Welcome,  everybody, to  Pictures  from  the  Gallery 7.

My  name  is  Scott  Wise, I'm  a  Senior  Systems  Engineer

in  the  US W est  Coast  and  I'm  joined today  by  my  daughter  Samantha.

-Hey. -Hey.

I  wanted  to  ask  you,  you're a  brand- new  incoming  college  student.

What  are  you  most concerned  about  for  the  future?

Well,  to  start,  I'm  pretty  worried  about negative  effects  on  the  environment

like  deforestation  and  soil depletion  and  climate  change.

Additionally,  I'm  worried about  things  like  sexism  in  the  workplace

and  gender  gap  wages.

Wow,  that's  a  lot  to  think  about.

It  got  me  thinking  as  well  what  we  can do  to  make  this  world  a  better  place.

To  start  off  our  presentation, I  got  three  suggestions  here.

If  we  stay  curious, part  of  what  we  can  do  with  that  curiosity

is  actually  share  with each  other  good  data.

You  all  like  to  analyze  data,

but  sharing  some  good  data would  be  a  great  idea.

and JMP  has  a  data  for  green  initiative where  over  the  JMP  community,

you  can  actually  share what  you  think  are  meaningful  views,

meaningful  data  collections, and  we  can  analyze  these  things  together.

The  second  thing you  can  do  is  to  use  your  time.

So  JMP  and  SAS  have  both  partnered

with  the  IIASA, which  is  trying  to  actively  measure

the  amount  of  deforestation  in  the rainforest  to  help  guide  better  policy.

So  it's  kind  of  a  cool  application

that  lets  you  look  at  some of  their  satellite  images  and  actually

help  identify  where  you  see development   in human  growth

in  the  rainforest  and  enable them  to  do  a  better  measurements.

Lastly,  user  skills.

We  all  have  great  JMP  skills

in  practice,  looking  at  analytics and  building  visualizations.

Our  friends  at  WildTrack  I  think  are some  of  the  best  examples  where  they're

using  the  footprints  of  many different  species  of  endangered  animals,

and  by  doing  a  little  bit  of  JMP and  a  little  bit  of  visualization,

they're  able  to  help  track  in  a non- invasive  way  these  endangered  animals

to  help  us  again  create  better  policy.

That's  Sky  and  Zoe, and  definitely  I'll  put  a  link  in  here

where  you  can  check  out their  work  and  get  inspired.

All  right,  so  without  further  ado,

here  is  the  pictures for  the  gallery  for  this  version.

And  in  our  version,  I  am  going to  dedicate  every  view  to  something  around

environmental  green  data. We  can  start  that  conversation.

But  as  usual,  I  am  showing  you  some  things

that  are  new  into   Graph Builder, such  as  the  first  five  years  I  show  you

have  been  brand  new  things  in  JMP  16, as  well  as  I'm  going  to  show you

just  a  couple  of  tips  and  tricks you  probably  have  never  seen  before.

All  right,  I've  got  the  first  chart here,

and  the  first  chart  is going  to  address  equality

and  it's  on  the  gender  wage  gap.

It's  going  to  show  you  a  new  interval type  chart  that's  available  in  JMP 16

that  I  call  the  Dumbbell  Chart.

Now  I'm  going  to  give  you  this  journal, and  why  I'm  pointing  this  out  is

if  you  want  to  recreate  this  view,

you  not  only  have a  picture  of  what  it  looks  like

and  tips  on  how  to  set  your data up,

to  make  this  chart, but  I  give  you  the  steps.

In  order,  not  only  that, I  give  you  the  data,

and  within  the  data,  you  can  just  click on  the  script  to  regenerate  the  view.

It's  all  there  for  you.

I'm  going  to  build  this  one  from  scratch. What  is  this  data?

This  comes  from  the International  Labor  Organization

and  it  is  looking  at  the  nominal mean  earnings  of  males  and  females.

But  it  has  it  normalized  by  US  dollars.

