Preamble¶
import pandas as pd
from plotapi import LineFight
LineFight.set_license("your username", "your license key")
Introduction¶
Plotapi BarFight
, PieFight
, and LineFight
, expect a list
of dict
items that define the value of nodes over time. The following is an example of this data structure.
samples = [
{"order": 2000.01, "name": "Sankey", "value": 10},
{"order": 2000.01, "name": "Terminus", "value": 10},
{"order": 2000.01, "name": "Chord", "value": 40},
{"order": 2000.01, "name": "Bar Fight", "value": 90},
{"order": 2000.01, "name": "Pie Fight", "value": 70},
{"order": 2000.02, "name": "Sankey", "value": 30},
{"order": 2000.02, "name": "Terminus", "value": 20},
{"order": 2000.02, "name": "Chord", "value": 40},
{"order": 2000.02, "name": "Bar Fight", "value": 120},
{"order": 2000.02, "name": "Pie Fight", "value": 55},
{"order": 2000.03, "name": "Sankey", "value": 35},
{"order": 2000.03, "name": "Terminus", "value": 45},
{"order": 2000.03, "name": "Chord", "value": 60},
{"order": 2000.03, "name": "Bar Fight", "value": 85},
{"order": 2000.03, "name": "Pie Fight", "value": 100},
{"order": 2000.04, "name": "Sankey", "value": 25},
{"order": 2000.04, "name": "Terminus", "value": 60},
{"order": 2000.04, "name": "Chord", "value": 90},
{"order": 2000.04, "name": "Bar Fight", "value": 50},
{"order": 2000.04, "name": "Pie Fight", "value": 105},
{"order": 2000.05, "name": "Sankey", "value": 60},
{"order": 2000.05, "name": "Terminus", "value": 80},
{"order": 2000.05, "name": "Chord", "value": 120},
{"order": 2000.05, "name": "Bar Fight", "value": 30},
{"order": 2000.05, "name": "Pie Fight", "value": 95},
]
Dataset¶
Let’s work backwards to the DataFrame
, our starting point for this data wrangling exercise.
df = (
pd.DataFrame(samples)
.pivot(index="order", columns="name")["value"]
.reset_index()
.rename_axis(None, axis=1)
)
df
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order | Bar Fight | Chord | Pie Fight | Sankey | Terminus | |
---|---|---|---|---|---|---|
0 | 2000.01 | 90 | 40 | 70 | 10 | 10 |
1 | 2000.02 | 120 | 40 | 55 | 30 | 20 |
2 | 2000.03 | 85 | 60 | 100 | 35 | 45 |
3 | 2000.04 | 50 | 90 | 105 | 25 | 60 |
4 | 2000.05 | 30 | 120 | 95 | 60 | 80 |
Great! Now let’s work back to the samples dict
.
Wrangling¶
Our journey back to the samples list
of dict
items will be through pandas.melt
.
df_melted = pd.melt(
df,
id_vars="order",
value_vars=list(df.columns[1:]),
var_name="name",
value_name="value",
)
df_melted.head(10)
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order | name | value | |
---|---|---|---|
0 | 2000.01 | Bar Fight | 90 |
1 | 2000.02 | Bar Fight | 120 |
2 | 2000.03 | Bar Fight | 85 |
3 | 2000.04 | Bar Fight | 50 |
4 | 2000.05 | Bar Fight | 30 |
5 | 2000.01 | Chord | 40 |
6 | 2000.02 | Chord | 40 |
7 | 2000.03 | Chord | 60 |
8 | 2000.04 | Chord | 90 |
9 | 2000.05 | Chord | 120 |
We’re nearly there. This next step is optional – we’re going to sort by order
.
df_melted = df_melted.sort_values("order")
df_melted.head(10)
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order | name | value | |
---|---|---|---|
0 | 2000.01 | Bar Fight | 90 |
20 | 2000.01 | Terminus | 10 |
5 | 2000.01 | Chord | 40 |
15 | 2000.01 | Sankey | 10 |
10 | 2000.01 | Pie Fight | 70 |
1 | 2000.02 | Bar Fight | 120 |
21 | 2000.02 | Terminus | 20 |
6 | 2000.02 | Chord | 40 |
16 | 2000.02 | Sankey | 30 |
11 | 2000.02 | Pie Fight | 55 |
Now for the final step – let’s get our list
of dict
items.
