def test_dimension_func(monkeypatch, ndx):
monkeypatch.setattr(s, "DATA_COLUMNS", "{'close', 'open'}")
dat = ndx
fluctuation_eq = abs(VC("close") - VC("open"))
month_dim = Dimension("month", group_type="sum", func=fluctuation_eq)
assert 'Math.abs(d.close - d.open)' == month_dim.func
expected_str = '''
var month_dimension = facts.dimension(function(d){return d['month'];});
var month_group = month_dimension.group().reduceSum(function(d){
return Math.abs(d.close - d.open);
});
'''
expected_str_replaced = str(expected_str).replace("\n", "").replace(
" ", "").replace("\t", "")
asserted_str_replaced = str(month_dim).replace("\n", "").replace(
" ", "").replace("\t", "")
assert expected_str_replaced == asserted_str_replaced
def test_gainOrLossChart(ndx):
def gainOrLoss(x):
if x < 0:
return "Loss"
else:
return "Gain"
dat = ndx
dat["change"] = dat.close - dat.open
dat["gainOrLoss"] = dat.change.apply(gainOrLoss)
gainOrLoss_dim = Dimension("gainOrLoss")
gainOrLossChart = PieChart(
"gain-loss-chart",
gainOrLoss_dim,
width=180,
height=180,
radius=80,
inner_radius=40,
renderLabel=True,
label=Label("percent", precision=0),
transitionDuration=500,
colors=["#3182bd", "#6baed6", "#9ecae1", "#c6dbef", "#dadaeb"],
colorDomain=[-1750, 1644],
colorAccessor=True,
)
dc_documentation_string = """
var pie_chart_gain_loss_chart = dc.pieChart("#gain-loss-chart")
.width(180)
.height(180)
.radius(80)
.dimension(gainOrLoss_dimension)
.group(gainOrLoss_group)
.renderLabel(true)
.innerRadius(40)
.transitionDuration(500)
.colors(['#3182bd', '#6baed6', '#9ecae1', '#c6dbef', '#dadaeb'])
.colorDomain([-1750, 1644])
.colorAccessor(function(d, i){return d.value;});
pie_chart_gain_loss_chart.label(function (d) {
if (pie_chart_gain_loss_chart.hasFilter() && !pie_chart_gain_loss_chart.hasFilter(d.key)) {
return d.key + '(0%)';
}
var label = d.key;
if (all.value()) {
label += '(' + Math.floor(d.value / all.value() * 100)/1 + '%)';
}
return label;
});
"""
gainOrLossChart_replaced = (str(gainOrLossChart).replace("\n", "").replace(
" ", "").replace("\t", ""))
dc_documentation_string_replaced = (str(dc_documentation_string).replace(
"\n", "").replace(" ", "").replace("\t", ""))
assert gainOrLossChart_replaced == dc_documentation_string_replaced
def test_dayOfWeekChart(ndx):
def day_of_week(x):
y = pd.to_datetime(x)
return day_list[y.dayofweek]
dat = ndx
day_list = [
"Monday",
"Tuesday",
"Wednesday",
"Thursday",
"Friday",
"Saturday",
"Sunday",
]
dat["day_of_week"] = dat.date.apply(day_of_week)
day_of_week_dim = Dimension("day_of_week")
row_chart = RowChart(
"day-of-week-chart",
day_of_week_dim,
elasticX=True,
height=180,
width=180,
xAxis="ticks(4)",
label=Label("key", part=0),
)
dc_documentation_string = """
var row_chart_day_of_week_chart = dc.rowChart("#day-of-week-chart")
.width(180)
.height(180)
.margins({top: 20, left: 10, right: 10, bottom: 20})
.group(day_of_week_group)
.dimension(day_of_week_dimension)
.ordinalColors(['#3182bd', '#6baed6', '#9ecae1', '#c6dbef', '#dadaeb'])
.title(function (d) {
return d.value;
})
.elasticX(true)
.label(function (d) {
return d.key[0];
});
row_chart_day_of_week_chart.xAxis().ticks(4);
"""
row_chart_replaced = (str(row_chart).replace("\n",
"").replace(" ", "").replace(
"\t", ""))
dc_documentation_string_replaced = (str(dc_documentation_string).replace(
"\n", "").replace(" ", "").replace("\t", ""))
assert row_chart_replaced == dc_documentation_string_replaced
def test_fluctuationChart(ndx):
dat = ndx
dat["fluctuation"] = np.round((dat.close - dat.open) / dat.open * 100)
fluctuation_dim = Dimension("fluctuation")
fluctuation_chart = BarChart(
"volume-month-chart",
fluctuation_dim,
width=420,
height=180,
elasticY=True,
gap=1,
centerBar=True,
alwaysUseRounding=True,
round='dc.round.floor',
margins=Margin(top=10, right=50, bottom=30, left=40),
xAxis="tickFormat(function(v){return v+'%';})",
yAxis="ticks(5)",
x='d3.scaleLinear().domain([-25, 25])',
filter_printer=True)
dc_documentation_string = """
var bar_chart_volume_month_chart = dc.barChart("#volume-month-chart")
.width(420)
