Chart
The Chart widget allows you to visualize your data using different types of customizable charts.
tip
MINEO uses the library Ant Design Charts to render the charts. You can check their example gallery to browse the APIs along with many chart examples.
info
MINEO implements some of the charts offered by Ant Design Charts. If you would like to see a new chart type, please send us a message through the feedback button on the app!
Basic usage
First, we need a dataframe to visualize. Create a Python block with the following code and execute it:
import pandas as pd
df = pd.DataFrame([
{'sector': 'A', 'value': 100},
{'sector': 'B', 'value': 200},
{'sector': 'C', 'value': 300},
])
Now, create a Chart widget and configure $df as the input variable, then select
Column as our chart type.
The next step is selecting the columns we want to use as axes.
In this case, we will use sector as our X axis and value as our Y axis.
Save and execute the widget, and it will render the configured chart.
Advanced usage
Some chart options will not be available in the vanilla configuration form, and you will need
the advanced settings to configure them. To use certain, more complex charts (like the Stock chart), you will need to
use these settings too.
The advanced configuration tab contains a code editor that uses JavaScript to create a configuration object.
Inside this object, you can write whatever properties you want to use from the chart API (Ant Design Charts).
All props you write will be passed to the chart component in the same way antd does with their config objects
in their examples.
In this case, let's render a Stock chart. First, we need to create a dataset. For this, we will use
the Yahoo Finance python package. We will use this package to extract
the last 12 months of data from the stock of Tesla.
# Install and import Yahoo Finance
!pip install -q yfinance==0.1.85
import yfinance as yf
# Extract the data
data = yf.Ticker('TSLA')
hist = data.history(period="12mo")
If we print hist, our output variable, we will see it contains multiple columns:
Date, Open, High, Low, Close, Volume, Dividends and Stock Splits.
For this example, we will use only the first six.
Now, we will set up the basic chart configuration: We select Stock as our chart type,
$hist as our input variable, and then Date and Close for our X and Y axes respectively.
This is as far as we can go with basic config, and executing now would result in a crashed widget.
By checking the Ant Design Charts: Candlestick examples, we can see that
the component expects an yField prop, listing all the columns that will be included in the Candlestick plot.
caution
Incorrect or incomplete chart configuration can result in a crashed widget.
In our advanced configuration tab, paste the following code:
const config = {
yField: ['Open', 'Close', 'High', 'Low'],
slider: {},
}
With this configuration, we are doing the following:
- Configure the yField property to render the columns (
Open,Close,High,Low). This variable will be used to draw the chart boxes and their values will be displayed in the tooltip. - Add the date slider (including it as an empty object enables the default slider) under the X Axis, which will allow us to filter our stock data through time.
Now, if you execute your widget, you will get a beautiful Stock/Candlestick chart!
API reference
Despite having the possibility to add advanced settings in our graphs, the widget configuration uses a large number of configuration parameters to improve the graphics without using no-code approach.
Basic
| Setting name | Type | Description | Default |
|---|---|---|---|
Chart type | selector | The type of chart to render. | Bar |
Input variable | string/dataframe_variable_name | string/query_variable_name | string/form_variable_name | The name of the variable to use as input. | df |
X axis | selector | The name of the column to use as X axis. | |
Y axis | selector | The name of the column to use as Y axis. | |
Group by field | selector | In grouped charts defines the field to group by. | |
Max number of rows | int | Max number of rows to show in graph. | 1000 |
Format
tip
To display a chart title above your plot, you can use the block title.
| Setting name | Type | Description | Default |
|---|---|---|---|
X axis position | top | bottom | left | right | The X axis position | bottom |
Y axis position | top | bottom | left | right | The Y axis position | left |
X axis label | string | The label to display on the X axis. | |
Y axis label | string | The label to display on the Y axis. | |
X axis label position | start | center | end | The X axis label position. | center |
Y axis label position | start | center | end | The Y axis label position. | center |
Legend position | top | top-left | top-right | left | left-top | left-bottom | right | right-top | right-bottom | bottom | bottom-left | bottom-right | The position of the legend. | bottom |
Show grid | boolean | Whether to show the grid. | true |
Themes
| Setting name | Type | Description | Default |
|---|---|---|---|
Color palette | paletteColorSelector | Default palettes to use in graphs. |
Basic colors
| Setting name | Type | Description | Default |
|---|---|---|---|
Background color | color | Graph background color. | white |
Secondary color | color | Only applied in graphs that defines secondary colors (like Area graph). | white |
X axis label color | color | X axis values and label (if is visible) color. | black |
Y axis label color | color | Y axis values and label (if is visible) color. | black |
Labels
| Setting name | Type | Description | Default |
|---|---|---|---|
Show labels | boolean | If selected, value labels will appear on graph. | false |
Labels size | int | Labels font size (if labels are visible). | |
Labels color | color | Labels color (if labels are visible). | black |
Tooltips
Guides
| Setting name | Type | Description | Default |
|---|---|---|---|
Show guides | boolean | If selected, guides will appear on graph. | false |
Guide line | int | Guide lines width (if guides are visible). | |
Guide line color | color | Guide line color (if guides are visible) | black |
Markers
| Setting name | Type | Description | Default |
|---|---|---|---|
Show markers | boolean | If selected, markers will appear on graph. | false |
Marker size | int | Markers size (if markers are visible). |
Slider
| Setting name | Type | Description | Default |
|---|---|---|---|
Show slider | boolean | If selected, sliders will appear on graph. | false |
Slider start | float | Value between 0 and 1 for slider start. | 0 |
Slider end | float | Value between 0 and 1 for slider end. | 1 |
Slider background color | color | Slide background color | grey |
Annotations
| Setting name | Type | Description | Default |
|---|---|---|---|
Type | selector | Type of the annotation to add | |
Position/Start/End | string/variable | Coordinate to generate the annotation. . | |
Text | string/variable | Label for the annotation |
Animations
| Setting name | Type | Description | Default |
|---|---|---|---|
Type | selector | Type of the animation to add | Default |
Duration | integer | Duration in milliseconds of the animation | 1000 |
Delay | integer | Delay (ms) to start the animation | 0 |
Advanced
| Setting name | Type | Description | Default |
|---|---|---|---|
Advanced config | string/javascript | JavaScript code containing the chart config object. See Ant Design Charts | const config = {} |
Chart types
Bar
Example data:
import pandas as pd
df_bars = pd.DataFrame([
{'sector': 'North', 'value': 100},
{'sector': 'South', 'value': 200},
{'sector': 'East', 'value': 300},
{'sector': 'West', 'value': 400},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_bars |
X axis | value |
Y axis | sector |
Column
Example data:
import pandas as pd
df_columns = pd.DataFrame([
{'sector': 'North', 'value': 100},
{'sector': 'South', 'value': 200},
{'sector': 'East', 'value': 300},
{'sector': 'West', 'value': 400},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_columns |
X axis | sector |
Y axis | value |
Stacked columns
| Setting name | Type | Description | Default |
|---|---|---|---|
Group by field | Column name | The field to use to group elements |
Example data:
import pandas as pd
df_stacked_columns = pd.DataFrame([
{'sector': 'North', 'value': 100, 'type': 'A'},
{'sector': 'South', 'value': 200, 'type': 'A'},
{'sector': 'East', 'value': 300, 'type': 'A'},
{'sector': 'West', 'value': 400, 'type': 'A'},
{'sector': 'North', 'value': 200, 'type': 'B'},
{'sector': 'South', 'value': 400, 'type': 'B'},
{'sector': 'East', 'value': 600, 'type': 'B'},
{'sector': 'West', 'value': 800, 'type': 'B'},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_stacked_columns |
X axis | sector |
Y axis | value |
Group by field | type |
Grouped columns
| Setting name | Type | Description | Default |
|---|---|---|---|
Group by field | string/column_name | The field to use to group elements |
Example data:
import pandas as pd
df_grouped_columns = pd.DataFrame([
{'sector': 'North', 'value': 100, 'type': 'A'},
{'sector': 'South', 'value': 200, 'type': 'A'},
