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Update meetup data
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data/chapters_meetup.json

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"country_acronym": "it",
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"state": "RM",
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"city": "Roma",
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"members": 1310,
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"members": 1309,
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"lat": 41.9,
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"lon": 12.48,
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"timezone": "Europe/Rome"
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"country_acronym": "co",
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"state": "",
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"city": "Medellín",
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"members": 1151,
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"members": 1152,
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"lat": 6.25,
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"lon": -75.59,
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"timezone": "America/Bogota"
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"country_acronym": "in",
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"state": "",
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"city": "Delhi",
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"members": 426,
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"members": 427,
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"lat": 28.67,
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"lon": 77.21,
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"timezone": "Asia/Kolkata"
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"country_acronym": "us",
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"state": "VA",
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"city": "Charlottesville",
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"members": 431,
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"members": 432,
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"lat": 38,
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"lon": -78.46,
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"timezone": "America/New_York"
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"country_acronym": "us",
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"state": "DC",
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"city": "Washington",
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"members": 3033,
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"members": 3031,
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"lat": 38.91,
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"lon": -77.02,
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"timezone": "America/New_York"
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"country_acronym": "za",
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"state": "",
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"city": "Johannesburg",
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"members": 1118,
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"members": 1119,
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"lat": -26.19,
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"lon": 28.04,
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"timezone": "Africa/Johannesburg"

data/events.json

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"id": "304199693",
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"group_urlname": "rladies-philly",
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"title": "Lunch&Learn: {targets} with Irena Papst",
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"body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;27<\/p><p class='text-truncate'>This is a save the date! More details to come.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
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"body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;27<\/p><p class='text-truncate'>Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
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"start": "2025-01-22 12:00:05",
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"end": "2025-01-22 13:00:05",
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"date": "2025-01-22",
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"location": "Online event",
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"type": "published",
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"lat": -8.5211,
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"lon": 179.1962,
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"description": "This is a save the date! More details to come."
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"description": "Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years."
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},
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{
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"id": "304978583",

data/events_updated.json

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[
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{
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"date": "2024-12-23 12:15:28",
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"date": "2024-12-24 12:13:07",
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"n_events_past": 3943
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}
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]

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