04:33
36 Summary and What's Next
07:36
35 Creating System Activity Reports
04:28
34 Additional Tools
05:45
33 Installing the Package sysstat
06:58
32 Summary and What's Next
05:39
31 Recording Performance with top and vmstat
08:31
30 Working with uptime and tload
04:48
29 Using pwdx and pmap
04:20
28 Introduction and Listing Standard Tools
04:00
27 Summary and What's Next
08:48
26 Using Nice to Control Process Priority
07:11
25 Backgrounding Tasks
01:12
24 Introduction
05:18
23 Summary and What's Next
04:37
22 Shortcuts with pgrep, pkill, and top
06:05
21 Send Signals with kill
05:20
20 Using the proc directory and the $$ Variable
07:38
19 Listing Processes with ps
01:27
18 Introduction
04:14
17 Summary and What's Next
03:36
11 Summary
07:09
09 Managing GRUB Recovery
04:14
17 Summary and What's Next
04:31
16 Custom GRUB2 Entries
07:22
15 Password Protect GRUB2
05:39
14 Manage Persistent Setting with grubby
03:39
13 Manage GRUB2 Defaults
03:43
12 Introduction and Re installing GRUB
05:20
10 Reset Lost Root Passwords
03:29
08 Summary
05:08
07 Selecting Runlevels at Boot
07:47
06 Changing Runlevels
07:43
05 Shutdown Commands
05:27
04 Introduction and Using wall
01:58
03 Summary and What's Next
06:26
02 Reading Operating System Data
03:48
01 Introduction
02:49
50 ppt presentation to business users for data insights
09:50
49 data cleaning car price case study
08:19
48 data manipulation and analysis 2 car price case study
10:23
47 data manipulation and analysis 1 car price case study
05:55
46 extrapolatory data analysis case study car price data sets
05:20
45 timeseries plots heatmap plots
07:44
44 aggregators plots bi variate analysis bar charts boxplots histograms
02:21
43 seaborn correlation matrix1
07:02
42 searborn basics beautify the plots boxplots histograms scatter
07:02
42 searborn basics beautify the plots boxplots histograms scatter
05:06
41 matplotlib marketing data plots boxplots histograms scatter
06:24
40 matplotlib basics
00:47
39 introduction to the world of visualizations
05:09
38 imputing missing values techniques melbourne real estate data 2
11:59
37 imputing missing values techniques melbourne real estate data 1
10:23
32 pandas summarising grouping
01:19
36 data cleaning introduction
07:00
35 pandas webscrapping skill
05:32
34 reading delimited files and rdbms data
13:35
33 introduction to data extraction
10:23
32 pandas summarising grouping
07:43
31 pandas merging dataframes
09:30
30 pandas indexing
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