It  would  be  nice  to  see if  that  gap' s  getting  smaller,

like with  Sammy's  concern about  the  gender  wage  gap.

So  I  used  to  think you'd  have  to  create  a  formula

which  actually  took  the  delta, but  to  graph  it,  you  do  not.

You  just  need  to  have both  columns  you're  wanting  to  compare.

I'm  going  to  go  to   Graph Builder.

Everything  today is  going  to  be  in   Graph Builder.

And  I'm  going  to  take  the  female monthly  and  the  male  monthly.

I'm  going  to  put  them  both  on  the  x- axis,

but  I'm  also  going  to  put  them on  the  interval  landing  spots.

And  I'm  going  to  take  year and  put  year  on  the  Y.

Now  it  looks  really  busy and  it's  because  there's  many  countries

represented  here  over  this  span.

If  I  go  under  the  red  triangle,

I  like  to  call  this  a  hot  spot, and  add  a  local  data  filter.

We'll  just  look  at  it  by  one  country. Let's  pick  out  France.

Now  I  get  a  pretty  good  view.

It  might  be  better to  clean  up  the  view  a  little  bit.

I  can  right- click right  on  the  female  monthly  marker,

and  I  can  take this  marker  size  up  a  little  bit.

I'm  going  to  make  it  a  10.

And  now  I  can  do  the  same thing  with  the  male  monthly.

I'll  make  that   10 as  well.

I  can  right- click  right  here into  the  graph  and  go  to  Customize.

And  I  want  to  make  that  intersection  bar.

I  want  to  make  it  a  different  color. It's  the  second  air  bar  in  that  list,

and  I'm  going  to  make  it  gray and  maybe  make  it  a  bigger  width  of  three.

Now  I  got  the  view  I  like.

Now  you  can  kind  of  tell why I  call  it  a  Dumbbell  Chart,

because  if  anybody  likes  to  work  out, you  know,  at  the  gym,  you  have  weights

and  the  ends  of  the  weights  is where  the  heaviness  of  it  is  on  the  ends.

In  the  middle,  you  have  a  bar  to  lift.

That's  why  a  lot  of  people called  this  a  Dumbbell  Charts.

Now,  a  couple  of  cool things  I  can  show  you.

Number  one,  we  generally  don't  read from  bottom  up,  we  read  from  top  down.

You  can  right- click  here in  your   Axis Settings,

and  I  can  reverse  this  order  just  by clicking  on  this  little  box  right  here.

Now  I'm  going  2010  to  2019.

Also,  I  might  want  to  put  a  reference line  on  the  X-axis  to  help  my  eyes.

So  I'm  going  to  right- click go  to   Axis Settings.

And  I  think  about  3,500 would  make  a  good  little  reference  line.

It's  going  to  put  one on  the  X- axis,  and  there  we  go.

Now  I  can  kind  of  gauge,

is  the  gap  closing,  is  the  wage  increasing for  both  sexes,  that  type  of  thing.

Now  I'm  going  to  bring  a  lot of  pictures  in  as  examples  for  our  data,

and  I'm  going  to  show  you  that  if  you just  take  a  picture  and  you  just  put  it

into  your  graph,  it  will put  the  picture  as  a  background.

Now,  it's  sized  horribly  here.

It's  easy,  you  just  right- click   go  to  Image,  go  to  Size  and  Scale,

and  save   Fill Graph. There  we  go.

And  this  is  pretty  cool.

Now,  I  know  the  female  symbol  here in  the  background  map  is  red,

so  maybe  I'll  go  right  up  here

to  my  legend  and  I  will  change the  colors  around  here.

Pretty  easy  to  do.

A lso  I'm  going  to right- click  back  into  the  graph

and  in  my  image,  I'm  going  to  make that  background  a  little  more  transparent,

maybe  like  a  0.3  here.

Now  I've  got  a  really  cool  view.

Now,  one  word  of  warning, it's  locked  into  this  scale ,

and  you're  going  to  get a  different  scale  for  each  country

because  some  countries pay  more  than  others.

