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Comedians in Cars Getting Coffee – Seasons 1-9 Original Order

Here is the original order from the releases of Comedians in Cars Getting Coffee, as they were released before being moved to Netflix.

Title Season/Episode Guest Video Duration Release Date
‘Larry Eats a Pancake’ S1 E1 Larry David 13:35 2012-07-19
‘Mad Man in a Death Machine’ S1 E2 Ricky Gervais 11:33 2012-08-02
‘A Monkey and a Lava Lamp’ S1 E3 Brian Regan 12:18 2012-08-09
‘Just a Lazy Shiftless Bastard’ S1 E4 Alec Baldwin 11:24 2012-08-16
‘A Taste of Hell From on High’ S1 E5 Joel Hodgson 10:45 2012-08-23
‘Unusable on the Internet’ S1 E6 Bob Einstein 12:24 2012-08-30
‘You Don’t Want to Offend a Cannibal’ S1 E7 Barry Marder (Ted L. Nancy) 7:56 2012-09-06
‘I Hear Downton Abbey is Pretty Good…’ S1 E8 Colin Quinn & Mario Joyner 11:08 2012-09-13
‘I Want Sandwiches, I Want Chicken’ S1 E9 Carl Reiner & Mel Brooks 17:07 2012-09-20
‘It’s Bubbly Time, Jerry’ S1 E10 Michael Richards 17:13 2012-09-27
‘I’m Going To Change Your Life Forever’ S2 E1 Sarah Silverman 18:51 2013-06-13
‘I Like Kettlecorn’ S2 E2 David Letterman 18:24 2013-06-20
‘No Lipsticks for Nuns’ S2 E3 Gad Elmaleh 17:44 2013-06-27
‘You’ll Never Play the Copa’ S2 E4 Don Rickles 12:51 2013-07-04
‘Really?!’ S2 E5 Seth Meyers 14:23 2013-07-11
‘Kids Need Bullying’ S2 E6 Chris Rock 15:33 2013-07-18
‘Comedy, Sex and The Blue Numbers’ S3 E1 Louis C.K. 22:39 2014-01-02
‘How Would You Kill Superman?’ S3 E2 Patton Oswalt 12:31 2014-01-09
‘Comedy Is a Concealed Weapon’ S3 E3 Jay Leno 20:52 2014-01-16
‘So You’re Mellow and Tense?’ S3 E4 Todd Barry 14:49 2014-01-22
‘Feces Are My Purview’ S3 E5 Tina Fey 16:05 2014-01-30
‘The Over-Cheer’ S3 E6 George Costanza 06:19 2014-02-02
‘The Last Days of Howard Stern’ S3 E7 Howard Stern 13:21 2014-02-06
‘A Little Hyper-Aware’ S4 E1 Sarah Jessica Parker 19:34 2014-06-19
‘Two Polish Airline Pilots’ S4 E2 George Wallace 16:11 2014-06-26
‘Opera Pimp’ S4 E3 Robert Klein 15:55 2014-07-03
‘It’s Like Pushing a Building Off a Cliff’ S4 E4 Aziz Ansari 16:37 2014-07-10
‘The Sound of Virginity’ S4 E5 Jon Stewart 18:13 2014-07-17
‘You Look Amazing in the Wind’ S5 E1 Kevin Hart 19:36 2014-11-06
‘I’m Wondering What It’s Like To Date Me’ S5 E2 Amy Schumer 16:06 2014-11-13
‘Smoking Past The Band’ S5 E3 Bill Burr 16:03 2014-11-20
‘Happy Thanksgiving Miranda’ S5 E4 Miranda Sings 20:32 2014-11-27
‘I Wasn’t Told About This…With Special Feature: I’m Dying, Jerry’ S5 E5 Fred Armisen 20:56 2014-12-04
‘I’m Going To Take A Percocet And Let That One Go’ S5 E6 Ali Wentworth 17:54 2014-12-11
‘The Unsinkable Legend: Part 2’ S5 E7 Jimmy Fallon 16:58 2014-12-18
‘The Unsinkable Legend: Part 1’ S5 E8 Jimmy Fallon 17:04 2014-12-18
‘I’ll Go If I Don’t Have To Talk’ S6 E1 Julia Louis-Dreyfus 17:09 2015-06-04
‘Always Do The Banana Joke First’ S6 E2 Steve Harvey 18:18 2015-06-11
‘We Love Breathing What You’re Burning, Baby’ S6 E3 Jim Carrey 16:33 2015-06-18
‘The Comedy Team of Smug and Arrogant’ S6 E4 Bill Maher 18:53 2015-06-25
‘That’s the Whole Point of Apartheid, Jerry’ S6 E5 Trevor Noah 20:58 2015-07-02
‘Cut Up And Bloody But Looking Good’ S6 E6 Stephen Colbert 16:48 2015-07-09
‘Just Tell Him You’re the President’ S7 E1 President Barack Obama 19:13 2015-12-31
‘If You See This On A Toilet Seat, Don’t Sit Down’ S7 E2 Steve Martin 23:06 2016-01-07
‘Stroked Out On A Hot Machine’ S7 E3 Kathleen Madigan & Chuck Martin 17:56 2016-01-14
‘It’s Great That Garry Shandling Is Still Alive’ S7 E4 Garry Shandling 21:44 2016-01-21
‘I Don’t Think That’s Bestiality’ S7 E5 Sebastian Maniscalco 16:16 2016-01-28
‘Mr. Ferrell, For the Last Time, We’re Going To Ask You To Put the Cigar Out’ S7 E6 Will Ferrell 18:15 2016-02-04
‘Stick Around For The Pope’ S8 E1 Jim Gaffigan 19:15 2016-06-16
‘You Can Go Cho Again’ S8 E2 Margaret Cho 18:21 2016-06-23
‘Escape From Syosset’ S8 E3 Judd Apatow 16:13 2016-06-30
‘Everybody Respects A Bloody Nose’ S8 E4 J.B. Smoove 15:06 2016-07-06
‘Everybody Likes To See The Monkeys’ S8 E5 Lorne Michaels 16:22 2016-07-14
‘What Kind Of Human Animal Would Do This?’ S8 E6 John Oliver 18:10 2016-07-21
‘The Volvo-ness’ S9 E1 Kristen Wiig 17:32 2017-01-05
‘A Rusty Car In The Rain’ S9 E2 Norm MacDonald 21:15 2017-01-12
‘Dictators, Comics, And Preachers’ S9 E3 Cedric the Entertainer 14:36 2017-01-19
‘At What Point Am I Out From Under?’ S9 E4 Lewis Black 16:11 2017-01-26
‘Champagne, Cigars, And Pancake Batter’ S9 E5 Christoph Waltz 13:43 2017-02-02
‘It’s Not So Funny When It’s Your Mother’ S9 E6 Bob Einstein 23:09 2017-02-09