samples = df_melted.to_dict(orient="records")
samples
[{'order': 2000.01, 'name': 'Bar Fight', 'value': 90}, {'order': 2000.01, 'name': 'Terminus', 'value': 10}, {'order': 2000.01, 'name': 'Chord', 'value': 40}, {'order': 2000.01, 'name': 'Sankey', 'value': 10}, {'order': 2000.01, 'name': 'Pie Fight', 'value': 70}, {'order': 2000.02, 'name': 'Bar Fight', 'value': 120}, {'order': 2000.02, 'name': 'Terminus', 'value': 20}, {'order': 2000.02, 'name': 'Chord', 'value': 40}, {'order': 2000.02, 'name': 'Sankey', 'value': 30}, {'order': 2000.02, 'name': 'Pie Fight', 'value': 55}, {'order': 2000.03, 'name': 'Terminus', 'value': 45}, {'order': 2000.03, 'name': 'Sankey', 'value': 35}, {'order': 2000.03, 'name': 'Pie Fight', 'value': 100}, {'order': 2000.03, 'name': 'Chord', 'value': 60}, {'order': 2000.03, 'name': 'Bar Fight', 'value': 85}, {'order': 2000.04, 'name': 'Pie Fight', 'value': 105}, {'order': 2000.04, 'name': 'Chord', 'value': 90}, {'order': 2000.04, 'name': 'Sankey', 'value': 25}, {'order': 2000.04, 'name': 'Bar Fight', 'value': 50}, {'order': 2000.04, 'name': 'Terminus', 'value': 60}, {'order': 2000.05, 'name': 'Pie Fight', 'value': 95}, {'order': 2000.05, 'name': 'Chord', 'value': 120}, {'order': 2000.05, 'name': 'Sankey', 'value': 60}, {'order': 2000.05, 'name': 'Bar Fight', 'value': 30}, {'order': 2000.05, 'name': 'Terminus', 'value': 80}]
Perfect! We’re all done.
Visualisation¶
No Plotapi exercise is complete without a visualisation.
As we can see, we have set our license details in the preamble with LineFight.set_license()
.
Here we’re using .show()
which outputs to a Jupyter Notebook cell, however, we may want to output to an HTML file with .to_html()
instead.
LineFight(samples, format_current_order="0.2f").show()
#plotapi-chart-76680346 path {
fill: none;
stroke-linecap: round
}
#plotapi-chart-76680346 .tick:first-of-type text {
stroke-width: 0;
}
#plotapi-chart-76680346 .x_axis .tick:not(:first-of-type) line {
stroke-opacity: 0;
}
#plotapi-chart-76680346 .y_axis .tick:not(:first-of-type) line {
stroke: #999;
stroke-opacity: 0.5;
stroke-dasharray: 2,2
}
#plotapi-chart-76680346 .y_axis .tick:first-of-type line {
stroke-width: 0;
stroke: #999;
stroke-opacity: 0.4;
}
#plotapi-chart-76680346 .x_axis .tick:first-of-type line {
stroke-width: 0;
stroke: #999;
stroke-opacity: 0.4;
}
#plotapi-chart-76680346 .tick text {
fill: #999;
}
#plotapi-chart-76680346 .domain {
stroke-width: 0;
}
#plotapi-chart-76680346 .title {
stroke: #fcfcfc;
paint-order: stroke;
stroke-width: 3px;
stroke-linecap: butt;
stroke-linejoin: miter;
stroke-opacity: 0.4;
}
#plotapi-chart-76680346 .current_order_text {
font-size: 2em;
font-weight: bold;
fill-opacity: 0.4;
fill: #000;
font-size: 2em;
paint-order: stroke;
stroke: #fcfcfc;
stroke-width: 2px;
stroke-linecap: butt;
stroke-linejoin: miter;
stroke-opacity: 1;
font-weight: bold;
}
#plotapi-chart-76680346 {
font-family: “Lato”, sans-serif;
text-align: center;
}
#plotapi-chart-76680346 .event_detail_bg {
fill: black;
opacity: 0.7;
}
#plotapi-chart-76680346 .event_detail_text div,
#plotapi-chart-76680346 .event_detail_text p,
#plotapi-chart-76680346 .event_detail_text span {
font-size: 16px;
}
#plotapi-chart-76680346 text::selection,
#plotapi-chart-76680346 div::selection,
#plotapi-chart-76680346 img::selection,
#plotapi-chart-76680346 p::selection {
background: none;
}
(function() {
var jupyter_classic = !(typeof(IPython)===”undefined”);
var dependencies_paths = {
