Your First Chart in Django using FusionCharts
FusionCharts Suite XT includes the FusionCharts Django wrapper that lets you create interactive, data-driven charts. You can create a simple chart using the FusionCharts server-side Django wrapper without writing any JavaScript code.
The server-side Django wrapper generates the required JavaScript and HTML code as a string, which is then used to render charts on a browser page. We'll start with simple examples of creating a chart , then a gauge and a map .
Before going through this article, please install FusionCharts Django wrapper, if you haven’t installed it already.
Create your first chart
In this section, we will create a chart using FusionCharts Django server-side wrapper. We will create a Column 2D chart, which has the column2d chart alias in FusionCharts. We have 95+ chart types with their respective aliases for you to explore. Find the complete list of chart types here .
For this example, we have created a view named views.py. To keep things simple, we have placed all the chart rendering logics in the views.py view.
The example view we created is
app_name/views.py.
Let's start with a simple example of "Countries With Most Oil Reserves" chart, which we will plot in a Column 2D chart as shown below:
The data for this chart is represented in the table below:
| Country | No. of Oil Reserves | |
|---|---|---|
| Venezuela | 290 | |
| Saudi | 260 | |
| Canada | 180 | |
| Iran | 140 | |
| Russia | 115 | |
| UAE | 100 | |
| US | 30 | |
| China | 30 |
Convert tabular data into JSON/XML format
Now that you have the tabular data ready, it's time to convert it into JSON/XML format, as FusionCharts accepts data in JSON or XML format. The converted format is shown below:
There are different JSON/XML formats for different groups of charts in FusionCharts - e.g., single-series (which you see here), multi-series , combination , etc.
{
"chart": {
"caption": "Countries With Most Oil Reserves [2017-18]",
"subCaption": "In MMbbl = One Million barrels",
"xAxisName": "Country",
"yAxisName": "Reserves (MMbbl)",
"numberSuffix": "K",
"theme": "fusion"
},
"data": [
{
"label": "Venezuela",
"value": "290"
},
{
"label": "Saudi",
"value": "260"
},
{
"label": "Canada",
"value": "180"
},
{
"label": "Iran",
"value": "140"
},
{
"label": "Russia",
"value": "115"
},
{
"label": "UAE",
"value": "100"
},
{
"label": "US",
"value": "30"
},
{
"label": "China",
"value": "30"
}
]
}In the above code we have:
- Created the chart object to define the elements of the
chart. - Then, each row of the tabular data is present within the
dataarray to specify the labels and their corresponding values.
Both the chart object and the data array contain a set of key-value pairs known as attributes. These attributes are used to set the functional and cosmetic properties of the chart as defined below:
Functional Attributes
Functional attributes let you control a variety of functional elements on the chart. For example, you can opt to show/hide data labels or, data values. You can also set chart limits and extended properties. The functional attributes used in the above code are:
captionsets the caption of the chart.subcaptionsets the sub-caption of the chart.xAxisNamesets the name of the x-axis, whereasyAxisNamesets the name of the y-axis.numberPrefixadds a prefix to all the numbers visible on the chart.- Please note, we have used the
themeattribute in the chart's data and providedfusiontheme as its value. Using themes, you can centralize cosmetic and functional properties across various charts in your web application.
Cosmetic Attributes
Cosmetic attributes let you configure chart cosmetics like color, transparency, font size, etc. Since we are using the fusion theme to customize the chart's look and feel, no cosmetic attributes are used in this sample. For the detailed list of attributes, click here .
Create an instance for the chart
In this step, we will create an object for the chart type as column2d using FusionCharts class constructor, set the width and height (in pixels or %), and finally specify the data for the chart as a string.
The code to create an object of the chart is given below:
# dataSource = “JSON data of the chart”
column2D = FusionCharts("column2d", "myFirstChart" , "600", "400", "myFirstchart-container", "json", dataSource)In the above code:
- We have created an instance of the Column 2D chart. Each chart type in FusionCharts Suite XT has a unique alias, which you can use to create an instance of that chart. In this case, we are creating an instance of a Column 2D chart with dimensions of 600x400 pixels using
widthandheight. - To specify the data format as JSON, we have set the
dataFormatparameter to json. You can also provide the data in XML format. - The JSON data is embedded as the value of the
dataSourceparameter.
