets.mp4

13:49

04.02-renaming columns.mp4

07:42

04.03-selecting columns.mp4

04:19

04.04-selecting rows and setting the index (1).mp4

14:36

04.05-selecting rows and setting the index (2).mp4

13:38

04.06-subsetting both rows and columns.mp4

10:24

04.07-modifying values.mp4

14:10

04.08-making a copy.mp4

05:54

04.09-sorting data.mp4

10:14

05.01-nba games project overview.mp4

02:45

06.01-data cleaning overview.mp4

02:15

06.02-removing unnecessary columnsrows.mp4

10:58

06.03-missing data overview.mp4

17:02

06.04-tackling missing data (dropping).mp4

08:14

06.05-tackling missing data (imputing with constant).mp4

18:03

06.06-tackling missing data (imputing with statistics) and missing indicators.mp4

20:05

06.07-tackling missing data (imputing with model).mp4

07:38

06.08-handling outliers (1).mp4

15:23

06.09-handling outliers (2).mp4

15:57

06.10-cleaning text.mp4

15:39

07.01-extracting date and time.mp4

20:19

07.02-binning.mp4

17:55

07.03-mapping new values.mp4

11:42

07.04-applying functions.mp4

16:11

08.01-czech bank project overview.mp4

03:31

09.01-eda overview.mp4

02:44

09.02-aggregating statistics.mp4

23:09

09.03-group by.mp4

21:48

09.04-pivoting tables.mp4

17:17

09.05-distribution of one feature.mp4

17:20

09.06-seaborn library overview.mp4

14:03

09.07-relationship of two features (1).mp4

11:38

09.08-relationship of two features (2).mp4

16:28

09.09-relationship of multiple features.mp4

11:40

09.10-seaborn library recap.mp4

03:15

10.01-olympic games project overview.mp4

02:57

11.01-course wrap up.mp4

00:35

9781803243979 Code.zip

Description

Data analysis is a critical skill and is getting more popular. Nowadays, every organization has some data. Data could be extremely useful, but not without appropriate analysis. Data analysis enables us to transform data into insights for businesses to make informative decisions.

You can find data analysis being used in every industry, be it healthcare, finance, or technology. Python is one of the most in-demand skills for data science by employers. It is not only easy to learn but also powerful.

The course follows the approach of rather than dumping all the available Python libraries or functions to you, we picked only the most useful ones based on our industry experience to cover in the course. This allows you to focus and master the foundations. Besides Python programming, you will also get exposed to the basic statistical knowledge necessary for data analysis. Combined with detailed video lectures, you will be given a few projects to work on to reinforce your knowledge.

By the end of the course, you will have a solid foundation of data analysis, and be able to use Python for the complete process.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-for-Data-Analysis-step-by-step-with-projects-

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Python

Data Analysis

Just Into Data

Instructor's Courses

Just Into Data is the brainchild of Justin and Lianne. Justin is an experienced data scientist in many different fields, such as marketing, anti-money laundering, and big data technologies. He also has a bachelor’s degree in computer engineering and a master’s degree in statistics. Lianne is an experienced statistician who has worked in the central bank as well as commercial banks, where she monitored major financial institutions and conducted fraud analysis. She has both a bachelor’s and a master’s degree in statistics.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.