‘d3’: ‘https://plotapi.com/static/js/d3.v7.min’,
‘pako’: ‘https://plotapi.com/static/js/pako.min’
}
if(jupyter_classic){
require.config(
{
paths: dependencies_paths
}
);
require([‘d3’, ‘pako’], function(d3, pako) {
window.d3 = d3;
window.pako = pako;
plotapi_plot();
});
}
else{
var dependencies = Object.values(dependencies_paths);
function dependency_loader(dependencies_loaded){
var script = document.createElement(“script”);
script.type = “text/javascript”;
script.src = dependencies[dependencies_loaded] + “.js”;
script.onload = function () {
if(dependencies_loaded {
update(elapsed);
});
function update(elapsed) {
if (elapsed_time > 0) {
d3.select(“#plotapi-chart-76680346_svg .event_group”).transition().duration(250).style(“opacity”, 0);
elapsed_time = 0;
last_proc = elapsed;
} else {
if (sequence_index = 2000 || skip_first) {
skip_first = false;
current_order_text.text(
format_current_order(sequence[sequence_index])
);
show_event();
sequence_index++;
update_current(sequence_index);
last_proc = elapsed;
}
}
}
let last_event_duration = 0;
if (elapsed – last_proc a.id);
contestants.sort((a, b) => b.current_value – a.current_value);
current_order = contestants.map((a) => a.id);
var delta = elapsed – last_proc;
draw(delta);
} else if (sequence_index == sequence.length – 1) {
last_event_duration = show_event();
contestants.sort((a, b) => b.current_value – a.current_value);
draw(2000);
d3.select(“#plotapi-chart-76680346_svg .event_group”).transition().delay(last_event_duration).duration(250).style(“opacity”, 0);
sequence_index++;
}
if (sequence_index == sequence.length && !finished) {
contestants.sort((a, b) => b.current_value – a.current_value);
update_minimap();
finished = true;
t.stop();
show_restart(last_event_duration);
}
}
function show_event(){
var event_fired = false;
var element = events.find(item => {
return item.order === sequence_index
})
if(element == undefined){
return 0;
}
timer_stop(element);
d3.select(“#plotapi-chart-76680346_svg .event_detail_text”).html(function (d) {
return (
‘
element.event +
“
”
);
});
d3.select(“#plotapi-chart-76680346_svg .event_group”)
.interrupt()
.transition()
.duration(250)
.style(“opacity”, 1)
;
return element.duration ? element.duration : 5000
}
function update_current(current) {
x_travel_scale = d3
.scaleLinear()
.domain([0, 2000])
.range([sequence[sequence_index-1], sequence[sequence_index]]);
if (sequence_index > 0) {
update_minimap();
}
current_data = data.filter((d) => d.order == current);
for (var index = 0; index d.id == element.id);
if (contestant.length != 0) {
if(sequence_index > 1 && contestant[0].line_data.length == 1){
contestant[0].icon.transition()
.duration(200)
.style(“opacity”, 1)
contestant[0].line_path.transition()
.duration(200)
.style(“opacity”, 1)
contestant[0].line_path_bg.transition()
.duration(200)
.style(“opacity”, 0.25)
}
if (!isNaN(element.value)) {
contestant[0].current_value = contestant[0].target_value;
contestant[0].target_value = element.value;
contestant[0].line_data.push({“x”:sequence[sequence_index],”y”: contestant[0].current_value})
contestant[0].travel_scale = d3
.scaleLinear()
.domain([0, 2000])
.range([contestant[0].current_value, element.value]);
}
} else {
var target_value = !isNaN(element.value) ? element.value : 0;
var x_pos = 0;
contestant_rect = d3
.select(“#plotapi-chart-76680346_svg .bar_group”)
.append(“rect”)
.attr(“x”, 0)
.attr(“y”, y_scale(index))
.attr(“width”, x_pos)
.attr(“height”, bar_height)
.style(“fill”, color(element.id))