Custom Web AppBuilder Widgets in TypeScript

If you’re a JavaScript developer, you may have heard of TypeScript, a typed superset of JavaScript that compiles to plain JavaScript. If you’re also creating custom Web AppBuilder widgets, using TypeScript in a widget is a great way to get started with TypeScript. Here are a few notes and tips that I’ve discovered while using TypeScript within a Web AppBuilder custom widget development workflow.

Background

My usual Web AppBuilder development workflow is to have my widget code in its own code repository, and use a task runner like Grunt or Gulp to automatically compile and copy my code to the correct places (The stemapp directory and optionally the server directory of the app that I’m currently working on). Within this context, TypeScript fills the “transpiler” role where Babel might currently be in your stack.

tsconfig.json file

Many aspects of your tsconfig.json file are on a per-project basis, but there are a few things that you do need:

  1. “module”: “amd” – we choose “amd” because AMD is the module style that Web AppBuilder expects to see when loading a widget into an app.
  2. “moduleResolution”: “classic” – because we chose “AMD” above
  3. “target”: “es5” – the ECMAScript JavaScript type that we want the TypeScript compliler to output. We want to target es5 so the code we write in ES6-style JavaScript will be converted down so older browsers will be able to read it.
  4. “types”: [ “arcgis-js-api”, “dojo-typings”] – the names of the type definitions we want to include.
  5. “inlineSources” and “inlineSourceMap” – set these to true if you’ve got a build system that is moving code around, so that your source maps will work when debugging in the browser.

Full example here.

Declare Decorator

This is the main key to the entire process. It tells the TypeScript compiler how to translate your ES6-style class syntax in your Widget.ts file into the Dojo-style define/declare syntax that Web AppBuilder expects. This bit of code can be obtained from the dojo/typings repository, and included in your widget files. You then import it into your Widget.ts file, and apply the decorator on your Widget class. Note that decorators are experimental right now, so they could potentially be removed from TypeScript in the future, but for now this is a good option that keeps our code clean.

Promises

I would like to write code as close as possible to true ES6 JavaScript. So I’d like to use the native JavaScript Promise syntax. But when I tried to do this in my widget, I initially got an error, “error TS2693: ‘Promise’ only refers to a type, but is being used as a value here.” To resolve this problem, all I had to do was add the “es6-promise” library to my “lib” property in the “tsconfig.json” file. See the “–lib” line in the TypeScript Compiler Options Table for more information – including a clarification of why I’m including dom, es5, etc, as well as options that you can add other than es2015.promise.

[“dom”, “es5”, “scripthost”, “es2015.promise”]

Sourcemaps

I found it’s easiest if you set “inlineSources” and “inlineSourceMap” in your “tsconfig.json” file to true. If not, the path of the sourcemap is often wrong. The TS source shows as a separate file from your main widgets file:

Huh?