The full code for the above sample is:
from django.shortcuts import render
from django.http import HttpResponse
from collections import OrderedDict
# Include the `fusioncharts.py` file that contains functions to embed the charts.
from fusioncharts import FusionCharts
def myFirstChart(request):
#Chart data is passed to the `dataSource` parameter, as dictionary in the form of key - value pairs.
dataSource = OrderedDict()
# The `chartConfig` dict contains key - value pairs data for chart attribute
chartConfig = OrderedDict()
chartConfig["caption"] = "Countries With Most Oil Reserves [2017-18]"
chartConfig["subCaption"] = "In MMbbl = One Million barrels"
chartConfig["xAxisName"] = "Country"
chartConfig["yAxisName"] = "Reserves (MMbbl)"
chartConfig["numberSuffix"] = "K"
chartConfig["theme"] = "fusion"
# The `chartData` dict contains key - value pairs data
chartData = OrderedDict()
chartData["Venezuela"] = 290
chartData["Saudi"] = 260
chartData["Canada"] = 180
chartData["Iran"] = 140
chartData["Russia"] = 115
chartData["UAE"] = 100
chartData["US"] = 30
chartData["China"] = 30
dataSource["chart"] = chartConfig
dataSource["data"] = []
# Convert the data in the `chartData`array into a format that can be consumed by FusionCharts.
#The data for the chart should be in an array wherein each element of the array
#is a JSON object# having the `label` and `value` as keys.
#Iterate through the data in `chartData` and insert in to the `dataSource['data']` list.
for key, value in chartData.items():
data = {}
data["label"] = key
data["value"] = value
dataSource["data"].append(data)
# Create an object for the column 2D chart using the FusionCharts class constructor
# The chart data is passed to the `dataSource` parameter.
column2D = FusionCharts("column2d", "myFirstChart", "600", "400", "myFirstchart-container", "json", dataSource)
return render(request, 'index.html', {
'output': column2D.render()
})
The HTML template of the above sample is shown below:
<!-- Filename: app_name/templates/index.html -->
<!DOCTYPE html>
<html>
<head>
<title>FC-python wrapper</title>
{% load static %}
<script type="text/javascript" src="{% static "path/to/local/fusioncharts.js" %}"></script>
<script type="text/javascript" src="{% static "path/to/local/themes/fusioncharts.theme.fusion.js" %}"></script>
</head>
<body>
<div id="myFirstchart-container">{{ output|safe }}</div>
</body>
</html>That's it! When you run this HTML page now, you should see a chart representing your data.
See the complete list of all possible attributes (the keys in the dataSource object) for a Column 2D chart.
Now, go on and explore other 95+ chart types that we have in FusionCharts or explore the configuration attributes for the charts.
The FusionCharts Chart Class
The syntax of the Chart class constructor used to initialize the chart object is:
Chart <object name> = new Chart (chartType, chartId, chartWidth, chartHeight, dataFormat, dataSource, bgColor, bgOpacity)A list of available constructor parameters are given in the table below:
| Parameter | Type | Description |
|---|---|---|
chartType
|
String | It is used to specify the type of chart to be rendered. |
chartId |
String | It is used to specify a unique identifier for the chart. If multiple charts are rendered on the same HTML page, each chart is referred to using its unique ID. |
chartWidth |
String | It is used to specify the width of the chart, in pixels. |
chartHeight |
String | It is used to specify the height of the chart, in pixels. |
dataFormat |
String | It is used to specify the type of data that will be passed to the chart. This attribute takes the following values: json, xml, jsonurl, xmlurl. |
dataSource |
String | It specifies the source from where the data will be fetched, depending on the value passed to the dataFormat attribute. |
bgColor |
String | It is used to specify the hex code for the background color of the chart. |
bgOpacity |
String | It is used to specify the background opacity for the chart. This attribute takes values between 0 (transparent) and 100 (opaque). |
It is not necessary to assign values for all parameters during initialization. However, keep in mind the following:
- The order of parameters needs to be preserved.