I  know  Germany  pays  very  well. You  can  see  it  changed  my  picture,

so  you'd  have  to  right- click

and  go  to  Image  again  and  Fill the  Graph  to  pull  it  back  correctly.

You  might  want to  move  your  reference  line.

The  background  maps  are  not  great  if you're  going  to  change  your  scale  a  lot.

I  do  have  a  version  here  that's a  multiple  view  version  without  a  picture

and  if  you  right- click  on  this  one,

you  can  see  here  I  was comparing  over  the  same  scale.

I  fixed  the  scales but  made  them  a  little  bigger.

What  was  the  difference in  France,  Germany  and  Sweden,

and  you  can  see  that  in  France,

the  wage  gap doesn't  look  so  bad  on  this  scale,

but  Germany  has  a  bigger wage  gap  but  pays  higher.

Maybe  you  want  to  be  in  Germany.

And  I  noticed  in  Sweden that  the  females  make  more  than  the  males.

There  you  go. There's  a  lot  of  differences  out  there.

This  is  some  fun  data  to  play  with, so  definitely  see  what  views  you  like.

All  right,  second  picture  we're going  to  look  at  is  a  Word  Cloud.

This  was  the  second most  popular  thing  that  got  requested.

And  you  might  have  seen  in  JMP, there  is  a  Text  Explorer  platform

that  allows  you  to  look  at  unstructured text  data  that  you  might  have.

And  Word  Cloud  was  one  of  the  views it gave  you  just  with  a  click  of  a  button.

But  how  do  you  do  that  in   Graph Builder?

Well,  let's  take  a  look.

In   Graph Builder,  all  you  need is  the  unstructured  text.

In  this  case,  I  have  a  column  of  words  and you  need  some  sort  of  counterweighting.

Here  I  have  the  weight and  where  this  data  came  from.

This  was  a  study  run  during  COVID of  what  are  the  top  five  things

 teachers were  worried  about. Of  course  they  were  dealing  with  a  lo t.

Remote  teaching, sick  students,  sick teachers,

a  big  change  to  curriculums just  to  get  through  the  year.

So  here,  the  highest  weight  was  anxious.

Twenty  respondents  all mentioned  being  anxious.

So what  I've  done  is  I  have  sorted

the  words  by  weights and  then  I  just  put  a  order  here.

So  the  highest  weight  got  an  order  of  one

and  the  next  highest  got an  order  of  two  and  so  forth.

That's  how  I  got  the  weight  column and  that's  how  I  got  the  order  column.

And  I  also  created  some  random  data because  you  can  have  a  sorted,

ordered  word  cloud,  but  you  can  also have  one  that  just  looks  like  a  cloud.

To  generate  that  one...

You  might  not  have  known  this, but  if  you  go  and  open  a  new  column  in  JMP

with  this  initialized  data,

you  can  put  in  random  data  and  you  can put  in  things  like  random  normal  data.

Okay,  I  have  already  done  that.

Let's  just  go  to   Graph Builder and  see  how  this  works.

Well,  the  first  thing I'm  going  to  do,  I'm  going  to  put  weights.

There  we  go  on  the  Y- axis,

and  I  am  going  to  size  by  weight, but  I  don't  want  points.

And  here's  a  little  trick  in  JMP  16,

under  the  red  triangle, under  the  points  elements  panel  here

that's on  your  bottom  left hand  side  of  the  Graph  Builder,

I  could  set  a  shape  column.

When  I  do  that,  I  can  substitute for  points  the  actual  word.

And  now  you're  starting  to  see  the  words

and  as  you  start  to move  around  your  graph,

you  can  see  what's  going  on with  those  words  and  that  is  very  cool.

This  right  here  is  your  first check  of  doing  a  word  cloud.

Now  I  can  color,  by  the  way, to  give  this  thing  some  color.

Now,  I'll  want  to  make it  as  cloud-like  as  possible.

