promoters_top10
detractors_top10
viewof communities = vl.markBar()
.data(community_data)
.encode(
vl.color().fieldN('community_type'),
vl.x().fieldN('community').title("Community").axis({titleFontSize:12}),
vl.y().fieldQ('user_count').title("Number of Users").axis({titleFontSize:12}), //.sort(vl.sum('cases').order('descending'),
vl.tooltip(['user_count']))
.height(height/3)
.width(width/3)
.padding("20")
.render()
viewof account_status = vl.markBar({tooltip: {"content": "data"}, size:5})
.data(community_data)
.encode(
vl.color().fieldN('community_type'),
vl.x().fieldQ(
vl.repeat("repeat")
).axis({grid: false, titleFontSize:"13", labelFontSize: "12"}),
vl.y().fieldN('community').axis({grid: false, title: false, labelFontSize: "12"}),
//vl.y().fieldN('community_type').axis({grid: false, title: "Community Type", titleFontSize:"12", labelFontSize: "12"}),
//vl.tooltip().fieldT("date") //([vl.fieldT("date"), "total_cases", "total_hospitalizations"])
//vl.color( {"value": "teal"})
)
.height(height/9)
.width(width/4)
.repeat([
"active_users_p",
"deleted_users_p",
"suspended_p"
])
.columns(1)
//.title({text:"Total Cases, Hospitalizations, and Deaths in VA over Time", fontSize:"30", offset:"30"})
.padding("20")
.render()
viewof account_status_percent = vl.markBar({tooltip: {"content": "data"}, size:5})
.data(user_status_data)
.transform(
vl.groupby('community_type','user_status').aggregate(vl.average('percentage').as('total')))
.encode(
vl.color().fieldN('user_status'),
vl.x().fieldQ('total'),
vl.y().fieldN('community_type'
//vl.repeat("repeat")
)
)
// .repeat(['detractors',
// 'promoters'])
// .columns(1)
.padding("20")
.render()
viewof account_status_1 = vl.markBar({tooltip: {"content": "data"}, size:5})
.data(user_status_data)
.transform(
vl.groupby('user_status').aggregate(vl.average('percentage').as('total')))
.encode(
vl.x().fieldQ('total'),
vl.y().fieldN('user_status')
)
.padding("20")
.render()
viewof account_status_new_repeat = vl.markBar({tooltip: {"content": "data"}, size:5})
.data(user_status_data)
.transform(
vl.groupby('community_type','user_status').aggregate(vl.average('percentage').as('total_percentage')))
.encode(
vl.color().fieldN('user_status'),
vl.x().fieldQ('total_percentage'),
vl.y().fieldN('community_type'),
vl.y().fieldN(
vl.repeat("repeat")
)
)
.repeat(['detractors',
'promoters'])
.columns(1)
.padding("20")
.render()
viewof account_status_dp = vl.markBar({tooltip: {"content": "data"}, size:5})
.data(community_data)
.transform(
vl.groupby('community_type').aggregate(vl.sum('user_count').as('Users'), vl.sum('active_users').as('Active'),vl.sum('deleted_users').as('Deleted'),vl.sum('suspended_users').as('Suspended') ),
vl.calculate("datum.Active/datum.Users * 100").as("Percentage of Active Users"),
vl.calculate("datum.Deleted/datum.Users * 100").as("Percentage of Deleted Users"),
vl.calculate("datum.Suspended/datum.Users * 100").as("Percentage of Suspended Users")
)
.encode(
vl.color().fieldN('community_type'),
vl.x().fieldQ(
vl.repeat("repeat")
).axis({grid: false, titleFontSize:"13", labelFontSize: "12"}),
vl.y().fieldN('community_type').axis({grid: false, title: false, labelFontSize: "12"}),
//vl.y().fieldN('community_type').axis({grid: false, title: "Community Type", titleFontSize:"12", labelFontSize: "12"}),
//vl.tooltip().fieldT("date") //([vl.fieldT("date"), "total_cases", "total_hospitalizations"])
//vl.color( {"value": "teal"})
)
.width(width/5)
.repeat([
