Charles Karpati | Meetup's API docs

That sounds like us!

To begin. The directions say:

Redirect using the following url in a browser:

And

Once you visit that link:

• "Meetup will ask the user to login if they are not already logged in."

• "If the user has previously authorized access for the provided client_id, Meetup will immediately redirect the user back to the redirect_uri with success query parameters."

__Response Parameters__

• code - A string that can only be used once to request an access token

• state - An opaque string that you may provide in the initial request

Here is an example URL:

Clicking on that link will take you to an authorization page.

In the past, we had been getting: "invalid_request" errors. Meaning: "The request was malformed or missing parameters".

Naturally, the query failed when trying here for us because we didn't know the redirect_uri.

There exists more info in original documentation about all this.

Now the docs say:

With all this being done...

Make a post request with the following format using the key given to you in the previous response.

As apposed to a get request, this will not be something you can do by entering a url into an address bar.

Perform POST request for an access token using this:

Lets try it

SUCCESS!!

Lets look at the content

Did it look like whats below? A successfull submisson should look like this:

We got back JSON encoded in a string. Lets get that undefined because it's what we need amongst the other credentials to perform our query.

Otherwise, you'll get an error message. More information in the docs.

Once completed, API Queries can be made using the access_token and the KEY from before.

Skip down to the 'Querying Data' section if you made it down here.

Here are a bunch of queries we could make.

Docs, Template: undefined

API Query 5 - MEMBER INFORMATION Through Their ID

API Query 6 - Which Cities Are The Members From?

Save Those Queries!

We can use append undefined to the end of our Terminal commands to save the output.

Colabs has this special feature I will use that lets me store the output of a terminal command (deonted by the undefined) into a python variable.

In the following instance, I use the undefined terminal command to read the contents of each file and store them into variables as a textual 'string'.

From there, much like before, we can open the files with python to view their contents.

It's possible to perform data science with JSON.

But for now lets convert it to tabularized form: a CSV

the dataWorksCSV only has one record since we only requested data on one 'group' -> DataWorks

Colabs pre-formats the output for us.

You'll see that the undefined function flattened the hierarchical nesting of the json object.

Here are the new column names for this flattened JSON Object.

Lets take a peek at some information?

[link text](https:// [link text](https:// link text))Alright.. So we have 2311[link text](https:// link text) members and the group was created mid 2018?

What can we determine about our members?

A lot of these columns don't have much information. The status column has only 1 unique value 'active', for instance.

created - The time this member joined the Group, represented as milliseconds since the epoch

updated - The last time this member edited their Group profile, represented as milliseconds since the epoch

visited - The last time this member visited the Group, represented as milliseconds since the epoch

we have previously created a dataset 'meetup_api_member_data.csv' by running through step 3-6.

We wont have to do those parts again. Just re-upload the file now.

First we download data for every single record.

Then we flatten it

This is a test to see if it works

This will do the flattening for all records