I  can  move  this  random  over  here.

A gain,  playing around  with  the  data  set,

I  can  get  the  view  that  I  like.

Maybe  I'll  say  done  here, maybe  I'll  go  to  the  legend  position,

maybe  I'll  put  it  on  the  inside  left.

Maybe  I'll  go  under  the  legend  settings.

Maybe  I'll  turn  off all  but  just  the  color  code .

And  now  I  got a  pretty  nice- looking  word  cloud.

Now  as  well, if  I  wanted  it  to  be  in  sorted  order,

because  I  know  anxious is  the  most  important.

That's  the  biggest- sized  word,

I  love  that  to  kind  of  be  on  top and  then  the  next,  and  then  the  next.

So  to  do  that  one,  I'll  open my  control  chart  panel  back  up.

I  will  swap  out  the  order  for  the  random.

Now  you  can  see all  the  big  words  are  on  the  bottom,

so  I'm  going  to  right- click here  under  Axis  Settings,

and  I'm  going  to  do that  reverse  order  again.

N ow  all  the  big  stuff  is  up at  the  very  top  that  I  have.

And  Jittering,  what  you  didn't  see  before

was  you  were  getting a  centered  grid  jitter.

And  that's  actually  what's automatically  in  your  points  jittering.

If  I  do  a  positive  grid  now, I  get  things  in  order.

Anxious,  constant  stress  and  tired, whatever  it  has  room  for  on  the  line.

But  it  is  in  that  row  order, which  is  pretty  cool.

But  it's  so  much  on  the left- hand  axis  that's  a  little  weird.

So  I  can  right- click  here  on  the  X-axis.

Even  though  there's  nothing  down  here, you  can  still  play  with  the  settings.

And  I  can  go  and  maybe  make  this a  negative  0.5  for  the  minimum.

It's  going  to  add  a  little bit  of  space  over  here.

And  if  it  did  a  nice  job, did  a  really  nice  job.

Now  you  can  get an  ordered  word  cloud.

All  right. And  then,  of  course,

the  ones  I  have  in  my  data  that  you  can play  with,  you  can  see  I  put  in  a  nice

transparent  apple  background just  by  bringing  in  that  picture,

which  is  really  nice  to  play  with the  colors  and  all  those  type  of  things.

All  right,  that  was  a  nice popular  view  everybody  asked  for.

The  third  most  popular view  was  Line  Charts.

Everybody  likes  to  do  line  charts. In  JMP  16,  there's  many  new  features

that  actually fit  lines  through  points

in  a  lot  of  different  formats, as  well  as  label  your  line  interactively.

And  we're  going to  look  at  tree  cover  loss.

Remember  I  showed  you  that  link that  would  help  you  with  folks

that  were  trying  to  save  the  rainforest.

Well,  it's  important  to  know  how much  we're  losing  around  the  planet.

We  have  some  of  that  data, the  under  three  here,

moving  average  smoother  line  chart.

I  bring  up  my  data  here.

I've  got  tree  cover  loss  in  hectares.

By  year,  this  should  be pretty  straightforward,

so  I'll  just  go  to  my   Graph Builder.

I  will  put  my  tree  cover  loss  in  hectares.

I  will  put  my  year  down  here  on  the  X.

And  you  can  see  I've  got points  and  smoother  lines.

Not  so  exciting, maybe  take  drivers  and  overlay.

Getting  more  interesting, but  I  don't  like  these  lines.

What  other  options  do  I  have for  other  smoother  lines?

Well,  in  JMP  16,  they  put things  like  moving  average.

Maybe  a  moving  average  would  be  cool.

You  can  control   the  spread  of that  mover  average  with  this  local  width.

And  I'm  going  to  do  that  one.

I'm  going  to  say  done.

And  now  it's  looking  pretty  good. I'm  actually  going  to  open  it

right  back  up, there's  one  thing  I  forgot  to  do.

You  can  actually  put a  confidence  in  around  them.

