Update(blocks): python新增一些pandas图形块，多语言将在稳定后进行
新增pandas API如下： 1. 值排序: sort_values() 2. 获取前 / 后n行数据: head() / tail() 3. 根据所给条件筛选数据 4. 通过给定标签分组: groupby() 5. 常用聚合函数
This commit is contained in:
王立帮
@@ -1455,4 +1455,109 @@ export const py_sum = {
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this.setOutput(true);
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this.setTooltip('Returns the sum of the iterable.');
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}
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};
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};
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export const dataframe_sort_values = {
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init: function () {
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this.setColour(DATA_HUE);
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this.appendValueInput('DICT')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.setCheck('Dict');
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('值排序');
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this.appendValueInput('KEY')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('标签');
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('排序方式')
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.appendField(new Blockly.FieldDropdown([
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['升序', 'True'],
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['降序', 'False']
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]), 'AS_CENDING');
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this.setOutput(true);
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this.setInputsInline(true);
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this.setTooltip('');
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}
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}
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export const dataframe_head_tail = {
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init: function () {
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this.setColour(DATA_HUE);
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this.appendValueInput('DICT')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.setCheck('Dict');
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('获取')
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.appendField(new Blockly.FieldDropdown([
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['前几行', 'head'],
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['最后几行', 'tail']
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]), 'TYPE');
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this.appendValueInput('LINES')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('行数');
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this.setOutput(true);
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this.setInputsInline(true);
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this.setTooltip('');
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}
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}
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export const dataframe_select = {
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init: function () {
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this.setColour(DATA_HUE);
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this.appendValueInput('DICT')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.setCheck('Dict');
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('筛选数据');
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this.appendValueInput('KEY')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('满足条件');
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this.setOutput(true);
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this.setInputsInline(true);
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this.setTooltip('');
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}
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}
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export const dataframe_groupby = {
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init: function () {
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this.setColour(DATA_HUE);
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this.appendValueInput('DICT')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.setCheck('Dict');
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this.appendValueInput('KEY')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('通过标签');
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField('分组');
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this.setOutput(true);
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this.setInputsInline(true);
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this.setTooltip('');
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}
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}
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export const dataframe_aggregate_func = {
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init: function () {
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this.setColour(DATA_HUE);
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this.appendDummyInput()
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.setAlign(Blockly.inputs.Align.RIGHT)
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.appendField(new Blockly.FieldDropdown([
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['求最小值', 'min'],
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['求最大值', 'max'],
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['求和', 'sum'],
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['求平均值', 'mean'],
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['求中位数', 'median'],
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['求标准差', 'std']
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]), 'TYPE');
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this.appendValueInput('DICT')
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.setAlign(Blockly.inputs.Align.RIGHT)
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.setCheck('Dict');
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this.setOutput(true);
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this.setInputsInline(true);
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this.setTooltip('');
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}
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}
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@@ -644,4 +644,41 @@ export const py_sum = function (block, generator) {
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var array = generator.valueToCode(block, 'ARRAY', generator.ORDER_ATOMIC) || '[]';
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var code = 'sum(' + array + ')';
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return [code, generator.ORDER_ATOMIC];
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}
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export const dataframe_sort_values = function (block, generator) {
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const dict = generator.valueToCode(block, 'DICT', generator.ORDER_ATOMIC) || 'df';
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const key = generator.valueToCode(block, 'KEY', generator.ORDER_ATOMIC) || '\'tag\'';
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const ascending = block.getFieldValue('AS_CENDING');
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const code = `${dict}.sort_values(by=${key}, ascending=${ascending})`;
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return [code, generator.ORDER_ATOMIC];
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}
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export const dataframe_head_tail = function (block, generator) {
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const dict = generator.valueToCode(block, 'DICT', generator.ORDER_ATOMIC) || 'df';
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const lines = generator.valueToCode(block, 'LINES', generator.ORDER_ATOMIC) || '1';
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const type = block.getFieldValue('TYPE');
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const code = `${dict}.${type}(${lines})`;
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return [code, generator.ORDER_ATOMIC];
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}
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export const dataframe_select = function (block, generator) {
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const dict = generator.valueToCode(block, 'DICT', generator.ORDER_ATOMIC) || 'df';
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const key = generator.valueToCode(block, 'KEY', generator.ORDER_ATOMIC) || 'df[\'tag\'] > 1';
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const code = `${dict}[${key}]`;
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return [code, generator.ORDER_ATOMIC];
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}
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export const dataframe_groupby = function (block, generator) {
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const dict = generator.valueToCode(block, 'DICT', generator.ORDER_ATOMIC) || 'df';
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const key = generator.valueToCode(block, 'KEY', generator.ORDER_ATOMIC) || '\'tag\'';
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const code = `${dict}.groupby(by=${key})`;