.style(“display”, “none”)
;
contestant_icon_image = icon(element.id);
if(contestant_icon_image == undefined){
contestant_icon = d3
.select(“#plotapi-chart-76680346_svg .bar_group”)
.append(‘circle’)
.attr(“cx”, 0)
.attr(“cy”, y_scale(index) + icon_padding)
.attr(‘r’, icon_size/2)
.style(“opacity”, 1)
.style(“stroke-opacity”, 0.25)
.attr(“stroke-width”, 8)
.attr(“stroke”, darken_color(color(element.id),-0.5))
.attr(‘fill’, color(element.id));
}
else{
contestant_icon = d3
.select(“#plotapi-chart-76680346_svg .bar_group”)
.append(“image”)
.attr(“x”, 0)
.attr(“y”, y_scale(index) + icon_padding)
.attr(“width”, icon_size)
.attr(“height”, icon_size)
.style(“opacity”, 1)
.attr(“xlink:href”, contestant_icon_image)
}
contestant_icon
.on(“mouseover”, function (d, i) {
d3.selectAll(“#plotapi-chart-76680346_svg .bartext_group .grp”+element.id)
.transition()
.duration(200)
.style(“opacity”, 1);
}
)
.on(“mouseout”, function (d, i) {
d3.selectAll(“#plotapi-chart-76680346_svg .bartext_group .grp”+element.id)
.transition()
.transition()
.duration(200)
.style(“opacity”, 0);
}
);
contestant_line_path_bg = line_group.append(“path”)
.attr(“stroke-width”, 12)
.style(“stroke”, color(element.id))
.style(“opacity”, 0.25);
contestant_line_path = line_group.append(“path”)
.style(“stroke”, color(element.id))
.attr(“stroke-width”, 4)
if(sequence_index > 0){
contestant_icon.style(“opacity”, 0);
contestant_line_path.style(“opacity”, 0);
contestant_line_path_bg.style(“opacity”, 0);
}
contestant_text_value = d3
.select(“#plotapi-chart-76680346_svg .bartext_group”)
.append(“text”)
.attr(“x”, x_pos – 5)
.attr(“y”, bar_text_upper_y(index))
.text(element.value)
.style(“text-anchor”, “end”)
.style(“dominant-baseline”, “central”)
.style(“fill”, “black”)
.attr(“opacity”,”0″)
.style(“font-size”, bartext_font_size + “px”)
.classed(“grp”+element.id,true);
contestant_text_name = d3
.select(“#plotapi-chart-76680346_svg .bartext_group”)
.append(“text”)
.attr(“x”, 0)
.attr(“y”, bar_text_lower_y(index))
.text(unique_names[element.id])
.style(“text-anchor”, “end”)
.style(“dominant-baseline”, “central”)
.style(“fill”, “black”)
.attr(“opacity”,”0″)
.style(“font-weight”, “900”)
.style(“font-size”, bartext_font_size + “px”)
.classed(“grp”+element.id,true);
contestant = {
id: element.id,
rect: contestant_rect,
line_data: [{“x”:sequence[sequence_index],”y”: target_value}],
line_path: contestant_line_path,
line_path_bg: contestant_line_path_bg,
icon_image: !(contestant_icon_image == undefined),
icon: contestant_icon,
text_value: contestant_text_value,
text_name: contestant_text_name,
current_value: target_value,
target_value: target_value,
travel_scale: d3
.scaleLinear()
.domain([0, 2000])
.range([target_value, target_value]),
};
contestants.push(contestant);
}
}
}
function draw(delta) {
x_axis_current_x = x_travel_scale(delta);
x_scale = d3
.scaleLinear()
.domain([sequence[0], sequence[sequence.length-1]])
.range([0, 760.0]);
x_axis.scale(x_scale);
x_scale_current_x = x_scale(x_axis_current_x);
d3.select(“#plotapi-chart-76680346_svg”)
.select(“.x_axis”)
.transition()
.duration(250)
.ease(d3.easeLinear)
.call(x_axis);
for (var index = 0; index d.current_value);
if (new_max != current_max) {
current_max = new_max;
y_scale = d3
.scaleLinear()
.domain([10.0, 120.0])
.range([420, 0]);
y_axis.scale(y_scale);
d3.select(“#plotapi-chart-76680346_svg”)
.select(“.y_axis”)
.transition()
.duration(250)
.ease(d3.easeLinear)
.call(y_axis);
}
var y_scale_current_y = y_scale(element.current_value);