{'sector': 'East', 'value': 300, 'type': 'A'},
{'sector': 'West', 'value': 400, 'type': 'A'},
{'sector': 'North', 'value': 200, 'type': 'B'},
{'sector': 'South', 'value': 400, 'type': 'B'},
{'sector': 'East', 'value': 600, 'type': 'B'},
{'sector': 'West', 'value': 800, 'type': 'B'},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_grouped_columns |
X axis | sector |
Y axis | value |
Group by field | type |
Histogram
| Setting name | Type | Description | Default |
|---|---|---|---|
Bin field | string/column_name | The field to use to group elements | |
Bin number | int | Number of bins to use in the histogram | 4 |
Example data:
import pandas as pd
df_histogram = pd.DataFrame(
[
{"value": 1.2},
{"value": 3.4},
{"value": 3.7},
{"value": 4.3},
{"value": 5.2},
{"value": 5.8},
{"value": 6.1},
{"value": 6.5},
{"value": 6.8},
{"value": 7.1},
{"value": 7.3},
{"value": 7.7},
{"value": 8.3},
{"value": 8.6},
{"value": 8.8},
{"value": 9.1},
{"value": 9.2},
{"value": 9.4},
{"value": 9.5},
{"value": 9.7},
{"value": 10.5},
{"value": 10.7},
{"value": 10.8},
{"value": 11},
{"value": 11},
{"value": 11.1},
{"value": 11.2},
{"value": 11.3},
{"value": 11.4},
{"value": 11.4},
{"value": 11.7},
{"value": 12},
{"value": 12.9},
{"value": 12.9},
{"value": 13.3},
{"value": 13.7},
{"value": 13.8},
{"value": 13.9},
{"value": 14},
{"value": 14.2},
{"value": 14.5},
{"value": 15},
{"value": 15.2},
{"value": 15.6},
{"value": 16},
{"value": 16.3},
{"value": 17.3},
{"value": 17.5},
{"value": 17.9},
{"value": 18},
{"value": 18},
{"value": 20.6},
{"value": 21},
{"value": 23.4},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_histogram |
Bin field | value |
Bin number | 8 |
Box
| Setting name | Type | Description | Default |
|---|---|---|---|
Group by field | string/column_name | The field to use to group elements | |
Low | string/column_name | The field to use for low values | |
Q1 | string/column_name | The field to use for Q1 values | |
Median | string/column_name | The field to use for median values | |
Q3 | string/column_name | The field to use for Q3 values | |
High | string/column_name | The field to use for high values |
Example data:
import pandas as pd
df_box = pd.DataFrame(
[
{
"x": "Oceania",
"low": 1,
"q1": 9,
"median": 16,
"q3": 22,
"high": 24,
},
{
"x": "East Europe",
"low": 1,
"q1": 5,
"median": 8,
"q3": 12,
"high": 16,
},
{
"x": "Australia",
"low": 1,
"q1": 8,
"median": 12,
"q3": 19,
"high": 26,
},
{
"x": "South America",
"low": 2,
"q1": 8,
"median": 12,
"q3": 21,
"high": 28,
},
{
"x": "North Africa",
"low": 1,
"q1": 8,
"median": 14,
"q3": 18,
"high": 24,
},
{
"x": "North America",
"low": 3,
"q1": 10,
"median": 17,
"q3": 28,
"high": 30,
},
{
"x": "West Europe",
"low": 1,
"q1": 7,
"median": 10,
"q3": 17,
"high": 22,
},
{
"x": "West Africa",
"low": 1,
"q1": 6,
"median": 8,
"q3": 13,
"high": 16,
},
]
)
Example configuration:
| Setting name | Value |
|---|---|
X axis | x |
Input variable | $df_box |
Low | low |
Q1 | q1 |
Median | median |
Q3 | q3 |
High | high |
Line
Example data:
import pandas as pd
df_lines = pd.DataFrame([
{'year': '1999', 'value': 100},
{'year': '2000', 'value': 200},
{'year': '2001', 'value': 300},
{'year': '2002', 'value': 400},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_lines |
X axis | year |
Y axis | value |
Area
Example data:
import pandas as pd
df_area = pd.DataFrame([
{'year': '1999', 'value': 100},
{'year': '2000', 'value': 200},
{'year': '2001', 'value': 300},
{'year': '2002', 'value': 400},
])
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_area |
X axis | year |
Y axis | value |
Pie
Example data:
import pandas as pd
df_pie = pd.DataFrame(
[
{"year": "1999", "value": 100},
{"year": "2000", "value": 200},
{"year": "2001", "value": 300},
{"year": "2002", "value": 400},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_pie |
X axis | sector |
Y axis | value |
Violin
Example data:
import pandas as pd
df_violin = pd.DataFrame(
[
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.5},
{"species": "I. setosa", "x": "SepalLength", "y": 5.1},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3},
{"species": "I. setosa", "x": "SepalLength", "y": 4.9},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.3},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.2},
{"species": "I. setosa", "x": "SepalLength", "y": 4.7},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.1},
{"species": "I. setosa", "x": "SepalLength", "y": 4.6},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.6},
{"species": "I. setosa", "x": "SepalLength", "y": 5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.7},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.9},
{"species": "I. setosa", "x": "SepalLength", "y": 5.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.3},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 4.6},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 2.9},
{"species": "I. setosa", "x": "SepalLength", "y": 4.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.1},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.1},
{"species": "I. setosa", "x": "SepalLength", "y": 4.9},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.7},
{"species": "I. setosa", "x": "SepalLength", "y": 5.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.6},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 4.8},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.1},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3},
{"species": "I. setosa", "x": "SepalLength", "y": 4.8},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.1},
{"species": "I. setosa", "x": "PetalLength", "y": 1.1},
{"species": "I. setosa", "x": "SepalWidth", "y": 3},
{"species": "I. setosa", "x": "SepalLength", "y": 4.3},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.2},
{"species": "I. setosa", "x": "SepalWidth", "y": 4},
{"species": "I. setosa", "x": "SepalLength", "y": 5.8},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 4.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5.7},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.3},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.9},
{"species": "I. setosa", "x": "SepalLength", "y": 5.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.3},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.5},
{"species": "I. setosa", "x": "SepalLength", "y": 5.1},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.3},
{"species": "I. setosa", "x": "PetalLength", "y": 1.7},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.8},
{"species": "I. setosa", "x": "SepalLength", "y": 5.7},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.3},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.8},
{"species": "I. setosa", "x": "SepalLength", "y": 5.1},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.7},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.7},
{"species": "I. setosa", "x": "SepalLength", "y": 5.1},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.6},
{"species": "I. setosa", "x": "SepalLength", "y": 4.6},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.5},
{"species": "I. setosa", "x": "PetalLength", "y": 1.7},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.3},
{"species": "I. setosa", "x": "SepalLength", "y": 5.1},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.9},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 4.8},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.6},
{"species": "I. setosa", "x": "SepalWidth", "y": 3},
{"species": "I. setosa", "x": "SepalLength", "y": 5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.6},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.5},
{"species": "I. setosa", "x": "SepalLength", "y": 5.2},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5.2},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.6},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.2},
{"species": "I. setosa", "x": "SepalLength", "y": 4.7},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.6},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.1},
{"species": "I. setosa", "x": "SepalLength", "y": 4.8},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.4},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.4},
{"species": "I. setosa", "x": "SepalLength", "y": 5.4},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.1},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 4.1},
{"species": "I. setosa", "x": "SepalLength", "y": 5.2},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.4},
{"species": "I. setosa", "x": "SepalWidth", "y": 4.2},
{"species": "I. setosa", "x": "SepalLength", "y": 5.5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.5},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.1},
{"species": "I. setosa", "x": "SepalLength", "y": 4.9},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
{"species": "I. setosa", "x": "PetalLength", "y": 1.2},
{"species": "I. setosa", "x": "SepalWidth", "y": 3.2},
{"species": "I. setosa", "x": "SepalLength", "y": 5},
{"species": "I. setosa", "x": "PetalWidth", "y": 0.2},