- Make sure that all of these parameters have been assigned values using the constructor, the
Chartclass methods, or theRender()method before running the application. - If not, either the chart will not render at all or it will not render the way you want it to.
Create your first gauge
Gauges are powerful tools that can showcase information using a radial scale to display data and a dial to indicate the value. In this section, we will create an Angular Gauge.
For this example, we have created a view named views.py. To keep things simple, we have placed all the chart rendering logics in the views.py view only.
The example view we created is
app_name/views.py.
To start with, we'll build a simple gauge showcasing Nordstorm's Customer Satisfaction Score as shown below:
The thresholds for the above sample have been defined using the following range.
| Range | Color | Hex Code | |
|---|---|---|---|
| 0-50 | Red | #F2726F | |
| 50-75 | Yellow | #FFC533 | |
| 75-100 | Green | #62B58F |
So, any score less than 50 is bad and is red. Any score between 50 and 75 is average and is yellow. Any score above 75 means good and is green.
Convert tabular data into JSON/XML format
Now that you have the tabular data ready, it's time to convert it into JSON/XML format, as FusionCharts accepts data in JSON or XML format. The converted format is shown below:
{
"chart": {
"caption": "Nordstorm's Customer Satisfaction Score for 2017",
"lowerLimit": "0",
"upperLimit": "100",
"showValue": "1",
"numberSuffix": "%",
"theme": "fusion",
"showToolTip": "0"
},
"colorRange": {
"color": [
{
"minValue": "0",
"maxValue": "50",
"code": "#F2726F"
},
{
"minValue": "50",
"maxValue": "75",
"code": "#FFC533"
},
{
"minValue": "75",
"maxValue": "100",
"code": "#62B58F"
}
]
},
"dials": {
"dial": [
{
"value": "81"
}
]
}
}Create an instance for the gauge
In this step, we will create an object for the chart type as angularGauge using FusionCharts class constructor, set the width and height (in pixels or %), and finally specify the data for the chart as a string.
The code to create an instance of the gauge is given below:
# dataSource = “JSON data of the gauge”
angulargaugeWidget = FusionCharts("angulargauge", "myFirstWidget", "100%", "200", "myFirstwidget-container", "json", dataSource)The full code for the above sample is:
from django.shortcuts import render
from django.http import HttpResponse
from collections import OrderedDict
# Include the `fusioncharts.py` file that contains functions to embed the widget.
from fusioncharts import FusionCharts
def myFirstWidget(request):
#Load dial indicator values from simple string array# e.g.dialValues = ["52", "10", "81", "95"]
dialValues = ["81"]
# widget data is passed to the `dataSource` parameter, as dict, in the form of key - value pairs.
dataSource = OrderedDict()
# The `widgetConfig` dict contains key - value pairs data for widget attribute
widgetConfig = OrderedDict()
widgetConfig["caption"] = "Nordstorm's Customer Satisfaction Score for 2017"
widgetConfig["lowerLimit"] = "0"
widgetConfig["upperLimit"] = "100"
widgetConfig["showValue"] = "1"
widgetConfig["numberSuffix"] = "%"
widgetConfig["theme"] = "fusion"
widgetConfig["showToolTip"] = "0"
# The `colorData` dict contains key - value pairs data for ColorRange of dial
colorRangeData = OrderedDict()
colorRangeData["color"] = [{
"minValue": "0",
"maxValue": "50",
"code": "#F2726F"
},
{
"minValue": "50",
"maxValue": "75",
"code": "#FFC533"
},
{
"minValue": "75",
"maxValue": "100",
"code": "#62B58F"
}
]
# Convert the data in the `dialData` array into a format that can be consumed by FusionCharts.
dialData = OrderedDict()
dialData["dial"] = []