element.line_data[element.line_data.length-1].y = element.current_value
element.line_data[element.line_data.length-1].x = x_axis_current_x
var line = d3.line()
.x(function(d,i) { return x_scale(d.x);})
.y(function(d) { return y_scale(d.y);})
var path = element.line_path
.attr(“d”, line(element.line_data))
var path_bg = element.line_path_bg
.attr(“d”, line(element.line_data))
element.text_name
.attr(
“x”,
x_scale_current_x –
text_padding –
(icon_size/2)
)
.attr(“y”, bar_text_lower_y(y_scale_current_y));
element.text_value
.attr(
“x”,
x_scale_current_x –
text_padding –
(icon_size/2)
)
.text(format_value(element.current_value))
.attr(“y”, bar_text_upper_y(y_scale_current_y));
element.rect.attr(“width”, x_scale_current_x);
element.icon
.attr(
“x”,
x_scale_current_x – (icon_size/2)
)
.attr(“y”, y_scale_current_y – ((icon_size)/2))
.attr(
“cx”,
x_scale_current_x
)
.attr(“cy”, y_scale_current_y);
if (
false
) {
element.rect
.interrupt()
.transition()
.ease(d3.easeSinOut)
.duration(500)
.attr(“y”, y_scale(index));
element.icon
.interrupt()
.transition()
.ease(d3.easeSinOut)
.duration(500)
.attr(“y”, y_scale(index) + icon_padding);
element.text_name
.interrupt()
.transition()
.ease(d3.easeSinOut)
.duration(500)
.attr(“y”, bar_text_lower_y(index));
element.text_value
.interrupt()
.transition()
.ease(d3.easeSinOut)
.duration(500)
.attr(“y”, bar_text_upper_y(index));
}
}
}
}
function initialise() {
contestants = [];
d3.select(“#plotapi-chart-76680346_svg .line_group”)
.selectAll(“*”)
.remove();
d3.select(“#plotapi-chart-76680346_svg .bar_group”)
.selectAll(“*”)
.remove();
d3.select(“#plotapi-chart-76680346_svg .bartext_group”)
.selectAll(“*”)
.remove();
d3.select(“#plotapi-chart-76680346_svg .minimap_group”)
.selectAll(“*”)
.remove();
last_proc = 0;
top_n = 5;
bar_padding = 0;
bar_height = d3.max([420 / 5 – bar_padding, 0]);
icon_padding =0;
text_padding = 5;
current_order = [];
last_order = [];
elapsed_time = 0;
sequence_index = 0;
current_max = null;
bartext_font_size = 14;
icon_size = 40
y_scale = d3
.scaleLinear()
.domain([10.0, 120.0])
.range([420, 0]);
update_current(sequence_index);
current_order_text.text(format_current_order(sequence[sequence_index]))
new_max = d3.max(contestants, (d) => d.current_value);
if (new_max != current_max) {
current_max = new_max;
}
x_scale = d3
.scaleLinear()
.domain([sequence[0], sequence[sequence.length-1]])
.range([0, 760.0]);
x_axis = d3
.axisBottom()
.scale(x_scale)
.ticks(sequence.length-1, undefined)
.tickSize(-420)
.tickFormat((d) => d3.format(“,”)(d));
y_axis = d3
.axisLeft()
.scale(y_scale)
.ticks(7.6, undefined)
.tickSize(-760.0)
.tickFormat((d) => d3.format(“,”)(d));
d3.select(“#plotapi-chart-76680346_svg .axis_group”)
.selectAll(“*”)
.remove();
var x_axis_line = d3
.select(“#plotapi-chart-76680346_svg .axis_group”)
.append(“g”)
.attr(“class”, “axis x_axis”)
.attr(“transform”, `translate(0, 420)`)
.call(x_axis)
.selectAll(“.tick line”)
.classed(“origin”, (d) => d == 0);
var y_axis_line = d3
.select(“#plotapi-chart-76680346_svg .axis_group”)
.append(“g”)
.attr(“class”, “axis y_axis”)
.attr(“transform”, `translate(0, 0))`)
.call(y_axis)
d3.select(“#plotapi-chart-76680346_svg”)
.select(“.y_axis”)
.style(“text-anchor”, “start”)
}
function darken_color(color, factor) {
return d3.color(color).darker(factor)
}
function color(index) {
node = nodes[index];
if (node.color) {
return node.color;
}
var ratio = index / (5);
return d3.interpolateRainbow(ratio);
}