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{"species": "I. virginica", "x": "SepalLength", "y": 5.8},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.3},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.2},
{"species": "I. virginica", "x": "SepalLength", "y": 6.4},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 5.5},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.5},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.2},
{"species": "I. virginica", "x": "PetalLength", "y": 6.7},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.8},
{"species": "I. virginica", "x": "SepalLength", "y": 7.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 6.9},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.6},
{"species": "I. virginica", "x": "SepalLength", "y": 7.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.5},
{"species": "I. virginica", "x": "PetalLength", "y": 5},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.2},
{"species": "I. virginica", "x": "SepalLength", "y": 6},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.7},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.2},
{"species": "I. virginica", "x": "SepalLength", "y": 6.9},
{"species": "I. virginica", "x": "PetalWidth", "y": 2},
{"species": "I. virginica", "x": "PetalLength", "y": 4.9},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 5.6},
{"species": "I. virginica", "x": "PetalWidth", "y": 2},
{"species": "I. virginica", "x": "PetalLength", "y": 6.7},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 7.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 4.9},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.7},
{"species": "I. virginica", "x": "SepalLength", "y": 6.3},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.1},
{"species": "I. virginica", "x": "PetalLength", "y": 5.7},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 6},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.2},
{"species": "I. virginica", "x": "SepalLength", "y": 7.2},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 4.8},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 6.2},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 4.9},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.1},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.1},
{"species": "I. virginica", "x": "PetalLength", "y": 5.6},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 6.4},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.6},
{"species": "I. virginica", "x": "PetalLength", "y": 5.8},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 7.2},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.9},
{"species": "I. virginica", "x": "PetalLength", "y": 6.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 7.4},
{"species": "I. virginica", "x": "PetalWidth", "y": 2},
{"species": "I. virginica", "x": "PetalLength", "y": 6.4},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.8},
{"species": "I. virginica", "x": "SepalLength", "y": 7.9},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.2},
{"species": "I. virginica", "x": "PetalLength", "y": 5.6},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 6.4},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.5},
{"species": "I. virginica", "x": "PetalLength", "y": 5.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.8},
{"species": "I. virginica", "x": "SepalLength", "y": 6.3},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.4},
{"species": "I. virginica", "x": "PetalLength", "y": 5.6},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.6},
{"species": "I. virginica", "x": "SepalLength", "y": 6.1},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 6.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 7.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.4},
{"species": "I. virginica", "x": "PetalLength", "y": 5.6},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.4},
{"species": "I. virginica", "x": "SepalLength", "y": 6.3},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 5.5},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.1},
{"species": "I. virginica", "x": "SepalLength", "y": 6.4},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 4.8},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 6},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.1},
{"species": "I. virginica", "x": "PetalLength", "y": 5.4},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.1},
{"species": "I. virginica", "x": "SepalLength", "y": 6.9},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.4},
{"species": "I. virginica", "x": "PetalLength", "y": 5.6},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.1},
{"species": "I. virginica", "x": "SepalLength", "y": 6.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.1},
{"species": "I. virginica", "x": "SepalLength", "y": 6.9},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.9},
{"species": "I. virginica", "x": "PetalLength", "y": 5.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.7},
{"species": "I. virginica", "x": "SepalLength", "y": 5.8},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.9},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.2},
{"species": "I. virginica", "x": "SepalLength", "y": 6.8},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.5},
{"species": "I. virginica", "x": "PetalLength", "y": 5.7},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.2},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.7},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.9},
{"species": "I. virginica", "x": "PetalLength", "y": 5},
{"species": "I. virginica", "x": "SepalWidth", "y": 2.5},
{"species": "I. virginica", "x": "SepalLength", "y": 6.3},
{"species": "I. virginica", "x": "PetalWidth", "y": 2},
{"species": "I. virginica", "x": "PetalLength", "y": 5.2},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 6.5},
{"species": "I. virginica", "x": "PetalWidth", "y": 2.3},
{"species": "I. virginica", "x": "PetalLength", "y": 5.4},
{"species": "I. virginica", "x": "SepalWidth", "y": 3.4},
{"species": "I. virginica", "x": "SepalLength", "y": 6.2},
{"species": "I. virginica", "x": "PetalWidth", "y": 1.8},
{"species": "I. virginica", "x": "PetalLength", "y": 5.1},
{"species": "I. virginica", "x": "SepalWidth", "y": 3},
{"species": "I. virginica", "x": "SepalLength", "y": 5.9},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_violin |
X axis | x |
Y axis | y |
Waterfall
Example data:
import pandas as pd
df_waterfall = pd.DataFrame(
[
{"year": "1999", "value": 100},
{"year": "2000", "value": -150},
{"year": "2001", "value": 225},
{"year": "2002", "value": -75},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_waterfall |
X axis | year |
Y axis | value |
Scatter
| Setting name | Type | Description | Default |
|---|---|---|---|
Color field | string/column_name | Field to use to color different values. |
Example data:
import pandas as pd
df_scatter = pd.DataFrame(
[
{
"Title": "Guardians of the Galaxy",
"Genre": "Action",
"Revenue (Millions)": 333.13,
"Rating": 8.1,
},
{
"Title": "Prometheus",
"Genre": "Adventure",
"Revenue (Millions)": 126.46,
"Rating": 7,
},
{
"Title": "Split",
"Genre": "Horror",
"Revenue (Millions)": 138.12,
"Rating": 7.3,
},
{
"Title": "Sing",
"Genre": "Animation",
"Revenue (Millions)": 270.32,
"Rating": 7.2,
},
{
"Title": "Suicide Squad",
"Genre": "Action",
"Revenue (Millions)": 325.02,
"Rating": 6.2,
},
{
"Title": "The Great Wall",
"Genre": "Action",
"Revenue (Millions)": 45.13,
"Rating": 6.1,
},
{
"Title": "La La Land",
"Genre": "Comedy",
"Revenue (Millions)": 151.06,
"Rating": 8.3,
},
{
"Title": "Mindhorn",
"Genre": "Comedy",
"Revenue (Millions)": None,
"Rating": 6.4,
},
{
"Title": "The Lost City of Z",
"Genre": "Action",
"Revenue (Millions)": 8.01,
"Rating": 7.1,
},
{
"Title": "Passengers",
"Genre": "Adventure",
"Revenue (Millions)": 100.01,
"Rating": 7,
},
{
"Title": "Fantastic Beasts and Where to Find Them",
"Genre": "Adventure",
"Revenue (Millions)": 234.02,
"Rating": 7.5,
},
{
"Title": "Hidden Figures",
"Genre": "Other",
"Revenue (Millions)": 169.27,
"Rating": 7.8,
},
{
"Title": "Rogue One",
"Genre": "Action",
"Revenue (Millions)": 532.17,
"Rating": 7.9,
},
{
"Title": "Moana",
"Genre": "Animation",
"Revenue (Millions)": 248.75,
"Rating": 7.7,
},
{
"Title": "Colossal",
"Genre": "Action",
"Revenue (Millions)": 2.87,
"Rating": 6.4,
},
{
"Title": "The Secret Life of Pets",
"Genre": "Animation",
"Revenue (Millions)": 368.31,
"Rating": 6.6,
},
{
"Title": "Hacksaw Ridge",
"Genre": "Other",
"Revenue (Millions)": 67.12,
"Rating": 8.2,
},
{
"Title": "Jason Bourne",
"Genre": "Action",
"Revenue (Millions)": 162.16,
"Rating": 6.7,
},
{"Title": "Lion", "Genre": "Other", "Revenue (Millions)": 51.69, "Rating": 8.1},
{
"Title": "Gold",
"Genre": "Adventure",
"Revenue (Millions)": 7.22,
"Rating": 6.7,
},
{
"Title": "Hounds of Love",
"Genre": "Crime",
"Revenue (Millions)": None,
"Rating": 6.7,
},
{
"Title": "Trolls",
"Genre": "Animation",
"Revenue (Millions)": 153.69,
"Rating": 6.5,
},
{
"Title": "Independence Day: Resurgence",
"Genre": "Action",
"Revenue (Millions)": 103.14,
"Rating": 5.3,
},
{
"Title": "Paris pieds nus",
"Genre": "Comedy",
"Revenue (Millions)": None,
