[ FreeCourseWeb ] Lynda - R Programming in Data Science- Dates and Times

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[ FreeCourseWeb.com ] Lynda - R Programming in Data Science- Dates and Times
  • Get More App Tips and Secrets!.url (0.2 KB)
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  • ~Get All Courses Here !.url (0.2 KB)
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    • 01 - Calculating times and dates with R.en.srt (1.9 KB)
    • 01 - Calculating times and dates with R.mp4 (7.4 MB)
    • 02 - Course organization.en.srt (0.8 KB)
    • 02 - Course organization.mp4 (1.4 MB)
    • 03 - Typical date calculations.en.srt (2.7 KB)
    • 03 - Typical date calculations.mp4 (5.1 MB)
    • 04 - How dates and times are stored in R.en.srt (4.4 KB)
    • 04 - How dates and times are stored in R.mp4 (6.6 MB)
    • 05 - Choose the right date and time tool.en.srt (1.7 KB)
    • 05 - Choose the right date and time tool.mp4 (2.3 MB)
    • 06 - The base R Date class.en.srt (5.3 KB)
    • 06 - The base R Date class.mp4 (9.3 MB)
    • 07 - Use formatters to recognize dates in character strings.en.srt (4.4 KB)
    • 07 - Use formatters to recognize dates in character strings.mp4 (8.3 MB)
    • 08 - Dealing with time zones and daylight savings time.en.srt (5.3 KB)
    • 08 - Dealing with time zones and daylight savings time.mp4 (9.1 MB)
    • 09 - Use operators to compare date objects.en.srt (3.5 KB)
    • 09 - Use operators to compare date objects.mp4 (6.9 MB)
    • 10 - Adding and subtracting dates and times.en.srt (5.0 KB)
    • 10 - Adding and subtracting dates and times.mp4 (8.6 MB)
    • 11 - Create sequences of dates, cut dates, and round dates.en.srt (6.3 KB)
    • 11 - Create sequences of dates, cut dates, and round dates.mp4 (10.6 MB)
    • 12 - Extract parts of a date.en.srt (4.6 KB)
    • 12 - Extract parts of a date.mp4 (10.6 MB)
    • 13 - Presenting formatted dates and times.en.srt (5.0 KB)
    • 13 - Presenting formatted dates and times.mp4 (9.1 MB)
    • 14 - Use read.csv() to import CSV date information.en.srt (6.2 KB)
    • 14 - Use read.csv() to import CSV date information.mp4 (11.6 MB)
    • 15 - Advantages of the Lubridate package.en.srt (2.3 KB)
    • 15 - Advantages of the Lubridate package.mp4 (4.7 MB)
    • 16 - Parsing date and time with Lubridate.en.srt (5.1 KB)
    • 16 - Parsing date and time with Lubridate.mp4 (10.2 MB)
    • 17 - Getting and setting time components with Lubridate.en.srt (6.7 KB)
    • 17 - Getting and setting time components with Lubridate.mp4 (15.0 MB)
    • 18 - Rounding dates and time with Lubridate.en.srt (3.2 KB)
    • 18 - Rounding dates and time with Lubridate.mp4 (7.0 MB)
    • 19 - Lubridate math with durations.en.srt (6.1 KB)
    • 19 - Lubridate math with durations.mp4 (8.9 MB)
    • 20 - Lubridate math with periods.en.srt (5.7 KB)
    • 20 - Lubridate math with periods.mp4 (9.0 MB)
    • 21 - Lubridate math with intervals.en.srt (6.7 KB)
    • 21 - Lubridate math with intervals.mp4 (11.9 MB)
    • 22 - Time zones with Lubridate.en.srt (3.2 KB)
    • 22 - Time zones with Lubridate.mp4 (6.1 MB)
    • 23 - The busdater package.en.srt (3.8 KB)
    • 23 - The busdater package.mp4 (6.5 MB)
    • 24 - The BusinessDuration package.en.srt (5.3 KB)
    • 24 - The BusinessDuration package.mp4 (8.8 MB)
    • 25 - The fmdates package.en.srt (4.3 KB)
    • 25 - The fmdates package.mp4 (5.8 MB)
    • 26 - Time-series data.en.srt (3.5 KB)
    • 26 - Time-series data.mp4 (4.6 MB)
    • 27 - The base R ts class.en.srt (4.1 KB)
    • 27 - The base R ts class.mp4 (9.0 MB)
    • 28 - The zoo package.en.srt (5.7 KB)
    • 28 - The zoo package.mp4 (10.8 MB)
    • 29 - The xts package.en.srt (5.2 KB)
    • 29 - The xts package.mp4 (9.4 MB)
    • 30 - The tsibble and tibbletime packages.en.srt (5.6 KB)
    • 30 - The tsibble and tibbletime packages.mp4 (8.4 MB)
    • 31 - Time-series rolling statistics.en.srt (5.0 KB)
    • 31 - Time-series rolling statistics.mp4 (9.7 MB)
    • 32 - Time-series graphics.en.srt (4.8 KB)
    • 32 - Time-series graphics.mp4 (8.2 MB)
    • 33 - The timelineR package.en.srt (7.1 KB)
    • 33 - The timelineR package.mp4 (11.5 MB)
    • 34 - The timelineS package.en.srt (2.5 KB)
    • 34 - The timelineS package.mp4 (4.4 MB)
    • 35 - The CRAN task view for time-series analysis.en.srt (1.5 KB)
    • 35 - The CRAN task view for time-series analysis.mp4 (5.3 MB)
    • 36 - The anytime package.en.srt (4.3 KB)
    • 36 - The anytime package.mp4 (7.3 MB)
    • 37 - The hms package.en.srt (4.2 KB)
    • 37 - The hms package.mp4 (6.7 MB)
    • 38 - The mondate package.en.srt (2.4 KB)
    • 38 - The mondate package.mp4 (4.3 MB)
    • 39 - The datetime package.en.srt (2.1 KB)
    • 39 - The datetime package.mp4 (4.0 MB)
    • 40 - The datetimeutils package.en.srt (2.4 KB)
    • 40 - The datetimeutils package.mp4 (5.1 MB)
    • 41 - The padr package.en.srt (5.8 KB)
    • 41 - The padr package.mp4 (9.8 MB)
    • 42 - Next steps.en.srt (1.0 KB)
    • 42 - Next steps.mp4 (2.2 MB)
    • Bonus Courses + Project Files.url (0.2 KB)
      • Ex_Files_R_Programming_Data_Science
      • Bonus Courses + Project Files.url (0.2 KB)
        • Exercise Files chapter 01
        • 01_01.R (0.4 KB)
        • 01_02.R (0.9 KB)
        • 01_03.R (0.5 KB)
        • year_month_data.csv (0.1 KB)
        chapter 02
        • 02_01_choosingBaseRTools.R (0.4 KB)
        • 02_02 character conversion.R (0.6 KB)
        • 02_03 time zones and daylight savings.R (1.2 KB)
        • 02_04 logical operators.R (0.8 KB)
        • 02_05 math.R (1.5 KB)
        • 02_06 seq cut round.R (1.7 KB)
        • 02_07 subset weekdays.R (0.9 KB)
        • 02_08 formatting dates.R (0.4 KB)
        • 02_09 import csv dates.R (1.4 KB)
        • Base R Functions Compared to Date and Time Classes.pdf (31.0 KB)
        • Results of Subtracting_Adding One Class from Another.pdf (27.5 KB)
        • year_month_day_data.csv (0.3 KB)
        chapter 03
        • 03_02 parsing with lubridate.R (0.9 KB)