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return [code, generator.ORDER_ATOMIC];
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}
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export const dataframe_aggregate_func = function (block, generator) {
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const dict = generator.valueToCode(block, 'DICT', generator.ORDER_ATOMIC) || 'df';
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const type = block.getFieldValue('TYPE');
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const code = `${dict}.${type}()`;
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return [code, generator.ORDER_ATOMIC];
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}
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@@ -2457,11 +2457,11 @@
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</value>
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</block>
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<block type="dataframe_info">
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<value name="DATAFRAME">
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<shadow type="variables_get">
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<field name="VAR">df</field>
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</shadow>
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</value>
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<value name="DATAFRAME">
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<shadow type="variables_get">
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<field name="VAR">df</field>
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</shadow>
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</value>
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</block>
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<block type="dataframe_median">
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<value name="DATAFRAME">
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@@ -2472,61 +2472,61 @@
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</block>
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<block type="numpy_min">
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<value name="ARRAY">
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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</value>
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<dummy>
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<field name="AXIS">None</field>
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<field name="AXIS">None</field>
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</dummy>
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</block>
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<block type="numpy_max">
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<value name="ARRAY">
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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</value>
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<dummy>
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<field name="AXIS">None</field>
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<field name="AXIS">None</field>
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</dummy>
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</block>
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<block type="numpy_sum">
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<value name="ARRAY">
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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</value>
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</block>
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<block type="py_sum">
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<block type="py_sum">
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<value name="ARRAY">
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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</value>
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</block>
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</block>
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<block type="numpy_size">
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<value name="ARRAY">
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">array</field>
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</shadow>
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</value>
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</block>
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<block type="dataframe_fillna">
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<value name="DATAFRAME">
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<shadow type="variables_get">
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<field name="VAR">df</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">df</field>
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</shadow>
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</value>
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<value name="VALUE">
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<shadow type="variables_get">
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<field name="VAR">value</field>
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</shadow>
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<shadow type="variables_get">
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<field name="VAR">value</field>
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</shadow>
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</value>
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<dummy>
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<field name="INPLACE">False</field>
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<field name="INPLACE">False</field>
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</dummy>
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</block>
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</block>
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<block type="pandas_dropna">
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<value name="DF">
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<shadow type="variables_get">
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@@ -2578,9 +2578,9 @@
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</block>
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<block type="numpy_random_random">
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<value name="SIZE">
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<shadow type="math_number">
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<field name="NUM">1</field>
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</shadow>
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<shadow type="math_number">
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<field name="NUM">1</field>
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</shadow>
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</value>
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</block>
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<block type="numpy_c_">
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@@ -2618,9 +2618,9 @@
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</block>
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<block type="numpy_square">
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<value name="ARRAY">
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<shadow type="variables_get">
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||||
<field name="VAR">array</field>
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</shadow>
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||||
<shadow type="variables_get">
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||||
<field name="VAR">array</field>
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||||
</shadow>
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||||
</value>
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</block>
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<block type="matrix_multiplication">
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@@ -2637,14 +2637,14 @@
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</block>
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<block type="numpy_dot">
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<value name="ARRAY1">
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<shadow type="variables_get">
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||||
<field name="VAR">array1</field>
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||||
</shadow>
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||||
<shadow type="variables_get">
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||||
<field name="VAR">array1</field>
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||||
</shadow>
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||||
</value>
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||||
<value name="ARRAY2">
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||||
<shadow type="variables_get">
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||||
<field name="VAR">array2</field>
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||||
</shadow>
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||||
<shadow type="variables_get">
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||||
<field name="VAR">array2</field>