"Rating": 6.8,
},
{
"Title": "Bahubali: The Beginning",
"Genre": "Action",
"Revenue (Millions)": 6.5,
"Rating": 8.3,
},
{
"Title": "Dead Awake",
"Genre": "Horror",
"Revenue (Millions)": 0.01,
"Rating": 4.7,
},
{
"Title": "Bad Moms",
"Genre": "Comedy",
"Revenue (Millions)": 113.08,
"Rating": 6.2,
},
{
"Title": "Assassin's Creed",
"Genre": "Action",
"Revenue (Millions)": 54.65,
"Rating": 5.9,
},
{
"Title": "Why Him?",
"Genre": "Comedy",
"Revenue (Millions)": 60.31,
"Rating": 6.3,
},
{
"Title": "X-Men: Apocalypse",
"Genre": "Action",
"Revenue (Millions)": 155.33,
"Rating": 7.1,
},
{
"Title": "Deadpool",
"Genre": "Action",
"Revenue (Millions)": 363.02,
"Rating": 8,
},
{
"Title": "Resident Evil: The Final Chapter",
"Genre": "Action",
"Revenue (Millions)": 26.84,
"Rating": 5.6,
},
{
"Title": "Captain America: Civil War",
"Genre": "Action",
"Revenue (Millions)": 408.08,
"Rating": 7.9,
},
{
"Title": "Interstellar",
"Genre": "Adventure",
"Revenue (Millions)": 187.99,
"Rating": 8.6,
},
{
"Title": "Doctor Strange",
"Genre": "Action",
"Revenue (Millions)": 232.6,
"Rating": 7.6,
},
{
"Title": "The Magnificent Seven",
"Genre": "Action",
"Revenue (Millions)": 93.38,
"Rating": 6.9,
},
{
"Title": "5- 25- 77",
"Genre": "Comedy",
"Revenue (Millions)": None,
"Rating": 7.1,
},
{
"Title": "Sausage Party",
"Genre": "Animation",
"Revenue (Millions)": 97.66,
"Rating": 6.3,
},
{
"Title": "Moonlight",
"Genre": "Other",
"Revenue (Millions)": 27.85,
"Rating": 7.5,
},
{
"Title": "Don't Fuck in the Woods",
"Genre": "Horror",
"Revenue (Millions)": None,
"Rating": 2.7,
},
{
"Title": "The Founder",
"Genre": "Other",
"Revenue (Millions)": 12.79,
"Rating": 7.2,
},
{
"Title": "Lowriders",
"Genre": "Other",
"Revenue (Millions)": 4.21,
"Rating": 6.3,
},
{
"Title": "Pirates of the Caribbean: On Stranger Tides",
"Genre": "Action",
"Revenue (Millions)": 241.06,
"Rating": 6.7,
},
{
"Title": "Miss Sloane",
"Genre": "Other",
"Revenue (Millions)": 3.44,
"Rating": 7.3,
},
{
"Title": "Fallen",
"Genre": "Adventure",
"Revenue (Millions)": None,
"Rating": 5.6,
},
{
"Title": "Star Trek Beyond",
"Genre": "Action",
"Revenue (Millions)": 158.8,
"Rating": 7.1,
},
{
"Title": "The Last Face",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 3.7,
},
{
"Title": "Star Wars: Episode VII - The Force Awakens",
"Genre": "Action",
"Revenue (Millions)": 936.63,
"Rating": 8.1,
},
{
"Title": "Underworld: Blood Wars",
"Genre": "Action",
"Revenue (Millions)": 30.35,
"Rating": 5.8,
},
{
"Title": "Mother's Day",
"Genre": "Comedy",
"Revenue (Millions)": 32.46,
"Rating": 5.6,
},
{
"Title": "John Wick",
"Genre": "Action",
"Revenue (Millions)": 43,
"Rating": 7.2,
},
{
"Title": "The Dark Knight",
"Genre": "Action",
"Revenue (Millions)": 533.32,
"Rating": 9,
},
{
"Title": "Silence",
"Genre": "Adventure",
"Revenue (Millions)": 7.08,
"Rating": 7.3,
},
{
"Title": "Don't Breathe",
"Genre": "Crime",
"Revenue (Millions)": 89.21,
"Rating": 7.2,
},
{
"Title": "Me Before You",
"Genre": "Other",
"Revenue (Millions)": 56.23,
"Rating": 7.4,
},
{
"Title": "Their Finest",
"Genre": "Comedy",
"Revenue (Millions)": 3.18,
"Rating": 7,
},
{
"Title": "Sully",
"Genre": "Other",
"Revenue (Millions)": 125.07,
"Rating": 7.5,
},
{
"Title": "Batman v Superman: Dawn of Justice",
"Genre": "Action",
"Revenue (Millions)": 330.25,
"Rating": 6.7,
},
{
"Title": "The Autopsy of Jane Doe",
"Genre": "Horror",
"Revenue (Millions)": None,
"Rating": 6.8,
},
{
"Title": "The Girl on the Train",
"Genre": "Crime",
"Revenue (Millions)": 75.31,
"Rating": 6.5,
},
{
"Title": "Fifty Shades of Grey",
"Genre": "Other",
"Revenue (Millions)": 166.15,
"Rating": 4.1,
},
{
"Title": "The Prestige",
"Genre": "Other",
"Revenue (Millions)": 53.08,
"Rating": 8.5,
},
{
"Title": "Kingsman: The Secret Service",
"Genre": "Action",
"Revenue (Millions)": 128.25,
"Rating": 7.7,
},
{
"Title": "Patriots Day",
"Genre": "Other",
"Revenue (Millions)": 31.86,
"Rating": 7.4,
},
{
"Title": "Mad Max: Fury Road",
"Genre": "Action",
"Revenue (Millions)": 153.63,
"Rating": 8.1,
},
{
"Title": "Wakefield",
"Genre": "Other",
"Revenue (Millions)": 0.01,
"Rating": 7.5,
},
{
"Title": "Deepwater Horizon",
"Genre": "Action",
"Revenue (Millions)": 61.28,
"Rating": 7.2,
},
{
"Title": "The Promise",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 5.9,
},
{
"Title": "Allied",
"Genre": "Action",
"Revenue (Millions)": 40.07,
"Rating": 7.1,
},
{
"Title": "A Monster Calls",
"Genre": "Other",
"Revenue (Millions)": 3.73,
"Rating": 7.5,
},
{
"Title": "Collateral Beauty",
"Genre": "Other",
"Revenue (Millions)": 30.98,
"Rating": 6.8,
},
{
"Title": "Zootopia",
"Genre": "Animation",
"Revenue (Millions)": 341.26,
"Rating": 8.1,
},
{
"Title": "Pirates of the Caribbean: At World's End",
"Genre": "Action",
"Revenue (Millions)": 309.4,
"Rating": 7.1,
},
{
"Title": "The Avengers",
"Genre": "Action",
"Revenue (Millions)": 623.28,
"Rating": 8.1,
},
{
"Title": "Inglourious Basterds",
"Genre": "Adventure",
"Revenue (Millions)": 120.52,
"Rating": 8.3,
},
{
"Title": "Pirates of the Caribbean: Dead Man's Chest",
"Genre": "Action",
"Revenue (Millions)": 423.03,
"Rating": 7.3,
},
{
"Title": "Ghostbusters",
"Genre": "Action",
"Revenue (Millions)": 128.34,
"Rating": 5.3,
},
{
"Title": "Inception",
"Genre": "Action",
"Revenue (Millions)": 292.57,
"Rating": 8.8,
},
{
"Title": "Captain Fantastic",
"Genre": "Comedy",
"Revenue (Millions)": 5.88,
"Rating": 7.9,
},
{
"Title": "The Wolf of Wall Street",
"Genre": "Other",
"Revenue (Millions)": 116.87,
"Rating": 8.2,
},
{
"Title": "Gone Girl",
"Genre": "Crime",
"Revenue (Millions)": 167.74,
"Rating": 8.1,
},
{
"Title": "Furious Seven",
"Genre": "Action",
"Revenue (Millions)": 350.03,
"Rating": 7.2,
},
{
"Title": "Jurassic World",
"Genre": "Action",
"Revenue (Millions)": 652.18,
"Rating": 7,
},
{
"Title": "Live by Night",
"Genre": "Crime",
"Revenue (Millions)": 10.38,
"Rating": 6.4,
},
{
"Title": "Avatar",
"Genre": "Action",
"Revenue (Millions)": 760.51,
"Rating": 7.8,
},
{
"Title": "The Hateful Eight",
"Genre": "Crime",
"Revenue (Millions)": 54.12,
"Rating": 7.8,
},
{
"Title": "The Accountant",
"Genre": "Action",
"Revenue (Millions)": 86.2,
"Rating": 7.4,
},
{
"Title": "Prisoners",
"Genre": "Crime",
"Revenue (Millions)": 60.96,
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"Genre": "Action",
"Revenue (Millions)": 227.14,
"Rating": 8.1,
},
{
"Title": "Srpski film",
"Genre": "Horror",
"Revenue (Millions)": None,
"Rating": 5.2,
},
{
"Title": "The Purge: Election Year",
"Genre": "Action",
"Revenue (Millions)": 79,
"Rating": 6,
},
{
"Title": "3 Idiots",
"Genre": "Comedy",
"Revenue (Millions)": 6.52,
"Rating": 8.4,
},
{
"Title": "Zoolander 2",
"Genre": "Comedy",
"Revenue (Millions)": 28.84,
"Rating": 4.7,
},
{
"Title": "World War Z",
"Genre": "Action",
"Revenue (Millions)": 202.35,
"Rating": 7,
},
{
"Title": "Mission: Impossible - Ghost Protocol",
"Genre": "Action",
"Revenue (Millions)": 209.36,
"Rating": 7.4,
},
{
"Title": "Let Me Make You a Martyr",
"Genre": "Action",
"Revenue (Millions)": None,
"Rating": 6.4,
},
{
"Title": "Filth",
"Genre": "Comedy",
"Revenue (Millions)": 0.03,
"Rating": 7.1,
},
{
"Title": "The Longest Ride",
"Genre": "Other",
"Revenue (Millions)": 37.43,
"Rating": 7.1,
},
{
"Title": "The imposible",
"Genre": "Other",
"Revenue (Millions)": 19,
"Rating": 7.6,
},
{
"Title": "Kick-Ass 2",
"Genre": "Action",
"Revenue (Millions)": 28.75,
"Rating": 6.6,
},
{
"Title": "Folk Hero & Funny Guy",
"Genre": "Comedy",
"Revenue (Millions)": None,
"Rating": 5.6,
},
{
"Title": "Oz the Great and Powerful",
"Genre": "Adventure",
"Revenue (Millions)": 234.9,
"Rating": 6.3,
},
{
"Title": "Brooklyn",
"Genre": "Other",
"Revenue (Millions)": 38.32,
"Rating": 7.5,
},
{
"Title": "Coraline",
"Genre": "Animation",
"Revenue (Millions)": 75.28,
"Rating": 7.7,
},
{
"Title": "Blue Valentine",
"Genre": "Other",
"Revenue (Millions)": 9.7,
"Rating": 7.4,
},
{
"Title": "The Thinning",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 6,
},
{
"Title": "Silent Hill",
"Genre": "Adventure",
"Revenue (Millions)": 46.98,
"Rating": 6.6,
},
{
"Title": "Dredd",
"Genre": "Action",
"Revenue (Millions)": 13.4,
"Rating": 7.1,
},
{
"Title": "Hunt for the Wilderpeople",
"Genre": "Adventure",
"Revenue (Millions)": 5.2,
"Rating": 7.9,
},
{
"Title": "Big Hero 6",
"Genre": "Animation",
"Revenue (Millions)": 222.49,
"Rating": 7.8,
},
{
"Title": "Carrie",
"Genre": "Other",
"Revenue (Millions)": 35.27,
"Rating": 5.9,
},
{
"Title": "Iron Man 2",
"Genre": "Action",
"Revenue (Millions)": 312.06,
"Rating": 7,
},
{
"Title": "Demolition",
"Genre": "Comedy",
"Revenue (Millions)": 1.82,
"Rating": 7,
},
{
"Title": "Pandorum",
"Genre": "Action",
"Revenue (Millions)": 10.33,
"Rating": 6.8,
},
{
"Title": "Olympus Has Fallen",
"Genre": "Action",
"Revenue (Millions)": 98.9,
"Rating": 6.5,
},
{
"Title": "I Am Number Four",
"Genre": "Action",
"Revenue (Millions)": 55.09,
"Rating": 6.1,
},
{
"Title": "Jagten",
"Genre": "Other",
"Revenue (Millions)": 0.61,
"Rating": 8.3,
},
{
"Title": "The Proposal",
"Genre": "Comedy",
"Revenue (Millions)": 163.95,
"Rating": 6.7,
},
{
"Title": "Get Hard",
"Genre": "Comedy",
"Revenue (Millions)": 90.35,
