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Scatter plot
A scatter plot, or chart, uses dots to represent numerical values for two variables. The position of each dot on the horizontal and vertical axis indicates the values for each data point. Scatter plots are used to verify relationships between variables.

The method to use

The method is shimoku.plt.scatter()
It must contain the following input variables:
data: Union[str, DataFrame, List[Dict]]
x: str
y: List[str]
menu_path: str
order: int
Accepts the following input variables as optional:
title: Optional[str]
x_axis_name: Optional[str]
y_axis_name: Optional[str]
rows_size: Optional[int]
cols_size: Optional[int]
padding: Optional[List[int]]
And it may be personalized with the input variables:
option_modifications: Optional[Dict]

Examples

1. Default configuration

If the code runs with data, menu_path and axes configured as this:
data = [
{'date': dt.date(2021, 1, 1), 'x': 5, 'y': 3},
{'date': dt.date(2021, 1, 2), 'x': 6, 'y': 7},
{'date': dt.date(2021, 1, 3), 'x': 4, 'y': 5},
{'date': dt.date(2021, 1, 4), 'x': 7, 'y': 6},
{'date': dt.date(2021, 1, 5), 'x': 3, 'y': 5},
]
shimoku.plt.scatter(
data=data,
x='date', y=['x', 'y'],
menu_path='test/scatter-1',
order=0,
)
The result is:
The scatter plot in the default configuration.

2. Title, axes names, legend and use of option_modifications, size and padding

It is possible to personalize the title of the chart, adding data points, name for each axis, the legend, size and space occupied. One example could be obtained using:
data = [
{'date': dt.date(2021, 1, 1), 'store 1': 5, 'store 2': 3},
{'date': dt.date(2021, 1, 2), 'store 1': 6, 'store 2': 7},
{'date': dt.date(2021, 1, 3), 'store 1': 4, 'store 2': 5},
{'date': dt.date(2021, 1, 4), 'store 1': 7, 'store 2': 6},
{'date': dt.date(2021, 1, 5), 'store 1': 3, 'store 2': 5},
{'date': dt.date(2021, 1, 6), 'store 1': 6, 'store 2': 1},
{'date': dt.date(2021, 1, 7), 'store 1': 3, 'store 2': 5},
]
shimoku.plt.scatter(
data=data,
x='date', y=['store 1', 'store 2'],
menu_path='test/scatter-2',
order=0, rows_size=2, cols_size=11,
padding="0,0,0,1",
title="Orders (10k)",
x_axis_name="date",
option_modifications={'dataZoom': False},
)
The result is:
The zoom bar was removed using option_modifications={'dataZoom': False}, note the space before the component using padding="0,0,0,1", and the reduction in size with cols_size=11.
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The method to use
Examples
1. Default configuration
2. Title, axes names, legend and use of option_modifications, size and padding