def makeTestingLine(df):
template = [{
"title": "Source of Covid-19 infections in Queensland",
"subtitle":
f"""Showing the daily count of new cases by the source of infection. {last_date}""",
"footnote": "",
"source":
"| Sources: Covidlive.com.au, Queensland Department of Health",
"dateFormat": "%Y-%m-%d",
"minY": "0",
"maxY": "",
"xAxisDateFormat": "%b %d",
"tooltip":
"<strong>{{#formatDate}}{{data.Date}}{{/formatDate}}</strong><br/>{{group}}: {{groupValue}}<br/>Total: {{total}}",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}]
key = []
periods = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
yachtCharter(template=template,
labels=labels,
data=chartData,
chartId=[{
"type": "stackedbar"
}],
chartName="qld_covid_infection_source")
def makeTestingLine(df):
template = [
{
"title": "Queensland Covid Hotspots",
"subtitle": f"""""",
"footnote": "",
"source": "| Sources: Queensland Department of Health",
"yScaleType":"",
"minY": "0",
"maxY": "",
"x_axis_cross_y":"",
"periodDateFormat":"",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}
]
key = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
yachtCharter(template=template, labels=labels, data=chartData, chartId=[{"type":"table"}],
options=[{"colorScheme":"guardian","format": "scrolling","enableSearch": "TRUE","enableSort": "TRUE"}], chartName="qld_covid_hotspots")
def makeDropChart(df):
template = [{
"title": "Government responses to the Covid pandemic",
"subtitle":
"From Global Recovery Observatory data, grouped by spending category and measured in billions of US dollars",
"footnote":
"""Global Recovery Observatory dataset was updated through 28/02/2021.
Guardian Australia has added recovery measures from the 2021 Australian and United Kingdom budgets, South Korea supplementary budget, and the American Recovery Plan. More about categorisation in the notes.""",
"source":
"Global Recovery Observatory, Oxford University Economic Recovery Project, Yonhap News Agency, Wall Street Journal, International Monetary Fund, government websites",
"dateFormat": "%Y-%m-%d",
"minY": "0",
"maxY": "",
"xAxisDateFormat": "%b %d",
# "tooltip":"<strong>{{#formatDate}}{{data.Date}}{{/formatDate}}</strong><br/>{{group}}: {{groupValue}}<br/>Total: {{total}}",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}]
key = []
periods = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
dropdown = [{
"data": "Infrastructure",
"display": "Infrastructure"
}, {
"data": "Liquidity support",
"display": "Liquidity support"
}, {
"data": "Tax measures",
"display": "Tax measures"
}, {
"data": "Transfers and job support",
"display": "Transfers and job support"
}]
options = [{"enableShowMore": 0}]
yachtCharter(template=template,
dropdown=dropdown,
options=options,
labels=labels,
data=chartData,
chartId=[{
"type": "horizontalbar"
}],
chartName="oz-covid-budget-comparison")
def makeDropChart(df):
template = [{
"title": "Government Covid spending as % of GDP",
"subtitle":
"Comparing the federal government's Covid economic support estimate with the COVID-19 Economic Stimulus Index",
"footnote": "",
"source":
"COVID-19 Economic Stimulus Index - Ceyhun Elgin, Gokce Basbug, Abdullah Yalaman; Australian federal government budget website",
"dateFormat": "%Y-%m-%d",
"minY": "0",
"maxY": "",
"xAxisDateFormat": "%b %d",
# "tooltip":"<strong>{{#formatDate}}{{data.Date}}{{/formatDate}}</strong><br/>{{group}}: {{groupValue}}<br/>Total: {{total}}",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}]
key = []
periods = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
# dropdown = [{
# "data":"Infrastructure",
# "display":"Infrastructure"
# },{
# "data":"Liquidity support",
# "display":"Liquidity support"
# },{
# "data":"Tax measures",
# "display":"Tax measures"
# },{
# "data":"Transfers and job support",
# "display":"Transfers and job support"
# }]
dropdown = []
options = [{"enableShowMore": 0}]
yachtCharter(template=template,
dropdown=dropdown,
options=options,
labels=labels,
data=chartData,
chartId=[{
"type": "horizontalbar"
}],
chartName="oz-covid-budget-gdp-comparison")
def makeTable(df):
template = [{
"title": "Major global infrastructure programs",
"subtitle":
f"50 of the largest infrastructure programs announced during the Covid-19 pandemic",
"footnote": "",
"source":
"Global Recovery Observatory, Oxford University Economic Recovery Project, all Street Journal, International Monetary Fund, government websites",
"yScaleType": "",
"minY": "0",
"maxY": "",
"x_axis_cross_y": "",
"periodDateFormat": "",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}]
key = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
yachtCharter(template=template,
dropdown=[],
labels=labels,
data=chartData,
chartId=[{
"type": "table"
}],
options=[{
"colorScheme": "guardian",
"format": "scrolling",
"enableSearch": "FALSE",
"enableSort": "FALSE",
"enableShowMore": 1
}],
chartName="big-infrastructure-programs")
def makeSince100Chart(df):
template = [{
"title": "Australia's state vaccine rollout",
"subtitle":
f"Showing the Covid-19 vaccine doses administered per hundred people. Doses administered by GPs and aged care included in Australia's total. Last updated {display_date}.",
"footnote": "",
"source": "Covidlive.com.au, Australian Bureau of Statistics",
"dateFormat": "",
"yScaleType": "",
"xAxisLabel": "Days since first vaccination",
"yAxisLabel": "Doses per hundred people",
"minY": "",
"maxY": "",
"periodDateFormat": "",
"margin-left": "50",
"margin-top": "15",
"margin-bottom": "20",
"margin-right": "20",
"breaks": "no"
}]
key = []
periods = []
labels = []
chartId = [{"type": "linechart"}]
df.fillna('', inplace=True)
df = df.reset_index()
chartData = df.to_dict('records')
# print(since100.head())
# print(chartData)
yachtCharter(template=template,
data=chartData,
chartId=[{
"type": "linechart"
}],
options=[{
"colorScheme": colours,
"lineLabelling": "FALSE"
}],
chartName="testo_testo")
def makeTestingLine(df):
template = [{
"title":
"Trend in local and overseas-related transmission of Covid-19 in QLD, last 60 days",
"subtitle":
f"""Showing the 7 day rolling average of locally and overseas-acquired cases, with those under investigation added to the local category. Last updated {last_date}""",
"footnote": "",
"source":
"| Sources: Covidlive.com.au, Queensland Department of Health",
"dateFormat": "%Y-%m-%d",
"yScaleType": "",
"minY": "0",
"maxY": "",
"x_axis_cross_y": "",
"periodDateFormat": "",
"margin-left": "50",
"margin-top": "30",
"margin-bottom": "20",
"margin-right": "10"
}]
key = []
periods = []
# labels = []
df.fillna("", inplace=True)
chartData = df.to_dict('records')
labels = []
yachtCharter(template=template,
labels=labels,
data=chartData,
chartId=[{
"type": "linechart"
}],
options=[{
"colorScheme": "guardian"
}],
chartName="qld_covid_locally_acquired_trend")