"Rating": 6,
},
{
"Title": "Just Go with It",
"Genre": "Comedy",
"Revenue (Millions)": 103.03,
"Rating": 6.4,
},
{
"Title": "Revolutionary Road",
"Genre": "Other",
"Revenue (Millions)": 22.88,
"Rating": 7.3,
},
{
"Title": "The Town",
"Genre": "Crime",
"Revenue (Millions)": 92.17,
"Rating": 7.6,
},
{
"Title": "The Boy",
"Genre": "Horror",
"Revenue (Millions)": 35.79,
"Rating": 6,
},
{
"Title": "Denial",
"Genre": "Other",
"Revenue (Millions)": 4.07,
"Rating": 6.6,
},
{
"Title": "Predestination",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 7.5,
},
{
"Title": "Goosebumps",
"Genre": "Adventure",
"Revenue (Millions)": 80.02,
"Rating": 6.3,
},
{
"Title": "Sherlock Holmes: A Game of Shadows",
"Genre": "Action",
"Revenue (Millions)": 186.83,
"Rating": 7.5,
},
{
"Title": "Salt",
"Genre": "Action",
"Revenue (Millions)": 118.31,
"Rating": 6.4,
},
{"Title": "Enemy", "Genre": "Other", "Revenue (Millions)": 1.01, "Rating": 6.9},
{
"Title": "District 9",
"Genre": "Action",
"Revenue (Millions)": 115.65,
"Rating": 8,
},
{
"Title": "The Other Guys",
"Genre": "Action",
"Revenue (Millions)": 119.22,
"Rating": 6.7,
},
{
"Title": "American Gangster",
"Genre": "Other",
"Revenue (Millions)": 130.13,
"Rating": 7.8,
},
{
"Title": "Marie Antoinette",
"Genre": "Other",
"Revenue (Millions)": 15.96,
"Rating": 6.4,
},
{"Title": 2012, "Genre": "Action", "Revenue (Millions)": 166.11, "Rating": 5.8},
{
"Title": "Harry Potter and the Half-Blood Prince",
"Genre": "Adventure",
"Revenue (Millions)": 301.96,
"Rating": 7.5,
},
{
"Title": "Argo",
"Genre": "Other",
"Revenue (Millions)": 136.02,
"Rating": 7.7,
},
{
"Title": "Eddie the Eagle",
"Genre": "Other",
"Revenue (Millions)": 15.79,
"Rating": 7.4,
},
{
"Title": "The Lives of Others",
"Genre": "Other",
"Revenue (Millions)": 11.28,
"Rating": 8.5,
},
{"Title": "Pet", "Genre": "Horror", "Revenue (Millions)": None, "Rating": 5.7},
{
"Title": "Paint It Black",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 8.3,
},
{
"Title": "Macbeth",
"Genre": "Other",
"Revenue (Millions)": None,
"Rating": 6.7,
},
{
"Title": "Forgetting Sarah Marshall",
"Genre": "Comedy",
"Revenue (Millions)": 62.88,
"Rating": 7.2,
},
{
"Title": "The Giver",
"Genre": "Other",
"Revenue (Millions)": 45.09,
"Rating": 6.5,
},
{
"Title": "Triple 9",
"Genre": "Action",
"Revenue (Millions)": 12.63,
"Rating": 6.3,
},
{
"Title": "Perfetti sconosciuti",
"Genre": "Comedy",
"Revenue (Millions)": None,
"Rating": 7.7,
},
{
"Title": "Angry Birds",
"Genre": "Animation",
"Revenue (Millions)": 107.51,
"Rating": 6.3,
},
{
"Title": "Moonrise Kingdom",
"Genre": "Adventure",
"Revenue (Millions)": 45.51,
"Rating": 7.8,
},
{
"Title": "Hairspray",
"Genre": "Comedy",
"Revenue (Millions)": 118.82,
"Rating": 6.7,
},
{
"Title": "Safe Haven",
"Genre": "Other",
"Revenue (Millions)": 71.35,
"Rating": 6.7,
},
{
"Title": "Focus",
"Genre": "Comedy",
"Revenue (Millions)": 53.85,
"Rating": 6.6,
},
{
"Title": "Ratatouille",
"Genre": "Animation",
"Revenue (Millions)": 206.44,
"Rating": 8,
},
{
"Title": "Stake Land",
"Genre": "Other",
"Revenue (Millions)": 0.02,
"Rating": 6.5,
},
{
"Title": "The Book of Eli",
"Genre": "Action",
"Revenue (Millions)": 94.82,
"Rating": 6.9,
},
{
"Title": "Cloverfield",
"Genre": "Action",
"Revenue (Millions)": 80.03,
"Rating": 7,
},
{
"Title": "Point Break",
"Genre": "Action",
"Revenue (Millions)": 28.77,
"Rating": 5.3,
},
{
"Title": "Under the Skin",
"Genre": "Other",
"Revenue (Millions)": 2.61,
"Rating": 6.3,
},
{
"Title": "I Am Legend",
"Genre": "Other",
"Revenue (Millions)": 256.39,
"Rating": 7.2,
},
{
"Title": "Men in Black 3",
"Genre": "Action",
"Revenue (Millions)": 179.02,
"Rating": 6.8,
},
{
"Title": "Super 8",
"Genre": "Other",
"Revenue (Millions)": 126.98,
"Rating": 7.1,
},
{
"Title": "Law Abiding Citizen",
"Genre": "Crime",
"Revenue (Millions)": 73.34,
"Rating": 7.4,
},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_scatter |
X axis | Revenue (Millions) |
Y axis | Rating |
Color field | Genre |
Funnel
| Setting name | Type | Description | Default |
|---|---|---|---|
Is transposed | boolean | Whether the chart is transposed (horizontal) or not (vertical). | false |
Example data:
import pandas as pd
df_funnel = pd.DataFrame(
[
{"year": "1999", "value": 500},
{"year": "2000", "value": 350},
{"year": "2001", "value": 215},
{"year": "2002", "value": 95},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_funnel |
X axis | year |
Y axis | value |
Is transposed | true |
Treemap
Example data:
import pandas as pd
df_treemap = pd.DataFrame(
[
{"city": "Madrid", "population": 6_800_000},
{"city": "Málaga", "population": 571_000},
{"city": "Sevilla", "population": 688_000},
{"city": "Barcelona", "population": 1_620_000},
{"city": "Bilbao", "population": 345_000},
{"city": "Valencia", "population": 791_000},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_treemap |
X axis | city |
Y axis | population |
Heatmap
| Setting name | Type | Description | Default |
|---|---|---|---|
Color field | string/column_name | Field to use to color different values. |
Example data:
import pandas as pd
df_heatmap = pd.DataFrame(
[
{"Month of Year": 201601, "District": "Central/Western", "AQHI": 3.341},
{"Month of Year": 201601, "District": "Eastern", "AQHI": 3.266},
{"Month of Year": 201601, "District": "Kwun Tong", "AQHI": 3.446},
{"Month of Year": 201601, "District": "Sham Shui Po", "AQHI": 3.425},
{"Month of Year": 201601, "District": "Kwai Chung", "AQHI": 3.415},
{"Month of Year": 201601, "District": "Tsuen Wan", "AQHI": 3.379},
{"Month of Year": 201601, "District": "Tseung Kwan O", "AQHI": "NULL"},
{"Month of Year": 201601, "District": "Yuen Long", "AQHI": 3.022},
{"Month of Year": 201601, "District": "Tuen Mun", "AQHI": 3.32},
{"Month of Year": 201601, "District": "Tung Chung", "AQHI": 3.05},
{"Month of Year": 201601, "District": "Tai Po", "AQHI": 2.95},
{"Month of Year": 201601, "District": "Sha Tin", "AQHI": 3.164},
{"Month of Year": 201601, "District": "Tap Mun", "AQHI": "NULL"},
{"Month of Year": 201601, "District": "Causeway Bay", "AQHI": 3.975},
{"Month of Year": 201601, "District": "Central", "AQHI": 3.507},
{"Month of Year": 201601, "District": "Mong Kok", "AQHI": 3.591},
{"Month of Year": 201602, "District": "Central/Western", "AQHI": 3.472},
{"Month of Year": 201602, "District": "Eastern", "AQHI": 3.256},
{"Month of Year": 201602, "District": "Kwun Tong", "AQHI": 3.721},
{"Month of Year": 201602, "District": "Sham Shui Po", "AQHI": 3.47},
{"Month of Year": 201602, "District": "Kwai Chung", "AQHI": 3.555},
{"Month of Year": 201602, "District": "Tsuen Wan", "AQHI": 3.418},
{"Month of Year": 201602, "District": "Tseung Kwan O", "AQHI": "NULL"},
{"Month of Year": 201602, "District": "Yuen Long", "AQHI": 3.192},
{"Month of Year": 201602, "District": "Tuen Mun", "AQHI": 3.407},
{"Month of Year": 201602, "District": "Tung Chung", "AQHI": 3.048},
{"Month of Year": 201602, "District": "Tai Po", "AQHI": 3.054},
{"Month of Year": 201602, "District": "Sha Tin", "AQHI": 3.225},
{"Month of Year": 201602, "District": "Tap Mun", "AQHI": 3.281},
{"Month of Year": 201602, "District": "Causeway Bay", "AQHI": 4.185},
{"Month of Year": 201602, "District": "Central", "AQHI": 3.776},
{"Month of Year": 201602, "District": "Mong Kok", "AQHI": 3.707},
{"Month of Year": 201603, "District": "Central/Western", "AQHI": 3.867},
{"Month of Year": 201603, "District": "Eastern", "AQHI": 3.883},
{"Month of Year": 201603, "District": "Kwun Tong", "AQHI": 3.965},
{"Month of Year": 201603, "District": "Sham Shui Po", "AQHI": 3.92},
{"Month of Year": 201603, "District": "Kwai Chung", "AQHI": 3.964},
{"Month of Year": 201603, "District": "Tsuen Wan", "AQHI": 3.797},
{"Month of Year": 201603, "District": "Tseung Kwan O", "AQHI": 3.839},
{"Month of Year": 201603, "District": "Yuen Long", "AQHI": 3.405},
{"Month of Year": 201603, "District": "Tuen Mun", "AQHI": 3.815},
{"Month of Year": 201603, "District": "Tung Chung", "AQHI": 3.556},
{"Month of Year": 201603, "District": "Tai Po", "AQHI": 3.32},
{"Month of Year": 201603, "District": "Sha Tin", "AQHI": 3.557},
{"Month of Year": 201603, "District": "Tap Mun", "AQHI": 3.442},
{"Month of Year": 201603, "District": "Causeway Bay", "AQHI": 4.356},
{"Month of Year": 201603, "District": "Central", "AQHI": 3.99},
{"Month of Year": 201603, "District": "Mong Kok", "AQHI": 4.039},
{"Month of Year": 201604, "District": "Central/Western", "AQHI": 3.247},
{"Month of Year": 201604, "District": "Eastern", "AQHI": 3.804},
{"Month of Year": 201604, "District": "Kwun Tong", "AQHI": 3.471},
{"Month of Year": 201604, "District": "Sham Shui Po", "AQHI": 3.377},
{"Month of Year": 201604, "District": "Kwai Chung", "AQHI": 3.616},
{"Month of Year": 201604, "District": "Tsuen Wan", "AQHI": 3.441},
{"Month of Year": 201604, "District": "Tseung Kwan O", "AQHI": 3.187},
{"Month of Year": 201604, "District": "Yuen Long", "AQHI": 2.919},
{"Month of Year": 201604, "District": "Tuen Mun", "AQHI": 3.476},
{"Month of Year": 201604, "District": "Tung Chung", "AQHI": 2.997},
{"Month of Year": 201604, "District": "Tai Po", "AQHI": 2.961},
{"Month of Year": 201604, "District": "Sha Tin", "AQHI": 3.119},