Description

[ FreeCourseWeb.com ] R Programming in Data Science: Dates and Times

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MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch | Duration: 2h 17m
Genre: eLearning | Language: English + Sub | Size: 322 MB

One of the fundamental difficulties of data science is working with dates and times. This course shows data engineers, DevOps practitioners, and data-science programmers the most common (and many not so common!) problems and how to use R-based tools to implement solutions. Learn how dates and times are stored and retrieved in base R. Find out how to format, compare, add and subtract, and extract dates and times using built-in R functions. Then discover how to incorporate specialized R packages, such as lubridate, busdater, zoo, timelineR, anytime, datetime, and more, to perform some of the heavy lifting. Instructor Mark Niemann-Ross walks you through each package, so you can appreciate the advantages and best uses of each one.
Topics include:
Choosing the right tool
Dates and times in base R
Dealing with time zones
Adding and subtracting dates and times
Formatting dates and times
Rounding dates and times
Using lubridate for dates and times
Business and finance packages for R
Working with time-series data
Specialized data and time packages

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[ FreeCourseWeb ] Lynda - R Programming in Data Science- Dates and Times

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322.1 MB
seeders:10
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[ FreeCourseWeb ] Lynda - R Programming in Data Science- Dates and Times

Torrent hash: EB51CDED7F8DE9054FDB1A9746EB14867080E155