.height(180)
.margins({top: 10, right: 50, bottom: 30, left: 40})
.dimension(fluctuation_dimension)
.group(fluctuation_group)
.elasticY(true)
.centerBar(true)
.gap(1)
.round(dc.round.floor)
.alwaysUseRounding(true)
.renderHorizontalGridLines(true)
.x(d3.scaleLinear().domain([-25, 25]))
.filterPrinter(function (filters) {
var filter = filters[0], s = '';
s += numberFormat(filter[0]) + '% -> ' + numberFormat(filter[1]) + '%';
return s;
});
bar_chart_volume_month_chart.xAxis().tickFormat(
function (v) { return v + '%'; });
bar_chart_volume_month_chart.yAxis().ticks(5);
"""
row_chart_replaced = (str(fluctuation_chart).replace("\n", "").replace(
" ", "").replace("\t", ""))
dc_documentation_string_replaced = (str(dc_documentation_string).replace(
"\n", "").replace(" ", "").replace("\t", ""))
assert row_chart_replaced == dc_documentation_string_replaced
def test_volume_chart():
monthDim = Dimension('month',
group="volume",
group_type='sum',
modifier='/500000')
stacked_area_range = BarChart(
"stacked_area_range",
monthDim,
width=990,
height=40,
elasticY=True,
alwaysUseRounding=True,
round='d3.timeMonth.round',
gap=1,
centerBar=True,
xUnits='d3.timeMonths',
margins=Margin(0, 50, 20, 40),
renderHorizontalGridLines=False,
x='d3.scaleTime().domain([new Date(1985, 0, 1), new Date(2012, 11, 31)])'
)
expected = '''var bar_chart_stacked_area_range = dc.barChart("#stacked_area_range")
.width(990)
.height(40)
.margins({top: 0, right: 50, bottom: 20, left: 40})
.dimension(month_dimension)
.group(month_group)
.elasticY(true)
.centerBar(true)
.gap(1)
.round(d3.timeMonth.round)
.xUnits(d3.timeMonths)
.alwaysUseRounding(true)
.x(d3.scaleTime().domain([new Date(1985, 0, 1), new Date(2012, 11, 31)]));
'''
assert str(stacked_area_range).replace("\n", "").replace(" ", "").replace(
"\t", "") == str(expected).replace("\n",
"").replace(" ",
"").replace("\t", "")
def bar_chart(ndx):
dat = ndx
dat["fluctuation"] = np.round((dat.close - dat.open) / dat.open * 100)
fluctuation_dim = Dimension("fluctuation")
fluctuation_chart = BarChart(
"volume-month-chart",
fluctuation_dim,
width=420,
height=180,
elasticY=True,
gap=1,
centerBar=True,
alwaysUseRounding=True,
xAxis="tickFormat(function(v){return v+'%';})",
yAxis="ticks(5)",
)
return fluctuation_chart
from pydashboard import components as s
from pydashboard.example_data.example_data import dat
from pydashboard.components import Dimension, MultiDimension
from pydashboard.dc_components import PieChart, RowChart, ScatterPlot
from pydashboard.dominate_template import dashboard2 as t
dim_address = Dimension("address")
dim_Pstatus = Dimension("Pstatus")
dim_famsize = Dimension("famsize")
dim_romantic = Dimension("romantic")
dim_studytime = Dimension("studytime")
dim_age_absences = MultiDimension("age", "absences")
# pie_chart = PieChart("A", dim_address, radius=200, height=500, width=500)
pie_chart2 = PieChart("B", dim_Pstatus, radius=100, slicesCap=2)
pie_chart3 = PieChart("C", dim_famsize, radius=100, inner_radius=20)
pie_chart4 = PieChart("D", dim_romantic)
pie_chart5 = RowChart(
"E", dim_studytime, elasticX=True, xAxis="tickValues([0, 20, 200])"
)
pie_chart6 = PieChart("F", dim_romantic)
pie_chart7 = PieChart("G", dim_romantic)
pie_chart8 = PieChart("H", dim_romantic)
pie_chart9 = PieChart("I", dim_romantic)
scatter_plot = ScatterPlot("A", dim_age_absences)
dashboard = s.Dashboard(
scatter_plot,
dat.head()
dat["fluctuation"] = np.round((dat.close - dat.open) / dat.open * 100)
def get_year(x):
return x.split("/")[2]
dat["gain"] = dat.change.apply(gainOrLoss)
dat["year"] = dat.date.apply(get_year)
dat["quarter"] = dat.date.apply(get_quarter)
dat["day_of_week"] = dat.date.apply(day_of_week)
gain_dim = Dimension("gain")
fluctuation_dim = Dimension("fluctuation")
day_of_week_dim = Dimension("day_of_week")
quarter_dim = Dimension("quarter", group="volume", group_type="sum")
gain_loss_chart = PieChart(
"gain_loss_chart",
gain_dim,
radius=80,
width=180,
height=180,
label=Label("percent", precision=0),
)
quarter_chart = PieChart("quarters",
quarter_dim,