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||||
</shadow>
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||||
</value>
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||||
</block>
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||||
<block type="array_toarray">
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@@ -2835,6 +2835,95 @@
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||||
</shadow>
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||||
</value>
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||||
</block>
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||||
<block type="dataframe_sort_values">
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||||
<value name="DICT">
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||||
<shadow type="variables_get">
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||||
<field name="VAR">df1</field>
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||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_head_tail">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="LINES">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_select">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<block type="logic_compare">
|
||||
<field name="OP">GT</field>
|
||||
<value name="A">
|
||||
<block type="dataframe_get">
|
||||
<field name="MODE">column</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
<value name="B">
|
||||
<block type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_groupby">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_aggregate_func">
|
||||
<field name="TYPE">min</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
<block type="dataframe_get">
|
||||
<field name="MODE">column</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
<block type="pl_plot_easy">
|
||||
<value name="SER">
|
||||
<shadow type="variables_get">
|
||||
@@ -3225,342 +3314,342 @@
|
||||
</category>
|
||||
<category id="catsklearn" colour="80">
|
||||
<block type="sklearn_make_classification">
|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">20</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_informative">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_redundant">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_repeated">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_classes">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_clusters_per_class">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
</value>
|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">20</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_informative">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_redundant">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_repeated">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_classes">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_clusters_per_class">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="sklearn_make_regression">
|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
<value name="n_informative">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">10</field>
|
||||
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|
||||
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|
||||
<value name="n_targets">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
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|
||||
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|
||||
<value name="bias">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0.0</field>
|
||||
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|
||||
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|
||||
<value name="noise">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0.0</field>
|
||||
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|
||||
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|
||||
<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
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|
||||
<shadow type="math_number">
|
||||
<field name="NUM">10</field>
|
||||
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|
||||
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|
||||
<value name="n_targets">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
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|
||||
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|
||||
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|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0.0</field>
|
||||
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|
||||
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|
||||
<value name="noise">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">0.0</field>
|
||||
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|
||||
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|
||||
<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
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|
||||
<block type="sklearn_make_blobs">
|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
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|
||||
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|
||||
<value name="centers">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
<value name="cluster_std">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1.0</field>
|
||||
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|
||||
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|
||||
<value name="center_box">
|
||||
<block type="tuple_create_with_text_return">
|
||||
<field name="TEXT">-10.0,10.0</field>
|
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|
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|
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|
||||
<shadow type="logic_boolean">
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<value name="n_samples">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
<value name="n_features">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">2</field>
|
||||
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|
||||
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|
||||
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|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
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|
||||
<shadow type="math_number">
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<field name="TEXT">-10.0,10.0</field>
|
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|
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">iris</field>
|
||||
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|
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|
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|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">iris_y</field>
|
||||
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|
||||
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|
||||
<value name="test_size">
|
||||
<shadow type="math_number">
|
||||
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|
||||
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|
||||
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|
||||
<value name="rondom_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
<value name="train_data">
|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
||||
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|
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<value name="test_size">
|
||||
<shadow type="math_number">
|
||||
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|
||||
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|
||||
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|
||||
<value name="rondom_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
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|
||||
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|
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|
||||
<value name="fit_intercept">
|
||||
<shadow type="logic_boolean">
|
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|
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|
||||
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|
||||
<value name="normalize">
|
||||
<shadow type="logic_boolean">
|
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<field name="BOOL">FALSE</field>
|
||||
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|
||||
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|
||||
<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
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|
||||
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|
||||
<shadow type="logic_boolean">
|
||||
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|
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|
||||
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|
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<value name="normalize">
|
||||
<shadow type="logic_boolean">
|
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<field name="BOOL">FALSE</field>
|
||||
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|
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|
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<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
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|
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</block>
|
||||
<block type="sklearn_Ridge">
|
||||
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|
||||
<shadow type="variables_get">
|
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<field name="VAR">model</field>
|
||||
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|
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|