{"Month of Year": 201604, "District": "Tap Mun", "AQHI": 2.972},
{"Month of Year": 201604, "District": "Causeway Bay", "AQHI": 3.845},
{"Month of Year": 201604, "District": "Central", "AQHI": 3.493},
{"Month of Year": 201604, "District": "Mong Kok", "AQHI": 3.565},
{"Month of Year": 201605, "District": "Central/Western", "AQHI": 3.084},
{"Month of Year": 201605, "District": "Eastern", "AQHI": 3.916},
{"Month of Year": 201605, "District": "Kwun Tong", "AQHI": 3.559},
{"Month of Year": 201605, "District": "Sham Shui Po", "AQHI": 3.305},
{"Month of Year": 201605, "District": "Kwai Chung", "AQHI": 3.373},
{"Month of Year": 201605, "District": "Tsuen Wan", "AQHI": 3.321},
{"Month of Year": 201605, "District": "Tseung Kwan O", "AQHI": 3.333},
{"Month of Year": 201605, "District": "Yuen Long", "AQHI": 2.996},
{"Month of Year": 201605, "District": "Tuen Mun", "AQHI": 3.208},
{"Month of Year": 201605, "District": "Tung Chung", "AQHI": 3.169},
{"Month of Year": 201605, "District": "Tai Po", "AQHI": 3.034},
{"Month of Year": 201605, "District": "Sha Tin", "AQHI": 3.155},
{"Month of Year": 201605, "District": "Tap Mun", "AQHI": 3.286},
{"Month of Year": 201605, "District": "Causeway Bay", "AQHI": 3.686},
{"Month of Year": 201605, "District": "Central", "AQHI": 3.592},
{"Month of Year": 201605, "District": "Mong Kok", "AQHI": 3.563},
{"Month of Year": 201606, "District": "Central/Western", "AQHI": 2.316},
{"Month of Year": 201606, "District": "Eastern", "AQHI": 2.704},
{"Month of Year": 201606, "District": "Kwun Tong", "AQHI": 2.877},
{"Month of Year": 201606, "District": "Sham Shui Po", "AQHI": 2.449},
{"Month of Year": 201606, "District": "Kwai Chung", "AQHI": 2.708},
{"Month of Year": 201606, "District": "Tsuen Wan", "AQHI": 2.467},
{"Month of Year": 201606, "District": "Tseung Kwan O", "AQHI": 2.312},
{"Month of Year": 201606, "District": "Yuen Long", "AQHI": 2.332},
{"Month of Year": 201606, "District": "Tuen Mun", "AQHI": 2.417},
{"Month of Year": 201606, "District": "Tung Chung", "AQHI": 2.252},
{"Month of Year": 201606, "District": "Tai Po", "AQHI": 2.117},
{"Month of Year": 201606, "District": "Sha Tin", "AQHI": 2.155},
{"Month of Year": 201606, "District": "Tap Mun", "AQHI": 2.167},
{"Month of Year": 201606, "District": "Causeway Bay", "AQHI": 3.081},
{"Month of Year": 201606, "District": "Central", "AQHI": 2.728},
{"Month of Year": 201606, "District": "Mong Kok", "AQHI": 2.624},
{"Month of Year": 201607, "District": "Central/Western", "AQHI": 2.485},
{"Month of Year": 201607, "District": "Eastern", "AQHI": 2.721},
{"Month of Year": 201607, "District": "Kwun Tong", "AQHI": 3.2},
{"Month of Year": 201607, "District": "Sham Shui Po", "AQHI": 2.68},
{"Month of Year": 201607, "District": "Kwai Chung", "AQHI": 2.926},
{"Month of Year": 201607, "District": "Tsuen Wan", "AQHI": 2.661},
{"Month of Year": 201607, "District": "Tseung Kwan O", "AQHI": 2.554},
{"Month of Year": 201607, "District": "Yuen Long", "AQHI": 2.674},
{"Month of Year": 201607, "District": "Tuen Mun", "AQHI": 2.683},
{"Month of Year": 201607, "District": "Tung Chung", "AQHI": 2.538},
{"Month of Year": 201607, "District": "Tai Po", "AQHI": 2.468},
{"Month of Year": 201607, "District": "Sha Tin", "AQHI": 2.461},
{"Month of Year": 201607, "District": "Tap Mun", "AQHI": 2.51},
{"Month of Year": 201607, "District": "Causeway Bay", "AQHI": 3.257},
{"Month of Year": 201607, "District": "Central", "AQHI": 2.885},
{"Month of Year": 201607, "District": "Mong Kok", "AQHI": 2.959},
{"Month of Year": 201608, "District": "Central/Western", "AQHI": 3.16},
{"Month of Year": 201608, "District": "Eastern", "AQHI": 3.395},
{"Month of Year": 201608, "District": "Kwun Tong", "AQHI": 3.64},
{"Month of Year": 201608, "District": "Sham Shui Po", "AQHI": 3.354},
{"Month of Year": 201608, "District": "Kwai Chung", "AQHI": 3.477},
{"Month of Year": 201608, "District": "Tsuen Wan", "AQHI": 3.292},
{"Month of Year": 201608, "District": "Tseung Kwan O", "AQHI": 3.095},
{"Month of Year": 201608, "District": "Yuen Long", "AQHI": 3.354},
{"Month of Year": 201608, "District": "Tuen Mun", "AQHI": 3.428},
{"Month of Year": 201608, "District": "Tung Chung", "AQHI": 2.996},
{"Month of Year": 201608, "District": "Tai Po", "AQHI": 3.039},
{"Month of Year": 201608, "District": "Sha Tin", "AQHI": 2.907},
{"Month of Year": 201608, "District": "Tap Mun", "AQHI": 3.025},
{"Month of Year": 201608, "District": "Causeway Bay", "AQHI": 3.819},
{"Month of Year": 201608, "District": "Central", "AQHI": 3.418},
{"Month of Year": 201608, "District": "Mong Kok", "AQHI": 3.441},
{"Month of Year": 201609, "District": "Central/Western", "AQHI": 3.792},
{"Month of Year": 201609, "District": "Eastern", "AQHI": 3.636},
{"Month of Year": 201609, "District": "Kwun Tong", "AQHI": 4.008},
{"Month of Year": 201609, "District": "Sham Shui Po", "AQHI": 3.739},
{"Month of Year": 201609, "District": "Kwai Chung", "AQHI": 3.748},
{"Month of Year": 201609, "District": "Tsuen Wan", "AQHI": 3.599},
{"Month of Year": 201609, "District": "Tseung Kwan O", "AQHI": 3.519},
{"Month of Year": 201609, "District": "Yuen Long", "AQHI": 3.743},
{"Month of Year": 201609, "District": "Tuen Mun", "AQHI": 4.031},
{"Month of Year": 201609, "District": "Tung Chung", "AQHI": 3.441},
{"Month of Year": 201609, "District": "Tai Po", "AQHI": 3.324},
{"Month of Year": 201609, "District": "Sha Tin", "AQHI": 3.281},
{"Month of Year": 201609, "District": "Tap Mun", "AQHI": 3.522},
{"Month of Year": 201609, "District": "Causeway Bay", "AQHI": 4.391},
{"Month of Year": 201609, "District": "Central", "AQHI": 3.853},
{"Month of Year": 201609, "District": "Mong Kok", "AQHI": 3.733},
{"Month of Year": 201610, "District": "Central/Western", "AQHI": 3.116},
{"Month of Year": 201610, "District": "Eastern", "AQHI": 3.186},
{"Month of Year": 201610, "District": "Kwun Tong", "AQHI": 3.204},
{"Month of Year": 201610, "District": "Sham Shui Po", "AQHI": 3.175},
{"Month of Year": 201610, "District": "Kwai Chung", "AQHI": 3.13},
{"Month of Year": 201610, "District": "Tsuen Wan", "AQHI": 3.045},
{"Month of Year": 201610, "District": "Tseung Kwan O", "AQHI": 2.972},
{"Month of Year": 201610, "District": "Yuen Long", "AQHI": 3.186},
{"Month of Year": 201610, "District": "Tuen Mun", "AQHI": 3.312},
{"Month of Year": 201610, "District": "Tung Chung", "AQHI": 2.717},
{"Month of Year": 201610, "District": "Tai Po", "AQHI": 2.791},
{"Month of Year": 201610, "District": "Sha Tin", "AQHI": 2.835},
{"Month of Year": 201610, "District": "Tap Mun", "AQHI": 2.978},
{"Month of Year": 201610, "District": "Causeway Bay", "AQHI": 3.409},
{"Month of Year": 201610, "District": "Central", "AQHI": 3.216},
{"Month of Year": 201610, "District": "Mong Kok", "AQHI": 3.206},
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{"Month of Year": 201806, "District": "Central/Western", "AQHI": 3.049},
{"Month of Year": 201806, "District": "Eastern", "AQHI": 3.388},
{"Month of Year": 201806, "District": "Kwun Tong", "AQHI": 3.224},
{"Month of Year": 201806, "District": "Sham Shui Po", "AQHI": 3.072},
{"Month of Year": 201806, "District": "Kwai Chung", "AQHI": 3.235},
{"Month of Year": 201806, "District": "Tsuen Wan", "AQHI": 2.82},
{"Month of Year": 201806, "District": "Tseung Kwan O", "AQHI": 3.104},
{"Month of Year": 201806, "District": "Yuen Long", "AQHI": 3.04},
{"Month of Year": 201806, "District": "Tuen Mun", "AQHI": 3.209},
{"Month of Year": 201806, "District": "Tung Chung", "AQHI": 2.963},
{"Month of Year": 201806, "District": "Tai Po", "AQHI": 2.509},
{"Month of Year": 201806, "District": "Sha Tin", "AQHI": 3.105},
{"Month of Year": 201806, "District": "Tap Mun", "AQHI": 2.954},
{"Month of Year": 201806, "District": "Causeway Bay", "AQHI": 3.559},
{"Month of Year": 201806, "District": "Central", "AQHI": 3.424},
{"Month of Year": 201806, "District": "Mong Kok", "AQHI": 3.264},
{"Month of Year": 201807, "District": "Central/Western", "AQHI": 2.237},
{"Month of Year": 201807, "District": "Eastern", "AQHI": 2.467},
{"Month of Year": 201807, "District": "Kwun Tong", "AQHI": 2.507},
{"Month of Year": 201807, "District": "Sham Shui Po", "AQHI": 2.337},
{"Month of Year": 201807, "District": "Kwai Chung", "AQHI": 2.446},
{"Month of Year": 201807, "District": "Tsuen Wan", "AQHI": 2.139},
{"Month of Year": 201807, "District": "Tseung Kwan O", "AQHI": 2.308},
{"Month of Year": 201807, "District": "Yuen Long", "AQHI": 2.244},
{"Month of Year": 201807, "District": "Tuen Mun", "AQHI": 2.403},
{"Month of Year": 201807, "District": "Tung Chung", "AQHI": 2.214},
{"Month of Year": 201807, "District": "Tai Po", "AQHI": 2.259},
{"Month of Year": 201807, "District": "Sha Tin", "AQHI": 2.419},
{"Month of Year": 201807, "District": "Tap Mun", "AQHI": 2.169},
{"Month of Year": 201807, "District": "Causeway Bay", "AQHI": 2.834},
{"Month of Year": 201807, "District": "Central", "AQHI": 2.524},
{"Month of Year": 201807, "District": "Mong Kok", "AQHI": 2.599},
{"Month of Year": 201808, "District": "Central/Western", "AQHI": 3.154},
{"Month of Year": 201808, "District": "Eastern", "AQHI": 3.271},
{"Month of Year": 201808, "District": "Kwun Tong", "AQHI": 3.301},