Now  I'll  say  done  just  fine,  but  I clicked  this  little  button  right  there.

Very  cool.

But  I  just  want  to  look at  kind  of  the  big  hitters.

So  this  might  be  a  good  place to  go  under  the  red  triangle,

go  to  the  local  data  filter.

Go  ahead  under  drivers, and  just  take  the  top  three  drivers.

There  we  go.

This  is  a  good  chart,  I'm  very  close.

But  one  thing  that this  legend' s  kind  of  hard  to  read.

Wouldn't  it  be  nice  to  put  the  name  next to  the  line,  maybe  even  on  the  line?

Oh,  that  would  be  awesome.

Well,  you  can  do  it, you  might  not  know  this  is  the  place

you  can  do  it,  but  if  you  just  right- click right  here  on  the  legend  where  it  says

Agricultural  Shift,  you  can say  what  happens  to  the  label.

You  can  add  minimum  values and  first  value,  last  value,

but  just  go  click  Name  and  you  can  see... Oh,  look  at  that,  drew  it  right  in  there.

I'm  going  to  do  the same  thing  with  Commodity,

and  I'm  going  to  do the  same  thing  with  Forestry  Driven.

Now  I  don't  need  that  legend.

I  can  go  under  my  red triangle  versus   Graph Builder.

I  can  turn  off  the  legend because  it's  not  adding  any  value.

Now,  here's  what's  really  cool, you  don't  have  to  leave  it  out  here.

You  can  move  it  anywhere  along  the  line

if  you  get  close  to  the  line,

it  will  try  to  take  the  slope of  the  line  as  its  orientation.

I'll  do  this  for  Agricultural  Shift, I'll  put  that  one  there.

Commodity, I'll put  one  there. And  now  I  can  move  out  the  axis.

And  now  I've  got  a  really  cool  chart.

By  the  way,  on  this  chart, Agricultural  Shift  was  the  big  haha.

It  was  something  that  we  were definitely  having  a  huge  spike  in,

but  I  think  those  efforts, of  our  friends  trying  to  save

the  rainforest  have  managed to  pull  it  back  a  little  bit.

A gain,  you  have that  version  scripted  in  your  data

as  well  as  a  cool  little background  picture  in  the  background.

What  else  do  we  have  here?

Let's  go  to  the  bottom  of  our  chart.

The  next  most  popular  chart  was  actually a  Point  Cumulative  Summary  Chart.

Very  interesting,  it's  on  safety  data.

It's  not  using  points, it's  using,  looks  like  a  value  of  years.

That's  pretty  cool.

This  data  came  from  the Bureau of Transportation Statistics,

and  why  I  liked  this  data  was it  not  only  gave  us  a  index  of  crash  rate

and  injury  rates,  and  this  is  all based  off  millions  of  miles  driven,

but  for  each  year, like  in  1998  year,

it  told  us  that  the  dual  front airbags  was  the  safety  innovation

that  came  in  that  year.

T his  would  be  cool  to  see  what's going  on  with  my  line  chart.

I'm  going  to  go  graph,   Graph Builder.

We'll  go  ahead  and  take both  crash  and  injury  rate,

put  it  on  the  Y, put  year  on  the  X.

I'm  going  to  turn  off  the  smoother line here  and  just  look  at  the  points.

And  can  I  tell  any  difference between  crash  rate  and  injury  rate?

I  really  can't. This  is  where  having  a  cumulative  summary

would be  really  cool

because  I  can  go under  the  summary  statistic,

under  the  Points  element  and  just  change this  out  from  none  to  cumulative  summary.

Now,  do  you  get  a  sense  of  the differences  in  the  slope  of  the  line?

You  should,  because  the  summary  of  the crash  rate  definitely  has  a  steep  line,

and  I  would  expect  this,

there's  more  people on  the  Earth  now  driving  more  miles .

But  you  can  see  that  it  looks  like the  injury  rate  has  less  steep  slope

and  seems  to  be  flattening  out.

