/reimagined-enigma

python basics for data science

Primary LanguageJupyter Notebook

Introduction to Pandas Python

Welcome! This notebook will teach you about using Pandas in the Python Programming Language. By the end of this lab, you'll know how to use Pandas package to view and access data.

Table of Contents

  • About the Dataset
  • Introduction of Pandas
  • Viewing Data and Accessing Data
  • Quiz on DataFrame

  • Estimated time needed: 15 min

    About the Dataset

    The table has one row for each album and several columns
    • artist: Name of the artist
    • album: Name of the album
    • released_year: Year the album was released
    • length_min_sec: Length of the album (hours,minutes,seconds)
    • genre: Genre of the album
    • music_recording_sales_millions: Music recording sales (millions in USD) on [SONG://DATABASE]
    • claimed_sales_millions: Album's claimed sales (millions in USD) on [SONG://DATABASE]
    • date_released: Date on which the album was released
    • soundtrack: Indicates if the album is the movie soundtrack (Y) or (N)
    • rating_of_friends: Indicates the rating from your friends from 1 to 10
    You can see the dataset here:
    Artist Album Released Length Genre Music recording sales (millions) Claimed sales (millions) Released Soundtrack Rating (friends)
    Michael Jackson Thriller 1982 00:42:19 Pop, rock, R&B 46 65 30-Nov-82 10.0
    AC/DC Back in Black 1980 00:42:11 Hard rock 26.1 50 25-Jul-80 8.5
    Pink Floyd The Dark Side of the Moon 1973 00:42:49 Progressive rock 24.2 45 01-Mar-73 9.5
    Whitney Houston The Bodyguard 1992 00:57:44 Soundtrack/R&B, soul, pop 26.1 50 25-Jul-80 Y 7.0
    Meat Loaf Bat Out of Hell 1977 00:46:33 Hard rock, progressive rock 20.6 43 21-Oct-77 7.0
    Eagles Their Greatest Hits (1971-1975) 1976 00:43:08 Rock, soft rock, folk rock 32.2 42 17-Feb-76 9.5
    Bee Gees Saturday Night Fever 1977 1:15:54 Disco 20.6 40 15-Nov-77 Y 9.0
    Fleetwood Mac Rumours 1977 00:40:01 Soft rock 27.9 40 04-Feb-77 9.5