{"Month of Year": 201808, "District": "Sham Shui Po", "AQHI": 3.209},
{"Month of Year": 201808, "District": "Kwai Chung", "AQHI": 3.249},
{"Month of Year": 201808, "District": "Tsuen Wan", "AQHI": 3.043},
{"Month of Year": 201808, "District": "Tseung Kwan O", "AQHI": 3.143},
{"Month of Year": 201808, "District": "Yuen Long", "AQHI": 3.163},
{"Month of Year": 201808, "District": "Tuen Mun", "AQHI": 3.323},
{"Month of Year": 201808, "District": "Tung Chung", "AQHI": 3.072},
{"Month of Year": 201808, "District": "Tai Po", "AQHI": 3.147},
{"Month of Year": 201808, "District": "Sha Tin", "AQHI": 3.133},
{"Month of Year": 201808, "District": "Tap Mun", "AQHI": 2.967},
{"Month of Year": 201808, "District": "Causeway Bay", "AQHI": 3.728},
{"Month of Year": 201808, "District": "Central", "AQHI": 3.559},
{"Month of Year": 201808, "District": "Mong Kok", "AQHI": 3.595},
{"Month of Year": 201809, "District": "Central/Western", "AQHI": 3.423},
{"Month of Year": 201809, "District": "Eastern", "AQHI": 3.483},
{"Month of Year": 201809, "District": "Kwun Tong", "AQHI": 3.361},
{"Month of Year": 201809, "District": "Sham Shui Po", "AQHI": 3.385},
{"Month of Year": 201809, "District": "Kwai Chung", "AQHI": 3.4},
{"Month of Year": 201809, "District": "Tsuen Wan", "AQHI": 3.155},
{"Month of Year": 201809, "District": "Tseung Kwan O", "AQHI": 3.385},
{"Month of Year": 201809, "District": "Yuen Long", "AQHI": 3.407},
{"Month of Year": 201809, "District": "Tuen Mun", "AQHI": 3.677},
{"Month of Year": 201809, "District": "Tung Chung", "AQHI": 3.243},
{"Month of Year": 201809, "District": "Tai Po", "AQHI": 3.273},
{"Month of Year": 201809, "District": "Sha Tin", "AQHI": 3.38},
{"Month of Year": 201809, "District": "Tap Mun", "AQHI": 2.952},
{"Month of Year": 201809, "District": "Causeway Bay", "AQHI": 3.873},
{"Month of Year": 201809, "District": "Central", "AQHI": 3.725},
{"Month of Year": 201809, "District": "Mong Kok", "AQHI": 3.727},
{"Month of Year": 201810, "District": "Central/Western", "AQHI": 4.788},
{"Month of Year": 201810, "District": "Eastern", "AQHI": 4.826},
{"Month of Year": 201810, "District": "Kwun Tong", "AQHI": 4.568},
{"Month of Year": 201810, "District": "Sham Shui Po", "AQHI": 4.751},
{"Month of Year": 201810, "District": "Kwai Chung", "AQHI": 4.631},
{"Month of Year": 201810, "District": "Tsuen Wan", "AQHI": 4.47},
{"Month of Year": 201810, "District": "Tseung Kwan O", "AQHI": 4.73},
{"Month of Year": 201810, "District": "Yuen Long", "AQHI": 4.488},
{"Month of Year": 201810, "District": "Tuen Mun", "AQHI": 4.956},
{"Month of Year": 201810, "District": "Tung Chung", "AQHI": 4.392},
{"Month of Year": 201810, "District": "Tai Po", "AQHI": 4.476},
{"Month of Year": 201810, "District": "Sha Tin", "AQHI": 4.658},
{"Month of Year": 201810, "District": "Tap Mun", "AQHI": 4.595},
{"Month of Year": 201810, "District": "Causeway Bay", "AQHI": 4.947},
{"Month of Year": 201810, "District": "Central", "AQHI": 5.003},
{"Month of Year": 201810, "District": "Mong Kok", "AQHI": 4.917},
{"Month of Year": 201811, "District": "Central/Western", "AQHI": 3.865},
{"Month of Year": 201811, "District": "Eastern", "AQHI": 3.767},
{"Month of Year": 201811, "District": "Kwun Tong", "AQHI": 3.78},
{"Month of Year": 201811, "District": "Sham Shui Po", "AQHI": 3.717},
{"Month of Year": 201811, "District": "Kwai Chung", "AQHI": 3.733},
{"Month of Year": 201811, "District": "Tsuen Wan", "AQHI": 3.676},
{"Month of Year": 201811, "District": "Tseung Kwan O", "AQHI": 3.872},
{"Month of Year": 201811, "District": "Yuen Long", "AQHI": 3.721},
{"Month of Year": 201811, "District": "Tuen Mun", "AQHI": 3.945},
{"Month of Year": 201811, "District": "Tung Chung", "AQHI": 3.461},
{"Month of Year": 201811, "District": "Tai Po", "AQHI": 3.701},
{"Month of Year": 201811, "District": "Sha Tin", "AQHI": 3.825},
{"Month of Year": 201811, "District": "Tap Mun", "AQHI": 3.653},
{"Month of Year": 201811, "District": "Causeway Bay", "AQHI": 4.003},
{"Month of Year": 201811, "District": "Central", "AQHI": 4.089},
{"Month of Year": 201811, "District": "Mong Kok", "AQHI": 4.003},
{"Month of Year": 201812, "District": "Central/Western", "AQHI": 3.355},
{"Month of Year": 201812, "District": "Eastern", "AQHI": 3.329},
{"Month of Year": 201812, "District": "Kwun Tong", "AQHI": 3.333},
{"Month of Year": 201812, "District": "Sham Shui Po", "AQHI": 3.213},
{"Month of Year": 201812, "District": "Kwai Chung", "AQHI": 3.152},
{"Month of Year": 201812, "District": "Tsuen Wan", "AQHI": 3.164},
{"Month of Year": 201812, "District": "Tseung Kwan O", "AQHI": 3.234},
{"Month of Year": 201812, "District": "Yuen Long", "AQHI": 3.222},
{"Month of Year": 201812, "District": "Tuen Mun", "AQHI": 3.403},
{"Month of Year": 201812, "District": "Tung Chung", "AQHI": 3.092},
{"Month of Year": 201812, "District": "Tai Po", "AQHI": 3.101},
{"Month of Year": 201812, "District": "Sha Tin", "AQHI": 3.148},
{"Month of Year": 201812, "District": "Tap Mun", "AQHI": 2.935},
{"Month of Year": 201812, "District": "Causeway Bay", "AQHI": 3.659},
{"Month of Year": 201812, "District": "Central", "AQHI": 3.681},
{"Month of Year": 201812, "District": "Mong Kok", "AQHI": 3.495},
{"Month of Year": 201901, "District": "Central/Western", "AQHI": 4.134},
{"Month of Year": 201901, "District": "Eastern", "AQHI": 3.959},
{"Month of Year": 201901, "District": "Kwun Tong", "AQHI": 4.015},
{"Month of Year": 201901, "District": "Sham Shui Po", "AQHI": 4.005},
{"Month of Year": 201901, "District": "Kwai Chung", "AQHI": 3.986},
{"Month of Year": 201901, "District": "Tsuen Wan", "AQHI": 4.099},
{"Month of Year": 201901, "District": "Tseung Kwan O", "AQHI": 3.964},
{"Month of Year": 201901, "District": "Yuen Long", "AQHI": 4.04},
{"Month of Year": 201901, "District": "Tuen Mun", "AQHI": 3.937},
{"Month of Year": 201901, "District": "Tung Chung", "AQHI": 4.066},
{"Month of Year": 201901, "District": "Tai Po", "AQHI": 3.942},
{"Month of Year": 201901, "District": "Sha Tin", "AQHI": 3.837},
{"Month of Year": 201901, "District": "Tap Mun", "AQHI": 3.565},
{"Month of Year": 201901, "District": "Causeway Bay", "AQHI": 4.375},
{"Month of Year": 201901, "District": "Central", "AQHI": 4.505},
{"Month of Year": 201901, "District": "Mong Kok", "AQHI": 4.324},
{"Month of Year": 201902, "District": "Central/Western", "AQHI": 3.241},
{"Month of Year": 201902, "District": "Eastern", "AQHI": 3.196},
{"Month of Year": 201902, "District": "Kwun Tong", "AQHI": 3.227},
{"Month of Year": 201902, "District": "Sham Shui Po", "AQHI": 3.196},
{"Month of Year": 201902, "District": "Kwai Chung", "AQHI": 3.16},
{"Month of Year": 201902, "District": "Tsuen Wan", "AQHI": 3.177},
{"Month of Year": 201902, "District": "Tseung Kwan O", "AQHI": 3.269},
{"Month of Year": 201902, "District": "Yuen Long", "AQHI": 3.07},
{"Month of Year": 201902, "District": "Tuen Mun", "AQHI": 3.08},
{"Month of Year": 201902, "District": "Tung Chung", "AQHI": 2.95},
{"Month of Year": 201902, "District": "Tai Po", "AQHI": 3.137},
{"Month of Year": 201902, "District": "Sha Tin", "AQHI": 3.1},
{"Month of Year": 201902, "District": "Tap Mun", "AQHI": 3.05},
{"Month of Year": 201902, "District": "Causeway Bay", "AQHI": 3.547},
{"Month of Year": 201902, "District": "Central", "AQHI": 3.496},
{"Month of Year": 201902, "District": "Mong Kok", "AQHI": 3.407},
{"Month of Year": 201903, "District": "Central/Western", "AQHI": 3.539},
{"Month of Year": 201903, "District": "Eastern", "AQHI": 3.608},
{"Month of Year": 201903, "District": "Kwun Tong", "AQHI": 3.635},
{"Month of Year": 201903, "District": "Sham Shui Po", "AQHI": 3.45},
{"Month of Year": 201903, "District": "Kwai Chung", "AQHI": 3.579},
{"Month of Year": 201903, "District": "Tsuen Wan", "AQHI": 3.524},
{"Month of Year": 201903, "District": "Tseung Kwan O", "AQHI": 3.654},
{"Month of Year": 201903, "District": "Yuen Long", "AQHI": 3.481},
{"Month of Year": 201903, "District": "Tuen Mun", "AQHI": 3.486},
{"Month of Year": 201903, "District": "Tung Chung", "AQHI": 3.255},
{"Month of Year": 201903, "District": "Tai Po", "AQHI": 3.461},
{"Month of Year": 201903, "District": "Sha Tin", "AQHI": 3.455},
{"Month of Year": 201903, "District": "Tap Mun", "AQHI": 3.344},
{"Month of Year": 201903, "District": "Causeway Bay", "AQHI": 3.832},
{"Month of Year": 201903, "District": "Central", "AQHI": 3.867},
{"Month of Year": 201903, "District": "Mong Kok", "AQHI": 3.729},
{"Month of Year": 201904, "District": "Central/Western", "AQHI": 3.403},
{"Month of Year": 201904, "District": "Eastern", "AQHI": 3.459},
{"Month of Year": 201904, "District": "Kwun Tong", "AQHI": 3.601},
{"Month of Year": 201904, "District": "Sham Shui Po", "AQHI": 3.297},
{"Month of Year": 201904, "District": "Kwai Chung", "AQHI": 3.416},
{"Month of Year": 201904, "District": "Tsuen Wan", "AQHI": 3.222},
{"Month of Year": 201904, "District": "Tseung Kwan O", "AQHI": 3.506},
{"Month of Year": 201904, "District": "Yuen Long", "AQHI": 3.369},
{"Month of Year": 201904, "District": "Tuen Mun", "AQHI": 3.248},
{"Month of Year": 201904, "District": "Tung Chung", "AQHI": 3.195},
