Creating a Spreadsheet3:54 with Ben Deitch
In this video we'll import the data into a new Google Sheets spreadsheet.
When analyzing data, it'll usually be presented as a table. 0:00 You might be used to viewing tabular data in Microsoft's Excel or 0:04 Apple's Numbers app. 0:08 However, for this course, we'll be using Google Sheets, 0:09 which offers a spreadsheet app right within the browser. 0:12 If you're not familiar with Google Sheets, or 0:16 need a refresher on how to use spreadsheets, 0:17 check out our spreadsheet basics course linked in the teacher's notes below. 0:20 Let's go to sheets.google.com to get started. 0:24 You'll need a Google account to work with Google Sheets. 0:31 If you don't have one, it's easy and free to sign up. 0:34 Here, we can create a new spreadsheet by clicking the blank section under start 0:38 a new spreadsheet. 0:43 For this course, we'll be looking at the results of the Boston Marathon, 0:47 which is a popular race in the United States. 0:51 So for the first step, let's click up here on Untitled Spreadsheet and 0:54 change the title to Boston Marathon Results. 0:59 Awesome, next we need to import the data. 1:04 It's available down below in the teachers notes as a CSV file. 1:08 CSV stands for Common Separated Value,s and 1:14 if we open up the file in a text editor, 1:17 We can see that each line of the file represents a different runner. 1:23 And each piece of data about that runner is separated by a comma. 1:28 CSV files are easy to understand and easy to deal with. 1:32 You'll be seeing lots of CSV files as a data analyst. 1:37 Once you've downloaded the marathon_results_2017.csv file, 1:41 back in Google Sheets, choose file, Import, 1:47 and then on the upload tab, drag in your 1:52 marathon_results_2017.csv file. 1:56 We then need to choose an import action and a separator character. 2:02 For the import option, since all we've got is an empty sheet, 2:07 let's just choose to, Append rows to current sheet. 2:11 And for the separator character we could choose Comma, 2:15 but, Detect automatically will work just fine. 2:18 So let's leave it as is, and click Import. 2:22 It might take a minute to import the over 25,000 finishers of the Boston Marathon. 2:25 But after it does it should look something like this, and to make it a little easier 2:31 to see on my screen I'm going to enter presentation mode. 2:36 In this data set each row represents a single finisher, and 2:40 each column represents a discrete piece of information about that finisher. 2:44 Let's look through the data we have for each finisher. 2:50 First off, we've got a unused column that seems to be a line number. 2:53 Followed by their Bib number, 2:57 which is the number the runner was wearing during the race. 2:59 Next, we've got the runners Name, Age, and 3:02 whether the runner registered as male or female. 3:06 After that, we've got some geographic information. 3:09 City, state, country, and even citizenship for 3:13 athletes that live outside their home country. 3:16 Next, we have an empty column followed by the runners' times at 3:22 various intervals throughout the race. 3:26 K here stands for kilometers. 3:28 Then, we've got the runner's pace per mile, 3:34 an empty projected time column, and the official time of the runner. 3:37 Finally, at the end, we've got the runner's overall ranking, 3:42 ranking within their gender, and the ranking within their division. 3:46 It's a lot of data, but I'm sure we'll be able to analyze it. 3:50
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