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When analyzing data,
it'll usually be presented as a table.

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You might be used to viewing tabular
data in Microsoft's Excel or

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Apple's Numbers app.

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However, for this course,
we'll be using Google Sheets,

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which offers a spreadsheet
app right within the browser.

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If you're not familiar with Google Sheets,
or

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need a refresher on how
to use spreadsheets,

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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.

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You'll need a Google account
to work with Google Sheets.

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If you don't have one,
it's easy and free to sign up.

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Here, we can create a new spreadsheet by
clicking the blank section under start

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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.

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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

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marathon_results_2017.csv file.

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We then need to choose an import
action and a separator character.

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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.

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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.

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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

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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.