{"Month of Year": 201904, "District": "Tai Po", "AQHI": 3.38},
{"Month of Year": 201904, "District": "Sha Tin", "AQHI": 3.341},
{"Month of Year": 201904, "District": "Tap Mun", "AQHI": 3.306},
{"Month of Year": 201904, "District": "Causeway Bay", "AQHI": 3.73},
{"Month of Year": 201904, "District": "Central", "AQHI": 3.607},
{"Month of Year": 201904, "District": "Mong Kok", "AQHI": 3.62},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_heatmap |
X axis | Month of Year |
Y axis | District |
Color field | AQHI |
Word cloud
| Setting name | Type | Description | Default |
|---|---|---|---|
Color field | string/column_name | Field to use to color different values. |
Example data:
import pandas as pd
df_word_cloud = pd.DataFrame(
[
{"x": "China", "value": 1383220000, "category": "asia"},
{"x": "India", "value": 1316000000, "category": "asia"},
{"x": "United States", "value": 324982000, "category": "america"},
{"x": "Indonesia", "value": 263510000, "category": "asia"},
{"x": "Brazil", "value": 207505000, "category": "america"},
{"x": "Pakistan", "value": 196459000, "category": "asia"},
{"x": "Nigeria", "value": 191836000, "category": "africa"},
{"x": "Bangladesh", "value": 162459000, "category": "asia"},
{"x": "Russia", "value": 146804372, "category": "europe"},
{"x": "Japan", "value": 126790000, "category": "asia"},
{"x": "Mexico", "value": 123518000, "category": "america"},
{"x": "Ethiopia", "value": 104345000, "category": "africa"},
{"x": "Philippines", "value": 104037000, "category": "asia"},
{"x": "Egypt", "value": 93013300, "category": "africa"},
{"x": "Vietnam", "value": 92700000, "category": "asia"},
{"x": "Germany", "value": 82800000, "category": "europe"},
{"x": "Democratic Republic of the Congo","value": 82243000,"category": "africa"},
{"x": "Iran", "value": 80135400, "category": "asia"},
{"x": "Turkey", "value": 79814871, "category": "asia"},
{"x": "Thailand", "value": 68298000, "category": "asia"},
{"x": "France", "value": 67013000, "category": "europe"},
{"x": "United Kingdom", "value": 65110000, "category": "europe"},
{"x": "Italy", "value": 60599936, "category": "europe"},
{"x": "Tanzania", "value": 56878000, "category": "africa"},
{"x": "South Africa", "value": 55908000, "category": "africa"},
{"x": "Myanmar", "value": 54836000, "category": "asia"},
{"x": "South Korea", "value": 51446201, "category": "asia"},
{"x": "Colombia", "value": 49224700, "category": "america"},
{"x": "Kenya", "value": 48467000, "category": "africa"},
{"x": "Spain", "value": 46812000, "category": "europe"},
{"x": "Argentina", "value": 43850000, "category": "america"},
{"x": "Ukraine", "value": 42541633, "category": "europe"},
{"x": "Sudan", "value": 42176000, "category": "africa"},
{"x": "Uganda", "value": 41653000, "category": "africa"},
{"x": "Algeria", "value": 41064000, "category": "africa"},
{"x": "Poland", "value": 38424000, "category": "europe"},
{"x": "Iraq", "value": 37883543, "category": "asia"},
{"x": "Canada", "value": 36541000, "category": "america"},
{"x": "Morocco", "value": 34317500, "category": "africa"},
{"x": "Saudi Arabia", "value": 33710021, "category": "asia"},
{"x": "Uzbekistan", "value": 32121000, "category": "asia"},
{"x": "Malaysia", "value": 32063200, "category": "asia"},
{"x": "Peru", "value": 31826018, "category": "america"},
{"x": "Venezuela", "value": 31431164, "category": "america"},
{"x": "Nepal", "value": 28825709, "category": "asia"},
{"x": "Angola", "value": 28359634, "category": "africa"},
{"x": "Ghana", "value": 28308301, "category": "africa"},
{"x": "Yemen", "value": 28120000, "category": "asia"},
{"x": "Afghanistan", "value": 27657145, "category": "asia"},
{"x": "Mozambique", "value": 27128530, "category": "africa"},
{"x": "Australia", "value": 24460900, "category": "australia"},
{"x": "North Korea", "value": 24213510, "category": "asia"},
{"x": "Cameroon", "value": 23248044, "category": "africa"},
{"x": "Ivory Coast", "value": 22671331, "category": "africa"},
{"x": "Madagascar", "value": 22434363, "category": "africa"},
{"x": "Niger", "value": 21564000, "category": "africa"},
{"x": "Sri Lanka", "value": 21203000, "category": "asia"},
{"x": "Romania", "value": 19760000, "category": "europe"},
{"x": "Burkina Faso", "value": 19632147, "category": "africa"},
{"x": "Syria", "value": 18907000, "category": "asia"},
{"x": "Mali", "value": 18875000, "category": "africa"},
{"x": "Malawi", "value": 18299000, "category": "africa"},
{"x": "Chile", "value": 18191900, "category": "america"},
{"x": "Kazakhstan", "value": 17975800, "category": "asia"},
{"x": "Netherlands", "value": 17121900, "category": "europe"},
{"x": "Ecuador", "value": 16737700, "category": "america"},
{"x": "Guatemala", "value": 16176133, "category": "america"},
{"x": "Zambia", "value": 15933883, "category": "africa"},
{"x": "Cambodia", "value": 15626444, "category": "asia"},
{"x": "Senegal", "value": 15256346, "category": "africa"},
{"x": "Chad", "value": 14965000, "category": "africa"},
{"x": "Zimbabwe", "value": 14542235, "category": "africa"},
{"x": "Guinea", "value": 13291000, "category": "africa"},
{"x": "South Sudan", "value": 12131000, "category": "africa"},
{"x": "Rwanda", "value": 11553188, "category": "africa"},
{"x": "Belgium", "value": 11356191, "category": "europe"},
{"x": "Tunisia", "value": 11299400, "category": "africa"},
{"x": "Cuba", "value": 11239004, "category": "america"},
{"x": "Bolivia", "value": 11145770, "category": "america"},
{"x": "Somalia", "value": 11079000, "category": "africa"},
{"x": "Haiti", "value": 11078033, "category": "america"},
{"x": "Greece", "value": 10783748, "category": "europe"},
{"x": "Benin", "value": 10653654, "category": "africa"},
{"x": "Czech Republic", "value": 10578820, "category": "europe"},
{"x": "Portugal", "value": 10341330, "category": "europe"},
{"x": "Burundi", "value": 10114505, "category": "africa"},
{"x": "Dominican Republic", "value": 10075045, "category": "america"},
{"x": "Sweden", "value": 10054100, "category": "europe"},
{"x": "United Arab Emirates", "value": 10003223, "category": "asia"},
{"x": "Jordan", "value": 9889270, "category": "asia"},
{"x": "Azerbaijan", "value": 9823667, "category": "asia"},
{"x": "Hungary", "value": 9799000, "category": "europe"},
{"x": "Belarus", "value": 9498600, "category": "europe"},
{"x": "Honduras", "value": 8866351, "category": "america"},
{"x": "Austria", "value": 8773686, "category": "europe"},
{"x": "Tajikistan", "value": 8742000, "category": "asia"},
{"x": "Israel", "value": 8690220, "category": "asia"},
{"x": "Switzerland", "value": 8417700, "category": "europe"},
{"x": "Papua New Guinea", "value": 8151300, "category": "australia"},
]
)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_word_cloud |
X axis | x |
Y axis | value |
Color field | category |
Bullet
| Setting name | Type | Description | Default |
|---|---|---|---|
Title | string/variable_name | Title of the bullet. | |
Range | string/variable_name | Range (domain) of the bullet. | |
Target | string/variable_name | Target value of the bullet. |
info
The measure (value) of the bullet is configured via the Input variable field
Example data:
title = 'Value'
ranges = 100
measures = 80
target = 85
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $measures |
Title | $title |
Range | $range |
Target | $target |
Gauge
Example data:
gauge_percent = 0.75
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $gauge_percent |
Liquid
Example data:
liquid_percent = 0.75
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $liquid_percent |
Progress
Example data:
progress_percent = 0.75
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $progress_percent |
Ring progress
Example data:
progress_percent = 0.75
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $progress_percent |
Stock
| Setting name | Type | Description | Default |
|---|---|---|---|
Low | string/column_name | The field to use for low values | |
High | string/column_name | The field to use for high values | |
Open | string/column_name | The field to use for open values | |
Close | string/column_name | The field to use for close values |
Example data:
# Install and import Yahoo Finance
!pip install -q yfinance==0.1.85
import yfinance as yf
# Extract the data
data = yf.Ticker('TSLA')
df_stock = data.history(period="12mo")
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_stock |
X axis | Date |
Low | Low |
High | High |
Open | Open |
Close | Close |
Sankey
| Setting name | Type | Description | Default |
|---|---|---|---|
Group by field | string/column_name | The field to use as weight for the Sankey chart. |
info
X axis will act as source field, and Y axis as target field.
Example data:
import pandas as pd
data = {
"source": ["A", "B", "C", "D", "E"],
"target": ["X", "Y", "Z", "X", "Y"],
"value": [10, 20, 15, 40, 35],
}
df_sankey = pd.DataFrame(data)
Example configuration:
| Setting name | Value |
|---|---|
Input variable | $df_sankey |
X axis | source |
Y axis | target |
Group by field | value |
See also
- All widgets — browse the full widget catalog.
- Table — display the same data in tabular form.
- KPI — surface headline metrics alongside your charts.