dataSource["chart"] = widgetConfig
dataSource["colorRange"] = colorRangeData
dataSource["dials"] = dialData
# Iterate through the data in `dialValues` and insert in to the `dialData["dial"]` list.
# The data for the `dial`should be in an array wherein each element of the
# array is a JSON object# having the `value` as keys.
for i in range(len(dialValues)):
dialData["dial"].append({
"value": dialValues[i]
})
# Create an object for the angular-gauge using the FusionCharts class constructor
# The widget data is passed to the `dataSource` parameter.
angulargaugeWidget = FusionCharts("angulargauge", "myFirstWidget", "100%", "200", "myFirstwidget-container", "json", dataSource)
# returning complete JavaScript and HTML code, which is used to generate widget in the browsers.
return render(request, 'index.html', {'output' : angulargaugeWidget.render()})
The HTML template of the above sample is shown below:
<!-- Filename: app_name/templates/index.html -->
<!DOCTYPE html>
<html>
<head>
<title>FC-python wrapper</title>
{% load static %}
<script type="text/javascript" src="{% static "path/to/local/fusioncharts.js" %}"></script>
<script type="text/javascript" src="{% static "path/to/local/themes/fusioncharts.theme.fusion.js" %}"></script>
</head>
<body>
<div id="myFirstwidget-container">{{ output|safe }}</div>
</body>
</html>See the complete list of all possible attributes for an angular gauge.
Create your first map
For this example, we have created a view named views.py. To keep things simple, we have placed all the chart rendering logics in the views.py view only.
In this section, we will create a visualization using the World Map. Take a look at the map shown below:
The data for this chart is represented in the table below:
| State | Entity Name | Value | |
|---|---|---|---|
| North America | NA | 82 | |
| South America | SA | 2.04 | |
| Asia | AS | 1.78 | |
| Europe | EU | 40 | |
| Africa | AF | 2.58 | |
| Australia | AU | 1.30 |
In the above table, the column Entity Name represents the geographical entities represented in the map, whose full names are given in the State column in this example.
However, when you convert the data in a format acceptable by FusionCharts, the entities are denoted by the id key in the data object (see the code snippet of the next section).
For any map visualization you create, it is imperative that you provide the correct value for the id keys. For example, if you want to denote Africa, the value for the corresponding id must be AF, and not AFR. We have detailed Map Specification Sheets for all the maps that can be rendered using FusionCharts. Refer to them for the correct id of the map you want to create.
Convert tabular data into JSON/XML format
Now that you have the tabular data ready, it's time to convert it into JSON/XML format, as FusionCharts accepts data in JSON or XML format. The converted format is shown below:
{
"chart": {
"caption": "Average Annual Population Growth",
"subcaption": " 1955-2015",
"numbersuffix": "%",
"includevalueinlabels": "1",
"labelsepchar": ": ",
"entityFillHoverColor": "#FFF9C4",
"theme": "fusion"
},
"colorrange": {
"minvalue": "0",
"code": "#FFE0B2",
"gradient": "1",
"color": [
{
"minvalue": "0.5",
"maxvalue": "1.0",
"color": "#FFD74D"
},
{
"minvalue": "1.0",
"maxvalue": "2.0",
"color": "#FB8C00"
},
{
"minvalue": "2.0",
"maxvalue": "3.0",
"color": "#E65100"
}
]
},
"data": [
{
"id": "NA",
"value": ".82",
"showLabel": "1"
},
{
"id": "SA",
"value": "2.04",
"showLabel": "1"
},
{
"id": "AS",
"value": "1.78",
"showLabel": "1"
},
{
"id": "EU",
"value": ".40",
"showLabel": "1"
},
{
"id": "AF",
"value": "2.58",
"showLabel": "1"
},
{
"id": "AU",
"value": "1.30",
"showLabel": "1"
}
]
}Create an instance for the map
In this step, we will create an object for the map type as world using FusionCharts class constructor, set the width and height (in pixels or %), and finally specify the data for the chart as a string.
