1 00:00:00,740 --> 00:00:02,000 So how'd you do? 2 00:00:02,000 --> 00:00:05,766 Allow me show you how to combine all of my Billboard chart data and 3 00:00:05,766 --> 00:00:07,524 all of my Spotify chart data. 4 00:00:07,524 --> 00:00:10,650 We have two data frames containing Billboard data. 5 00:00:10,650 --> 00:00:15,460 billboard contains data from 2017 and 2018, 6 00:00:15,460 --> 00:00:19,125 billboard19 contains 2019 data. 7 00:00:19,125 --> 00:00:24,690 We wanna concatenate these datasets into a new data frame called billboard_all. 8 00:00:26,040 --> 00:00:29,800 The required argument is a Python list containing the data frames. 9 00:00:31,630 --> 00:00:34,240 We don't need any optional arguments in this case. 10 00:00:34,240 --> 00:00:39,894 So we type billboard_all 11 00:00:39,894 --> 00:00:46,833 = pd.concat([billboard, 12 00:00:46,833 --> 00:00:54,802 underscore billboard19.]). 13 00:00:58,396 --> 00:01:00,851 Let's do the same with the two Spotify dataframes. 14 00:01:03,251 --> 00:01:07,929 Spotify_all = pd.concat, 15 00:01:10,211 --> 00:01:17,001 ([spotify, spotify19]). 16 00:01:22,256 --> 00:01:24,069 Let's do a quick confidence check. 17 00:01:27,450 --> 00:01:37,050 Billboard.shape, billboard19.shape. 18 00:01:40,630 --> 00:01:47,446 Some quick math, billboard_all should have roughly 12,800 rows. 19 00:01:51,073 --> 00:01:53,739 Billboard_all.shape. 20 00:01:55,611 --> 00:01:57,515 And they all have 7 columns, great. 21 00:01:59,850 --> 00:02:05,165 I'll do the same for Spotify, spotify.shape, 22 00:02:10,384 --> 00:02:12,444 spotify19.shape. 23 00:02:17,981 --> 00:02:23,369 Let's see, 20 and 7, let's call it 54, 24 00:02:23,369 --> 00:02:31,204 spotify_all should have around 26,100 rows and 5 columns. 25 00:02:31,204 --> 00:02:34,018 spotify_all.shape. 26 00:02:36,828 --> 00:02:41,621 Now we have one large data frame with 30 months of Billboard chart data and 27 00:02:41,621 --> 00:02:45,820 another large data frame with 30 months of Spotify chart data. 28 00:02:47,040 --> 00:02:51,202 In the next video, we'll create our final dataset that is merged and 29 00:02:51,202 --> 00:02:55,241 concatenated from smaller datasets, all using the pandas tool. 30 00:02:55,241 --> 00:02:55,974 Can't wait.