That’s a lot of information, and it’s sometimes hard to get all the settings in your project exactly correct, so I’ve put together an example widget in a GitHub repository that is available for download here: Web AppBuilder Typescript Examples. Note there are 2 examples in there that represent 2 “styles” of project, so please read the README file for clarification on which to use. We’re also considering getting a TypeScript option into the Web AppBuilder Custom Widget Generator, and if you have any feedback on what you’d like to see there, please let us know via this GitHub issue. Thanks!

Links

Note: this post also appears on my Esri Community Blog.

ArcGIS JavaScript API 4 – Hover Feature Event

The way hover events work in the JavaScript API 4 vs 3 is a bit different. In the 3.x API, you could use the “mouse-move”, “mouse-over”, and “mouse-out” events on the Feature Layer object itself. See example here:

But in the 4.x API, you want to use the “pointer-move” event of the MapView (or SceneView). But that will give you events on any time the pointer moves in the map. So you then have to run a “hit-test” on the result to see what feature it is hovering over (if any). Example here:

A Geo Conference in STL Next Week!

A guest post by Gregory Brunner

ASPRS will host its inaugural GeoYou Conference on September 13 & 14, 2017 at the Cortex Innovation Community in St. Louis, MO. GeoYou brings together innovation leaders from government, industry and academia to highlight cutting-edge capabilities in geospatial big data and real-time analytics. Leading experts will discuss practical mechanisms for high-tech entrepreneurs to enter the market.

GeoYou will include presentations and discussions on agriculture, defense/intelligence, infrastructure/utilities, local government/emergency, research/education, services/commerce, and transportation. Brainstorming sessions will focus on geospatial analytics, collection systems, cloud, cyber, data science, and entrepreneur opportunities.

Keynote speakers for GeoYou include Judy Sindecuse, CEO of Capital Innovators, Mark Munsell, Deputy Director, CIO & IT Services at the National Geospatial-Intelligence Agency, and Eric Druker, Director of Data Science Solutions at Booz Allen Hamilton.

For more information go to GeoYou.org.

Shotcharts Revisited – From NBA Stats to Feature Service in Less Than 20 Lines of Code


View larger map

A guest post by Gregory Brunner

About two years ago, I wrote about creating shotcharts in ArcGIS using Python and arcpy. In the post, I demonstrated how to scrape the data from stats.nba.com and create a shots feature class from the data. I then shared the resulting shotchart as several web maps in ArcGIS Online. What I was unable to do at the time was automate the creation of the feature service and web maps that I shared in that post. Recent enhancements to the ArcGIS API for Python allow me to automate the process of sharing the shot data as a hosted feature service in ArcGIS Online and design web maps using the shot data. What I really like is that I can do this with less code than I wrote for my original blog post! In my previous post, I had to scrape the shot data, create a feature class, add fields to the feature class, and then add the shot data to the feature class. At that point, I would manually create a hosted feature service from the shot feature class. With recent enhancements to the ArcGIS API for Python, I can do this all in Python and I can to this in less than 20 lines of code! In this post, I will demonstrate how to to scrape data from the NBA stats site, put it into a spatial dataframe, share the spatial dataframe as a hosted feature service, and design web maps that use the hosted feature service. I will try to do this in as little code as possible!

Python Packages

In this post, I will use arcgis, pandas, and requests. After importing these packages, I will log into my ArcGIS Online account in order to save the shot data to a hosted feature service.

import arcgis
from arcgis.gis import GIS
from arcgis import SpatialDataFrame

import pandas as pd
import requests

from IPython.display import display

gis = GIS("https://www.arcgis.com", "gregb")

Getting the Shot Data

In my original post I looked at shots taken by Russell Westbrook from the 2014 – 2015 regular season. Here I will look at Russell Westbrook’s shots taken during the 2016 – 2017 regular season. I originally showed how to do this with urllib. Here, I will use requests similar to how Savvas Tjortjoglou does in How to Create NBA Shot Charts in Python.

player_id= '201566' #Russell Westbrook
season = '2016-17'  #MVP Season of 2016-17
seasontype="Regular+Season" #or use "Playoffs" for shots taken in playoffs

I will form the NBA stats request URL using Russell Westbrook’s NBA.com player ID and use requests to get the data.