The code to create an object of the gauge is given below:
# dataSource = “JSON data of the map”
fusionMap = FusionCharts("maps/world", "myFirstMap" , "650", "450", "myFirstmap-container", "json", dataSource)The full code for the above sample is:
from django.shortcuts import render
from django.http import HttpResponse
from collections import OrderedDict
# Include the `fusioncharts.py` file that contains functions to embed the maps.
from fusioncharts import FusionCharts
def myFirstMap(request):
# Chart data is passed to the `dataSource` parameter, as dict, in the form of key - value pairs.
dataSource = OrderedDict()
# The `mapConfig` dict contains key - value pairs data
for chart attribute
mapConfig = OrderedDict()
mapConfig["caption"] = "Average Annual Population Growth"
mapConfig["subcaption"] = "1955-2015"
mapConfig["numbersuffix"] = "%"
mapConfig["includevalueinlabels"] = "1"
mapConfig["labelsepchar"] = ":"
mapConfig["entityFillHoverColor"] = "#FFF9C4"
mapConfig["theme"] = "fusion"
# Map color range data
colorDataObj = {
"minvalue": "0",
"code": "#FFE0B2",
"gradient": "1",
"color": [{
"minValue": "0.5",
"maxValue": "1",
"code": "#FFD74D"
},
{
"minValue": "1.0",
"maxValue": "2.0",
"code": "#FB8C00"
},
{
"minValue": "2.0",
"maxValue": "3.0",
"code": "#E65100"
}
]
}
dataSource["chart"] = mapConfig
dataSource["colorrange"] = colorDataObj
dataSource["data"] = []
# Map data array
mapDataArray = [
["NA", "0.82", "1"],
["SA", "2.04", "1"],
["AS", "1.78", "1"],
["EU", "0.40", "1"],
["AF", "2.58", "1"],
["AU", "1.30", "1"]
]
# Iterate through the data in `mapDataArray` and insert in to the `dataSource["data"]` list.
#The data for the `data` should be in an array wherein each element
#of the array is a JSON object# having the `id`, `value` and `showlabel` as keys.
for i in range(len(mapDataArray)):
dataSource["data"].append({
"id": mapDataArray[i][0],
"value": mapDataArray[i][1],
"showLabel": mapDataArray[i][2]
})
# Create an object for the world map using the FusionCharts class constructor
# The chart data is passed to the `dataSource` parameter.
fusionMap = FusionCharts("maps/world", "myFirstMap", "650", "450", "myFirstmap-container", "json", dataSource)
# returning complete JavaScript and HTML code, which is used to generate map in the browsers.
return render(request, 'index.html', {
'output': fusionMap.render()
})The HTML template of the above sample is shown below:
<!-- Filename: app_name/templates/index.html -->
<!DOCTYPE html>
<html>
<head>
<title>FC-python wrapper</title>
{% load static %}
<script type="text/javascript" src="{% static "path/to/local/fusioncharts.js" %}"></script>
<script type="text/javascript" src="{% static "path/to/local/maps/fusioncharts.world.js" %}"></script>
<script type="text/javascript" src="{% static "path/to/local/themes/fusioncharts.theme.fusion.js" %}"></script>
</head>
<body>
<div id="myFirstmap-container">{{ output|safe }}</div>
</body>
</html>See the complete list of all possible attributes (the keys in the dataSource object) for the World Map. The respective ids, can be found here .
Problem rendering the chart?
In case there is an error, and you are unable to see the chart, check for the following:
If you don't see the chart getting rendered on the browser, it might be because some browsers does not allow JavaScript files to be loaded and run from the local filesystem. In such cases, either try a different browser, or create a local/remote server and provide the webpages containing the charts from the server.
If you are getting a JavaScript error on your page, check your browser console for the exact error and fix accordingly.
If the chart does not show up at all, but there are no JavaScript errors, check if the FusionCharts Suite XT JavaScript library has loaded correctly. You can use developer tools within your browser to see if
fusioncharts.jswas loaded. Check if the path tofusioncharts.jsfile is correct and whether the file exists in that location.If you get a Loading Data or Error in loading data message, check whether your JSON data structure is correct, or there are conflicts related to quotation marks in your code.