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<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Data 8 Tables Visualizer</title>
<link rel="stylesheet" type="text/css" href="./tables_files/bootstrap.css">
<link rel="stylesheet" type="text/css" href="./tables_files/stylesheet.css">
<script type="text/javascript" language="javascript" src="./tables_files/jquery-3.3.1.js"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js" integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"></script>
</head>
<body>
<div class="row text-center">
<div class="col-md-1"></div>
<div class="col-md-10">
<h1>
<p>Data 8 Table Function Visualizer<p>
</h1>
</div>
<div class="col-md-1" ></div>
</div>
<div class="container">
<ul class="nav nav-tabs" id="nav">
<li class="nav-item">
<a href="#group-tab" class="nav-link active" data-toggle="tab">Group</a>
</li>
<li class="nav-item">
<a href="#pivot-tab" class="nav-link" data-toggle="tab">Pivot</a>
</li>
<!--
<li class="nav-item">
<a href="#join-tab" class="nav-link" data-toggle="tab">Join</a>
</li> -->
</ul>
<div class="tab-content">
<div class="tab-pane active" id="group-tab">
<div class="row">
<div class="col-lg-12 text-center">
<form id="target-group">
<div class="form-group">
<div class="row text-center">
<div class="col-sm-2">
<select class="form-control" id="group-dataset">
<option>cones</option>
<option>chocolates</option>
</select>
</div>
<div class="col-xs-1">
<h2>.group(</h2>
</div>
<div class="col-md-3">
<select class="form-control" id="group-column">
<option>"Flavor"</option>
<option>"Price"</option>
</select>
</div>
<div class="col-xs-1">
<h2>, </h2>
</div>
<div class="col-md-3">
<select class="form-control" id="group-function">
<option>no function (count)</option>
<option>np.average</option>
<option>np.mean</option>
<option>sum</option>
<option>min</option>
<option>max</option>
<option>identity</option>
<option>first</option>
</select>
</div>
<div class="col-xs-2">
<h2>)</h2>
</div>
<div class="col-md-2">
<button type="submit" class="btn btn-primary">Visualize!</button>
</div>
</div>
</div>
</form>
</div>
</div>
</div>
<div class="tab-pane" id="pivot-tab">
<div class="row">
<div class="col-lg-12 text-center">
<form id="target-pivot">
<div class="form-group">
<div class="row text-center">
<div class="col-lg-1">
<select class="form-control" id="pivot-dataset">
<option>cones</option>
<option>chocolates</option>
</select>
</div>
<div class="col-xs-1">
<h2>.pivot(</h2>
</div>
<div class="col-lg-1">
<select class="form-control" id="pivot-column-1">
<option>"Flavor"</option>
<option>"Price"</option>
</select>
</div>
<div class="col-xs-1">
<h2>, </h2>
</div>
<div class="col-lg-1">
<select class="form-control" id="pivot-column-2">
<option>"Flavor"</option>
<option>"Price"</option>
</select>
</div>
<div class="col-xs-1">
<h2>, </h2>
</div>
<div class="col-lg-2">
<select class="form-control" id="pivot-column-3">
<option>no argument</option>
<option>"Flavor"</option>
<option>"Price"</option>
</select>
</div>
<div class="col-xs-1">
<h2>, </h2>
</div>
<div class="col-md-2">
<select class="form-control" id="pivot-function">
<option>no function (count)</option>
<option>np.average</option>
<option>np.mean</option>
<option>sum</option>
<option>min</option>
<option>max</option>
<option>identity</option>
<option>first</option>
</select>
</div>
<div class="col-xs-2">
<h2>)</h2>
</div>
<div class="col-md-2">
<button type="submit" class="btn btn-primary">Visualize!</button>
</div>
</div>
</div>
</form>
</div>
</div>
</div>
<div class="tab-pane" id="join-tab">
<div class="row">
<div class="col-lg-12 text-center">
<form id="target-join">
<div class="form-group">
<div class="row text-center">
<div class="col-sm-2">
<select class="form-control" id="join-dataset">
<option>cones</option>
<option>chocolates</option>
</select>
</div>
<div class="col-xs-8 text-left" id="join-text">
<h2>.join("Flavor", ratings, "Flavor")</h2>
</div>
<div class="col-md-2">
<button type="submit" class="btn btn-primary">Visualize!</button>
</div>
</div>
</div>
</form>
</div>
</div>
</div>
</div>
<div class="row">
<div class="col-md-12">
<h2 id="code"></h2>
</div>
</div>
<div class="row">
<div class="col-lg-6">
