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In this video we'll import the data into a new Google Sheets spreadsheet.
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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.
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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.
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For this course, we'll be looking at
the results of the Boston Marathon,
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which is a popular race
in the United States.
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So for the first step, let's click
up here on Untitled Spreadsheet and
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change the title to
Boston Marathon Results.
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Awesome, next we need to import the data.
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It's available down below in
the teachers notes as a CSV file.
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CSV stands for
Common Separated Value,s and
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if we open up the file in a text editor,
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We can see that each line of the file
represents a different runner.
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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.
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You'll be seeing lots of CSV
files as a data analyst.
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Once you've downloaded
the marathon_results_2017.csv file,
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back in Google Sheets,
choose file, Import,
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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,
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let's just choose to,
Append rows to current sheet.
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And for the separator character
we could choose Comma,
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but, Detect automatically
will work just fine.
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So let's leave it as is, and click Import.
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It might take a minute to import the over
25,000 finishers of the Boston Marathon.
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But after it does it should look something
like this, and to make it a little easier
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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
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each column represents a discrete piece
of information about that finisher.
2:44
Let's look through the data we have for
each finisher.
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First off, we've got a unused column
that seems to be a line number.
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Followed by their Bib number,
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which is the number the runner
was wearing during the race.
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Next, we've got the runners Name, Age, and
3:02
whether the runner registered as male or
female.
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After that,
we've got some geographic information.
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City, state, country,
and even citizenship for
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athletes that live outside
their home country.
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Next, we have an empty column
followed by the runners' times at
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various intervals throughout the race.
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K here stands for kilometers.
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Then, we've got
the runner's pace per mile,
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an empty projected time column, and
the official time of the runner.
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Finally, at the end,
we've got the runner's overall ranking,
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ranking within their gender, and
the ranking within their division.
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It's a lot of data, but
I'm sure we'll be able to analyze it.
3:50
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