||||
<value name="alpha">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1.0</field>
|
||||
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|
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|
||||
<value name="fit_intercept">
|
||||
<shadow type="logic_boolean">
|
||||
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|
||||
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|
||||
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|
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<value name="normalize">
|
||||
<shadow type="logic_boolean">
|
||||
<field name="BOOL">FALSE</field>
|
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|
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|
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<value name="max_iter">
|
||||
<shadow type="math_number">
|
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<field name="NUM">300</field>
|
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|
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|
||||
<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
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|
||||
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|
||||
<value name="alpha">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1.0</field>
|
||||
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|
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|
||||
<value name="fit_intercept">
|
||||
<shadow type="logic_boolean">
|
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|
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|
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|
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<value name="normalize">
|
||||
<shadow type="logic_boolean">
|
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|
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|
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|
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<value name="max_iter">
|
||||
<shadow type="math_number">
|
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<field name="NUM">300</field>
|
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|
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|
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<value name="random_state">
|
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<shadow type="logic_null"></shadow>
|
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|
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|
||||
<block type="sklearn_DecisionTreeClassifier_Regressor">
|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
||||
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|
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<value name="max_depth">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
||||
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|
||||
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|
||||
<value name="max_depth">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
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</value>
|
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|
||||
<block type="sklearn_RandomForestClassifier_Regressor">
|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
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|
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|
||||
<value name="n_estimators">
|
||||
<shadow type="math_number">
|
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<field name="NUM">100</field>
|
||||
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|
||||
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|
||||
<value name="max_depth">
|
||||
<shadow type="logic_null"></shadow>
|
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</value>
|
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<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
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|
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<value name="random_state">
|
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<shadow type="logic_null"></shadow>
|
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|
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<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
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|
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|
||||
<value name="n_estimators">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">100</field>
|
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|
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|
||||
<value name="max_depth">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
||||
<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="random_state">
|
||||
<shadow type="logic_null"></shadow>
|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
<value name="K">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">5</field>
|
||||
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|
||||
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|
||||
<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
||||
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|
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<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
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|
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|
||||
<value name="K">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">5</field>
|
||||
</shadow>
|
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</value>
|
||||
<value name="n_jobs">
|
||||
<shadow type="logic_null"></shadow>
|
||||
</value>
|
||||
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|
||||
<block type="sklearn_GaussianNB">
|
||||
<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
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|
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|
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<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
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|
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|
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</block>
|
||||
<block type="sklearn_KMeans">
|
||||
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|
||||
<shadow type="variables_get">
|
||||
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|
||||
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|
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|
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<value name="n_clusters">
|
||||
<shadow type="math_number">
|
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|
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|
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|
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|
||||
<shadow type="math_number">
|
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|
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|
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|
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|
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|
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|
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<value name="n_jobs">
|
||||
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|
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|
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|
||||
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
<shadow type="variables_get">
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
<field name="VAR">model</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="sklearn_save_load_model">
|
||||
<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="address">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">D:/mixly/test.pkl</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="model_name">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">model</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="address">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">D:/mixly/test.pkl</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
</category>
|
||||
</category>
|
||||
</xml>
|
||||
@@ -2578,6 +2578,95 @@
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_sort_values">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_head_tail">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="LINES">
|
||||
<shadow type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_select">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<block type="logic_compare">
|
||||
<field name="OP">GT</field>
|
||||
<value name="A">
|
||||
<block type="dataframe_get">
|
||||
<field name="MODE">column</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
<value name="B">
|
||||
<block type="math_number">
|
||||
<field name="NUM">1</field>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_groupby">
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
<block type="dataframe_aggregate_func">
|
||||
<field name="TYPE">min</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
<block type="dataframe_get">
|
||||
<field name="MODE">column</field>
|
||||
<value name="DICT">
|
||||
<shadow type="variables_get">
|
||||
<field name="VAR">df1</field>
|
||||
</shadow>
|
||||
</value>
|
||||
<value name="KEY">
|
||||
<shadow type="text">
|
||||
<field name="TEXT">tag</field>
|
||||
</shadow>
|
||||
</value>
|
||||
</block>
|
||||
</value>
|
||||
</block>
|
||||
<block type="pl_plot_easy">
|
||||
<value name="SER">
|
||||
<shadow type="variables_get">
|
||||
|
||||
Reference in New Issue
Block a user