And  maybe  that's because  of  these  innovations.

Here  under  my  Axis  Settings for  the  X- axis,  I  can  put  in  like  in  1998,

there  were  the  dual  airbags.

And  see  if  that  might  be an  inflection  point, a  cause  of  cars

that  are  now  protecting us  more  from  injury.

That's  pretty  cool. The  other  cool  thing  to  do,

you  could  as  well  under  your  points  red triangle,  set  the  shape  column  by  year.

And  even  though  it's  continuous, it's  just  going  to  give  you  the  value

in  this  case,  that  is  really  cool. So  now  I'm  seeing  it  by  year.

Very  nice. Then  I  have  a  view  in  here

where  I  have  gone  through and  added  a  whole  bunch

of  the  safety  innovations  over  time and  put  a  nice  more  transparent

airbag  background  because airbags  was  a  big  deal.

But  you  can  see  when  things like  blind  spot  warnings  came  in,

anti- lock  brake [inaudible 00:22:34]   technology.

Really  cool  to  see  how  the  industry is  helping  to  save  us  from  injuries.

All  right, [inaudible 00:22:45]   right  along.

Our  next  to  last  chart,  but  still  very popular  review,  is  Advanced  Box  Plots.

There's  a  lot  more  you  can  do with  box plots  to  integrate  them

even  with  other elements  like  points  and  labels.

And  we're  going  to  look at  some  climate  city  risk.

And  this  is  some  really  fun  data that  I  found  on  looking  out,

projecting  out  to  2050.

And  it  was  coming  up with  this  total  climate  change

risk  index  on  a 1- 100  scale.

And  it  was  looking  at  things  like potential  sea  rise,  shifts  in  temperature.

Shifts  in  climate  is  something very  important  for  a  lot  of  us,

especially  us  out  in  the  West  Coast, which  is  water  stress  or  water  scarcity.

And  that's  how  I  came  up  with  this total  climate  change  risk  score.

If  I  want  to  see  what  that  one is  looking  like  on  a  box  plot,

it  would  be  pretty  easy  to  just take my  total  climate  change  on  the  Y.

Take  my...  Well,  actually, I'm  going  to  put  it  on  the  X.

There  we  go.

And  I'm  going  to  do  it  by  region  on  the  Y.

Now  that's  going  to  allow  me to  then  ask  for  some   box plots

and  here  we  go. It's  not  so  interesting  to  me.

I'm  going  to  hold  my  Shift  key down  and  add  back  in the  points.

Now,  boring  box  plots  don't  have  to  be boring  anymore  because  now  I  have

different  types of  box  plot  types  I  can  do  in  styles.

Under  style  I  got  this  Solid  Style.

Now  it  colors  it  in, which  is  pretty  cool.

And  as  well, you  can  go  and  notch  them,

and  you  can  go  and  add  fences  to  them. By  the  way,  it's  got  the  Outlier  selected

and  since  it  looks  like  on  this  data  set, you  can  see  I've  turned  the  labels  on,

I've  already  sorted  this by  total  climate  risk.

I  just  want  to  label  the  top 10 that's  already  on  there.

I  can  turn  off  this  outlier  and  that  takes any  duplications  out  of  there

and  that's  what  we're  looking  at, which  is  pretty  cool.

Maybe  change  this  color.

By  the  way,  if  you  cannot  see your  points  in the boxplot,

sometimes  if  you  put the  box  plot  in  last,

it  would  have  moved  it  forward and  it's  over  top  of  your  points.

So  then  all  you  have  to  do  is go  into  your  points  and  move  it  forward.

Just  right- clicking  into  your  graph and  just  go  into  the  right  element

and  bringing  it  forward.

That  is  pretty  cool.

And  you  can  see  what's  going  on where  we  have  the  highest  risk

of  cities  running in  the  climate  change  risk  in  2050

and  usually  things  coastal are  at  extreme  risk  of  water  shortage.