nba_call_url = 'http://stats.nba.com/stats/shotchartdetail?AheadBehind=&CFID=&CFPARAMS=&ClutchTime=&Conference=&ContextFilter=&ContextMeasure=FGM&DateFrom=&DateTo=&Division=&EndPeriod=10&EndRange=28800&GameEventID=&GameID=&GameSegment=&GroupID=&GroupQuantity=5&LastNGames=0&LeagueID=00&Location=&Month=0&OpponentTeamID=0&Outcome=&PORound=0&Period=0&PlayerID=%s&PlayerPosition=&PointDiff=&Position=&RangeType=0&RookieYear=&Season=%s&SeasonSegment=&SeasonType=%s&ShotClockRange=&StartPeriod=1&StartRange=0&StarterBench=&TeamID=0&VsConference=&VsDivision=' % (player_id, season, seasontype)
response = requests.get(nba_call_url, headers={'User-Agent': "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/48.0.2564.82 Safari/537.36"})

I will push the response JSON into a pandas dataframe.

shots = response.json()['resultSets'][0]['rowSet']
headers = response.json()['resultSets'][0]['headers']
shot_df = pd.DataFrame(shots, columns=headers)

From DataFrame to SpatialDataFrame

In order to publish the shot data to ArcGIS Online as a shotchart, I will convert the pandas dataframe to an arcgis spatial dataframe. In addition to passing the shot_df to SpatialDataFrame, I will pass the geometries associated with each row in the dataframe.

shot_coords = shot_df.iloc[:,17:19].values.tolist()
sdf = SpatialDataFrame(shot_df,geometry=[arcgis.geometry.Geometry({'x':-r[0], 'y':r[1], 
                    'spatialReference':{'wkid':3857}}) for r in shot_coords])

From SpatialDataFrame to Feature Service

Now that the shots are in a spatial dataframe, I will publish the spatial dataframe to ArcGIS Online.

shot_chart = gis.content.import_data(sdf)

Voila! I have the shots as a hosted feature service! It took less than 20 lines of code (including import statements) and to go from the NBA stats response to a hosted feature service only took 7 lines!

display(shot_chart)

From Feature Service to Web Maps

Even though I have the shots as a feature service, I am not done. I can use the ArcGIS API for Python to visualize the shots. I will create three maps: one that shows the shots without any renderer, one the that shows the shots symbolized by whether it was made or missed, and one that shows all the shots taken as a heat map.

For the basketball court, I will use the court feature class that I have in ArcGIS Online.

court_tiles = gis.content.search("Basketball Court", outside_org=False, item_type="Feature")
court_layers = court_tiles[1].layers

The court is broken into two feature services: One for the court outline and one for the court lines. I need to add them separately to the web map.

Shot Locations

Now that I have the basketball court layers and the shots as a feature service, I can display them on my map. I will set the shot chart renderer to “None” so that the default point symbology is applied to the shot_chart layer.

chart1 = gis.map((0.002,0), zoomlevel=17)
display(chart1)
chart1.add_layer(court_layers[1])
chart1.add_layer(court_layers[0])
chart1.add_layer(shot_chart,{"renderer":"None"})
chart1.basemap='dark-gray'


View Web Map

Shots Made and Missed

I want to be able to differentiate between shots made and shots missed. I can do that by changing the renderer when I add the shot_chart layer to the map. I will use the “ClassedColorRenderer” and apply the class colors based on the values in the “SHOT_MADE_FLAG” field.

chart2 = gis.map((0.002,0), zoomlevel=17)
display(chart2)
chart2.add_layer(court_layers[1])
chart2.add_layer(court_layers[0])
chart2.add_layer(shot_chart, {"renderer":"ClassedColorRenderer",
               "field_name": "SHOT_MADE_FLAG"})
chart2.basemap='dark-gray'


View Web Map

Shots missed are in dark gray. Shots made are in white. I assume that this is the default “ClassedColorRenderer”. I need to do some more investigating to figure out how to apply my desired color map.

Shots Taken as a Heat Map

I also want to see the shots taken as a heat map. I will use the “HeatmapRenderer” to do that.

chart3 = gis.map((0.002,0), zoomlevel=17)
display(chart3)
chart3.add_layer(court_layers[1])
chart3.add_layer(court_layers[0])
chart3.add_layer(shot_chart, {"renderer":"HeatmapRenderer",
               "opacity": 0.75})
chart3.basemap='dark-gray'


View Web Map

Again, I assume the orange-to-red color ramp is the default heat map renderer. I need to learn a little bit more about the API if I want to change the heat map color ramp.

Conclusions

I thought it would be fun to revisit my post on mapping shotcharts with ArcGIS and Python and see how the code changes with the introduction of the ArcGIS API for Python. Using the trick to convert the pandas dataframe to ArcGIS spatial dataframe makes it very easy to go from NBA stats as JSON to a hosted feature service. It also reduces the amount of code I need to write. I no longer need to create a feature class with arcpy, add fields to the feature class, then add the data to the feature class. I can now go from the stats as JSON to hosted feature service in only a few lines of code! I am still learning some of the ins-and-outs of the API (like applying renderers to the MapView), but if you have any questions, don’t hesitate to ask!

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Gavin Rehkemper

JavaScript, WordPress, and GeoDev