Data Understanding and Data Visualization with Python

Focused View

AI Sciences

12:16:11

10 View

01.01-about the tutor and ai sciences.mp4

03:40

01.02-focus of the course.mp4

04:21

01.03-content of the course.mp4

07:59

02.01-introduction to strings.mp4

09:16

02.02-multi-line strings.mp4

05:50

02.03-indexing strings.mp4

14:09

02.04-string methods.mp4

14:56

02.05-string escape sequences.mp4

10:08

03.01-introduction to data structure.mp4

06:47

03.02-data structures-defining and indexing.mp4

06:01

03.03-data structures-insertion and deletion.mp4

07:29

03.04-data structures-insertion and deletion python practice.mp4

06:36

03.05-data structures-deep copy or reference and slicing.mp4

08:25

03.06-data structures-exploring methods using tab completion.mp4

07:23

03.07-data structures-abstract ways.mp4

06:32

03.08-data structures-problem solving practice.mp4

19:28

04.01-introduction to numpy.mp4

06:49

04.02-numpy dimensions.mp4

13:51

04.03-numpy shape size and bytes.mp4

04:40

04.04-numpy arange and random package.mp4

09:00

04.05-numpy random and reshape.mp4

10:22

04.06-numpy slicing combined.mp4

14:05

04.07-numpy masking.mp4

08:36

04.08-numpy broadcasting and concatenation.mp4

10:14

04.09-numpy ufuncs and speedtest.mp4

05:30

04.10-ufuncs add sum and plus operators.mp4

16:52

04.11-ufuncs subtract power mod.mp4

11:08

04.12-ufuncs comparisons logical operators.mp4

15:22

04.13-ufuncs output argument.mp4

06:57

04.14-numpy playing with images.mp4

20:22

04.15-numpy knn classifier from scratch.mp4

28:18

04.16-numpy structured arrays.mp4

09:06

05.01-introduction to pandas.mp4

06:58

05.02-pandas series.mp4

06:23

05.03-pandas dataframe.mp4

08:50

05.04-pandas missing values.mp4

06:43

05.05-pandas loc and iloc.mp4

06:46

05.06-pandas in practice.mp4

24:22

05.07-pandas group by.mp4

14:12

05.08-hierarchical indexing.mp4

09:04

05.09-pandas rolling.mp4

09:26

05.10-pandas where.mp4

08:43

05.11-pandas clip.mp4

05:37

05.12-pandas merge.mp4

12:45

05.13-pandas pivot table.mp4

16:16

05.14-pandas strings.mp4

05:33

05.15-pandas datetime.mp4

06:48

05.16-pandas hands-on covid-19 data.mp4

31:05

05.17-pandas hands-on covid-19 data bug fixed.mp4

02:30

06.01-introduction to matplotlib.mp4

05:49

06.02-matplotlib multiple plots.mp4

09:41

06.03-matplotlib colors and styles.mp4

08:27

06.04-matplotlib colors and styles shortcuts.mp4

08:02

06.05-matplotlib axis limits.mp4

11:13

06.06-matplotlib legends labels.mp4

06:59

06.07-matplotlib set function.mp4

05:35

06.08-matplotlib markers.mp4

08:35

06.09-matplotlib markers random plots.mp4

06:51

06.10-matplotlib scatter plot.mp4

12:15

06.11-matplotlib contour plot.mp4

09:12

06.12-matplotlib histograms.mp4

08:16

06.13-matplotlib subplots.mp4

10:13

06.14-matplotlib 3d introduction.mp4

06:02

06.15-matplotlib 3d scatter plots.mp4

05:02

06.16-matplotlib 3d surface plots.mp4

08:35

07.01-introduction to seaborn.mp4

11:03

07.02-seaborn relplot.mp4

04:25

07.03-seaborn relplot kind line.mp4

05:14

07.04-seaborn relplot facets.mp4

09:08

07.05-seaborn catplot.mp4

05:43

07.06-seaborn heatmaps.mp4

03:50

08.01-introduction to bokeh.mp4

04:15

08.02-bokeh multiplots markers.mp4

06:58

08.03-bokeh multiplots grid plot.mp4

06:06

09.01-plotly 3d interactive scatter plot.mp4

07:46

09.02-plotly 3d interactive surface plot.mp4

05:09

10.01-geographic maps with folium using covid-19 data.mp4

12:26

11.01-pandas for plotting.mp4

11:08

9781801078795 Code.zip

Description

Data visualization has gained a lot of traction resulting from an increased focus on data analytics. To be a successful data scientist, data manipulation and wrangling are not enough. Visualizing data to garner insights is an equally important tool in the data science toolkit. Given the myriad types of data that exist, visualization has become an increasingly important topic. This course will equip you with all the skills you need to successfully create insightful visualizations. The course first starts with the fundamentals of Python. Then, the course teaches you how to use libraries such as NumPy, Pandas, Matplotlib, Seaborn, Bokeh, and so on. Additionally, you will learn data manipulation, which is the step prior to visualization. You will also learn how to plot geographical data using Folium. Each module in the course has practical hands-on mini projects, and with the mammoth content, this is one of the most comprehensive courses you will be doing on data visualization in Python. By the end of this course, you have not only learned the theoretical fundamentals of visualizations but also gained essential practical skills to explore this growing domain. The code files and all related files are uploaded on GitHub at: https://github.com/PacktPublishing/Data-Understanding-and-Data-Visualization-with-Python

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Python

Data Visualization

AI Sciences

Instructor's Courses

We are a group of experts, PhDs and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.Our courses have had phenomenal success. Our Courses have helped more than 100,000 students to master AI and Data Science.

PacktPub

View courses PacktPub

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.