function icon(index) {
node = nodes[index];
if (node.icon) {
return node.icon;
}
return undefined;
}
function bar_text_upper_y(index) {
return (index-(icon_size/2) ) + icon_size * 0.75;
}
function bar_text_lower_y(index) {
return (index-(icon_size/2) ) + icon_size * 0.25;
}
function update_minimap() {
var minimap_order = contestants.slice();
minimap_order.sort((a, b) => b.current_value – a.current_value);
minimap_order = minimap_order.slice(0,6);
min_value = d3.min([minimap_order[minimap_order.length-1].current_value,0]);
minimap_order = minimap_order.slice(0,5);
if(min_value Math.abs(min_value) + item.current_value)
.reduce((prev, next) => prev + next);
}
else{
current_sum = minimap_order
.map((item) => item.current_value)
.reduce((prev, next) => prev + next);
}
if (current_sum != 0) {
var mm_bar_height = 42.0;
var mm_bar_drop_height = 126.0;
mm_y_scale = d3
.scaleLinear()
.domain([0, current_sum])
.range([0, mm_bar_height]);
mm_x_scale = d3
.scaleLinear()
.domain([0, sequence.length])
.range([0, 253.33333333333334]);
var mm_pos_x = mm_x_scale(sequence_index – 1);
var mm_width = mm_x_scale(1);
var mm_running_total = 0;
for (var mm_index = 0; mm_index < minimap_order.length; mm_index++) {
const element = minimap_order[mm_index];
var mm_pos_y = mm_y_scale(mm_running_total);
if(min_value < 0){
var mm_height = mm_y_scale(element.current_value + Math.abs(min_value));
}
else{
var mm_height = mm_y_scale(element.current_value);
}
d3.select("#plotapi-chart-76680346_svg .minimap_group")
.append("rect")
.attr("x", 506.66666666666663 + mm_pos_x)
.attr("y", 420 – mm_bar_drop_height + mm_pos_y)
.attr("width", mm_width)
.attr("height", mm_height)
.style("fill", color(element.id))
.style("opacity", 0)
.transition()
.duration(500)
.style("opacity", 1)
.attr("y", 420 – mm_bar_height + mm_pos_y);
if(min_value < 0){
mm_running_total += element.current_value + Math.abs(min_value);
}
else{
mm_running_total += element.current_value;
}
}
}
}
function timer_stop(element) {
elapsed_time = t._time;
t.stop();
d3.select("#plotapi-chart-76680346_svg .proceed")
.attr("width", 0)
.style("fill", "#420a91");
d3.select("#plotapi-chart-76680346_svg .proceed")
.interrupt()
.transition()
.ease(d3.easeLinear)
.duration(element.duration ? element.duration : 5000)
.attr("width", 253.33333333333334)
.style("fill", "#40f99b");
t.restart(update, element.duration ? element.duration : 5000);
}
function restart() {
d3.select("#plotapi-chart-76680346_svg .event_group").interrupt().style("opacity", 0);
d3.select("#plotapi-chart-76680346_svg .proceed").interrupt().attr("width", 0);
finished = false;
restart_opacity_lock = false;
skip_first = true;
t.stop();
t.restart(update, 0);
initialise();
d3.select("#plotapi-chart-76680346_restart")
.transition()
.ease(d3.easeQuad)
.duration(500)
.attr("width", 20)
.attr("height", 20)
.attr("x", 715.0)
.attr("y", -20)
.style("opacity", 0.6);
}
function show_restart(last_event_duration){
d3.select("#plotapi-chart-76680346_restart")
.transition()
.delay(last_event_duration)
.style(
"opacity",
0.6
);
d3.select("#plotapi-chart-76680346_restart")
.transition()
.ease(d3.easeQuad)
.delay(last_event_duration)
.duration(500)
.attr("width", 100)
.attr("height", 100)
.attr("x", 330.0)
.attr("y", 160.0)
.style("opacity", 0.6)
.on("end", function (d, i) { restart_opacity_lock = true; });
}
var event_detail_bg = d3.select("#plotapi-chart-76680346_svg .event_group")
.append("rect")
.attr("x", 506.66666666666663)
.attr("y", 220)
.attr("width", 253.33333333333334)