Very  cool.  All  right. And  as  well,

I  put  a  nice  little  background  picture in  the  background  on  this  one.

It  moved  the  legend  in  a  little  bit,  so that's  all  in  the  instructions  as  well.

All  right,  so  we  are  to  our  last

beautiful  pictures from  the  gallery  review.

And  that's  a  Wind  Rose  Chart, and  I  was  thinking  that

we're  getting  a  lot  of  adverse  weather

given  the  changes  in  our  climate, and  so  we're  always  trying  to  get  better

at  predicting  which  way are  the  winds  blowing,  how  strong,

where  are  hurricanes  going,  tornadoes, typhoons,  all  these  types  of  things.

There  is  a  cool  view  and  this is  not  limited  to  JMP  16.

But it is a  type  of... The  pie  chart  is  actually  a  version

of  a  Coxcomb  chart that  will  make  a  compass  rose.

If  I  can  get  it  labels  that  tell  it like  in  a compass,  what's  north  east?

What's  north  west? Those  type  of  compass  directions.

I  can  come  up  with  a  pretty  cool  pie  chart

that  lets  me  segment that  chart  by,  in  this  case,  wind speed.

So  let's  take  a  look  at  this  data.

There  we  go. This  is  a day's  worth  of  data

in  the  Great  Lakes  area.

If  you  take  a  look  here  at  the  6th  row, you  can  see  that  I  not  only  have  latitude

and  longitude  and  the  speed, where  it  starts,  how  strong  the  wind  was,

what  direction  it  was  going, and  then  of  course,  I  can  get  that

into  a  compass  direction like  west  southwest.

With  that  I  should  be  able  to  go

and  just  put  that  compass  direction down  on  the  X,  ask  for  a pie  chart,

but not  only  any  kind  of  pie  chart, I  am  going  to  ask  for  the   Coxcomb chart

and  I'm  going  to  take  the  wind  speed

and  I'm  going  to  overlay it  by  the  wind  speed.

You  can  play  with  these  colors, I  might  move  this  in  a  little  bit.

I  might  make  the  really  fast  winds  red.

And  now  I  can  see  that  they  were mainly  in  this  direction  on  the  compass.

That  was  where  predominantly most  of  the  wind  was

and  where  some of  the  darker  red  was  as  well.

Very  cool.

I  have  a  couple  of  versions  with  this, you  might  have  seen  that  I  brought  in

kind  of  an  old  type  of  wind  direction  map where  they're  drawing  the  wind  vectors

onto  a  map,  which  is  pretty  cool,

and  if  you  want  to  see  how  to  do  that  one, I  put  this  in  the  instructions  as  well.

And  if  I  open  the  control  panel  back  up,

and  I  go  under  the  spread hot spot  where  points  are,

and  I  go  to  Set  Shape E xpression.

You  can  see  that there's  a  formula  behind  it.

And  what  this  formula  is  doing is  it's  looking  at  each  point,

which  is  plotted  by  the  latitude and  the  longitude  on  the  map.

Then  it  is  taking  the  wind  speed, it  is  drawing  an  arrow,

and  it's  drawing  a  bigger  arrow, of  course,  if  there  was  a  stronger  speed.

That's  kind  of  cool, and  that's  what  draws  those  blue  lines

that  you're  seeing  involved  right  there.

All  right,  all  those are  in  your  instructions.

I'm  just  about  out  of  time  here, I  will  show  you  that  I  have  put

into  the  journal  that  I'm giving  you  where  to  learn  more.

You  can  see  other  galleries, you  can  see  blogs  in  journals,

other  presentations, and  even  great  tutorials.

They're  all  from  the JMP C ommunity,  community.jmp.com.

Those  are  there  for  you.

Go  have  fun  with  your Pictures  from  the  Gallery  7.

Go  try  to  recreate  these  views  on  your  own data  so  they  can  be  nice  and  compelling,

and  do  use your  curiosity, time,  and  skills  to  help  save  the  planet.