"Percentage of Active Users",
"Percentage of Deleted Users",
"Percentage of Suspended Users"
])
.columns(1)
//.title({text:"Total Cases, Hospitalizations, and Deaths in VA over Time", fontSize:"30", offset:"30"})
.padding("20")
.render()
viewof account_status_percentage = vl.markBar({tooltip: {"content": "data"}, size:20})
.data(user_status_data)
.params('select')
.transform(
vl.groupby('community_type','user_status').aggregate(vl.average('percentage').as('total')))
.encode(
vl.color().fieldN('user_status'),
vl.x().fieldQ('total'),
vl.y().fieldN('community_type'))
.height(height/6)
.width(width/2)
.padding("20")
.render()
viewof account_status1 = vl.markBar({tooltip: {"content": "data"}, size:15})
.data(user_status_data)
.transform(
vl.groupby('community_type', 'user_status', 'community').aggregate(vl.average('percentage').as('total_p')),
vl.calculate('datum.total_p/5').as('total')
)
.encode(
vl.color().fieldN('community_type'), //.scale( {"range": ["#7aacb3", "#006666"]}),
vl.x().fieldQ('total').title("Number of Users").axis({titleFontSize:12}),
vl.y().fieldN('user_status').title("Status").axis({titleFontSize:12}),
)
.title({text: "Account Status of Users", subtitle: "Suspended and deleted users were found to be mostly promoters" , color: "#ad6d9c", subtitleColor: "#856a7e", fontWeight: "bold", fontSize: "15"})
.height(0.08*height)
.width(width/2.7)
.padding("20")
.render()
viewof tweets = vl.markCircle({size: 50})
.data(tweet_data)
.params(vl.selectInterval().bind("scales"))
.encode(
vl.color().fieldN('community_type'),
vl.x().fieldQ("RTs").axis({ title: "Number of Retweets", titleFontSize:"12", labelFontSize: "15", tickCount:15}).scale({"domain": [0,30000]}), //.scale({"type": "log"}) // .timeUnit('utcmonthdate'),
vl.y().fieldQ("QTs").axis({title: "Number of Quote Tweets", titleFontSize:"12", labelFontSize: "15"}).scale({"domain": [0,6000]}),
vl.tooltip([vl.fieldN("tweet_id"), "RTs", "QTs"]), //.fieldQ("cases")
//vl.color( {"value": "teal"})
)
//.title( {text:"Total Cases Vs. Deaths Reported per Each Locality in VA", fontSize:"30"})
.height(height/3)
.width(width/3)
.padding("20")
//.background("#f5f7ff")
.render()
viewof users = vl.markPoint({size: 40})
.data(user_data)
.params(vl.selectInterval().bind("scales"))
.encode(
vl.color().fieldN('community_type'),
vl.x().fieldQ("RTs").axis({title: "Number of Retweets", titleFontSize:"12", labelFontSize: "15", tickCount:15}).scale({"domain": [0,30000]}), //.scale({"type": "log"}) // .timeUnit('utcmonthdate'),
vl.y().fieldQ("QTs").axis({title: "Number of Quote Tweets", titleFontSize:"12", labelFontSize: "15"}).scale({"domain": [0,6000]}),
vl.tooltip([vl.fieldN("user_id"), "RTs", "QTs"]), //.fieldQ("cases")
vl.href().fieldN('user_url')
//vl.color( {"value": "teal"})
)
//.title( {text:"Total Cases Vs. Deaths Reported per Each Locality in VA", fontSize:"30"})
.height(height/3)
.width(width/3)
.padding("20")
//.background("#f5f7ff")
.render()
viewof urls_detractors1 = vl.layer(
vl.markBar()
.encode(
vl.color().value('#66b2b2'),
vl.x().fieldQ('RTs_community0').title("Number of Retweets"),
vl.y().fieldN('domain').axis(null).title("Top 10 Domains").sort(vl.fieldQ('RTs_community0').order('descending')),
vl.tooltip(['RTs_community0'])
),
vl.markText({align: 'left', x: 1}).encode(vl.text().fieldN('domain'))
)
.data(detractors_top10)
.height(height/3)
.width(width/3)
.padding("20")
//.background("#f5f7ff")
.render()
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