.attr("height", 200)
.attr("rx", 5)
.attr("ry", 5)
.classed("event_detail_bg", true);
var event_detail_text = d3.select("#plotapi-chart-76680346_svg .event_group")
.append("foreignObject")
.classed("event_detail_text", true)
.attr("x", 506.66666666666663)
.attr("y", 220)
.attr("width", 253.33333333333334)
.attr("height", 200)
.style("display", "block")
.style("color", "white")
.style("padding", "10px")
.html(function (d) {
return "";
});
d3.select("#plotapi-chart-76680346_svg .event_group").style("opacity", 0);
var event_detail_autoplay = d3.select("#plotapi-chart-76680346_svg .event_group")
.append("rect")
.attr("x", 506.66666666666663)
.attr("y", 210)
.attr("width", 0)
.attr("rx", 5)
.attr("ry", 5)
.attr("height", 10)
.style("opacity", 0.7)
.style("fill", "#420a91")
.classed("proceed", true);
var current_order_text = d3
.select("#plotapi-chart-76680346_svg .order_group")
.append("text")
.classed("current_order_text", true)
.attr("x", 755.0)
.attr("y", 415)
.text(format_current_order(sequence[sequence_index]))
.style("text-anchor", "end")
.style("dominant-baseline", "text-top");
initialise();
d3.select("#plotapi-chart-76680346_svg .overlay_group")
.append("svg:a")
.attr("xlink:href", "https://plotapi.com")
.attr("target", "_blank")
.append("image")
.attr("xlink:href", "https://plotapi.com/gallery/icon/plotapi.svg")
.attr("width", 20)
.attr("height", 20)
.attr("x", 740.0)
.attr("y", -20)
.style("opacity", 0)
.attr("id", "plotapi-chart-76680346_icon");
d3.select("#plotapi-chart-76680346_icon")
.append("title")
.text("Produced with Plotapi");
d3.select("#plotapi-chart-76680346_icon").on(
"mouseover",
function (d, i) {
d3.select("#plotapi-chart-76680346_icon").style("opacity", 1);
}
);
d3.select("#plotapi-chart-76680346_icon").on(
"mouseout",
function (d, i) {
d3.select("#plotapi-chart-76680346_icon").style("opacity", 0.6);
}
);
d3.select("#plotapi-chart-76680346_svg .overlay_group")
.append("svg:a")
.append("image")
.style("cursor", "pointer")
.attr("xlink:href", "https://plotapi.com/gallery/icon/restart.svg")
.attr("width", 20)
.attr("height", 20)
.attr("x", 715.0)
.attr("y", -20)
.style("opacity", 0)
.attr("id", "plotapi-chart-76680346_restart");
d3.select("#plotapi-chart-76680346_restart").on(
"click",
function (d, i) {
restart();
}
);
d3.select("#plotapi-chart-76680346_restart").on(
"mouseover",
function (d, i) {
d3.select("#plotapi-chart-76680346_restart").style("opacity", 1);
}
);
d3.select("#plotapi-chart-76680346_restart").on(
"mouseout",
function (d, i) {
d3.select("#plotapi-chart-76680346_restart").style(
"opacity",
0.6
);
}
);
d3.select("#plotapi-chart-76680346 svg").on(
"mouseenter",
function () {
d3.select("#plotapi-chart-76680346_icon").style("opacity", 0.6);
if (!restart_opacity_lock) {
d3.select("#plotapi-chart-76680346_restart").style(
"opacity",
0.6
);
}
}
);
d3.select("#plotapi-chart-76680346 svg").on(
"mouseleave",
function () {
d3.select("#plotapi-chart-76680346_icon").style("opacity", 0);
d3.select("#plotapi-chart-76680346_plus").style("opacity", 0);
d3.select("#plotapi-chart-76680346_minus").style("opacity", 0);
if (!restart_opacity_lock) {
d3.select("#plotapi-chart-76680346_restart").style(
"opacity",
0
);
}
}
);
}
}());
Here we can see the default behaviour of Plotapi LineFight
.
You can do so much more than what’s presented in this example, and we’ll cover this in later sections. If you want to see the full list of growing features, check out the Plotapi Documentation.