<table id="original" class="table table-striped table-bordered" style="width:100%">
<caption>cones</caption>
<thead>
<tr>
<th>Flavor</th>
<th>Price</th>
</tr>
</thead>
<tbody>
<tr>
<td>Strawberry</td>
<td>3.55</td>
</tr>
<tr>
<td>Chocolate</td>
<td>4.75</td>
</tr>
<tr>
<td>Chocolate</td>
<td>6.55</td>
</tr>
<tr>
<td>Strawberry</td>
<td>5.25</td>
</tr>
<tr>
<td>Chocolate</td>
<td>5.25</td>
</tr>
</tbody>
</table>
</div>
<div class="col-lg-6">
<table id="grouped" class="table table-striped table-bordered" style="width:100%">
<caption>chocolates</caption>
<thead>
<tr>
<th>Color</th>
<th>Shape</th>
<th>Amount</th>
<th>Price</th>
</tr>
</thead>
<tbody>
<tr>
<td>Dark</td>
<td>Round</td>
<td>4</td>
<td>1.3</td>
</tr>
<tr>
<td>Milk</td>
<td>Rectangular</td>
<td>6</td>
<td>1.2</td>
</tr>
<tr>
<td>White</td>
<td>Rectangular</td>
<td>12</td>
<td>2</td>
</tr>
<tr>
<td>Dark</td>
<td>Round</td>
<td>7</td>
<td>1.75</td>
</tr>
<tr>
<td>Milk</td>
<td>Rectangular</td>
<td>9</td>
<td>1.4</td>
</tr>
<tr>
<td>Milk</td>
<td>Round</td>
<td>2</td>
<td>1</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="row">
<div class="col-lg-12 text-center" id="control" style="display: none;">
<h2 id="text"> </h2>
<button type="button" class="btn btn-danger" id="back">< Previous Step</button>
<button type="button" class="btn btn-success" id="next">Next Step ></button>
<button type="button" class="btn btn-primary" id="reload-button">New Visualization</button>
</div>
</div>
</div>
<div class= "text-center">
<p>Inspired by <a target="_blank" href="http://pythontutor.com/visualize.html"><b>Python Tutor</b></a> (created by <a target="_blank" href="http://pgbovine.net/">Philip Guo</a>) and visualizations created by Divyesh Chotai. Created by Yanay Rosen. This is a Beta.</p>
<img src="./tables_files/full_logo_final.png" alt="Data 8 Logo" style="height:3em;">
</div>
</body>
<script type="text/javascript">
// our first table
var datasets = {"cones": {"data":{"Flavor":["Strawberry", "Chocolate", "Chocolate", "Strawberry", "Chocolate"], "Price":[3.55, 4.75, 6.55, 5.25, 5.25]}, "col_order":["Flavor", "Price"], "join-data":{"Kind":["Strawberry", "Chocolate", "Vanilla"], "Stars":[2.5, 3.5, 4]}, "join-cols":["Flavor", "Kind"], "join-name":"ratings"},
"chocolates":{"data":{"Color":["Dark", "Milk", "White", "Dark", "Milk", "Milk"], "Shape":["Round", "Rectangular", "Rectangular", "Round", "Rectangular", "Round"],"Amount":[4,6,12,7,9,2],"Price":[1.3,1.2,2.0,1.75,1.4,1.0]}, "col_order":["Color", "Shape", "Amount", "Price"], "join-data":{"Shape":["Round", "Round", "Rectangular", "Triangular"], "Weight":[3.1, 4.25, 3,6, 2.9]}, "join-cols":["Shape", "Shape"], "join-name":"weights"}
}
var data;
// group function
function group(dataset, column, func_name) {
var states = [];
var data = dataset["data"];
// phase one is generate the new table with columns and rows
var columns = Object.keys(data);
if (func_name === "count") {
var new_columns = [column, "count"];
// highlight the group column in original table
var state = {"o_col_h":[dataset["col_order"].indexOf(column)]};
states.push(state);
// say default is to count and add column to new table
var n_data = {};
n_data[column] = [];
n_data["count"] = [];
var ordered = new_columns;
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "text":"By default, group will count the number of rows with unique values", "n_col_h":JSON.parse(JSON.stringify([1])), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
} else {
// highlight the group column in original table
var state = {"o_col_h":[dataset["col_order"].indexOf(column)]};
states.push(state);
// add the original column to the table
var n_data = {};
n_data[column] = [];
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_h":[0], "n_col_ord":[column]};
states.push(state);
var rest_of_columns = columns.filter(function(x) {
return x !== column;
});
var new_columns = [column] + rest_of_columns.map(x => x + " " + func_name)
// highlight the column names in original table
var ordered = [column];
var n_data = {};
n_data[column] = [];
rest_of_columns.forEach((item, i) => {
// highlight the specific column in original table and highlight the function name
var new_col_name = item + " " + func_name;
var state = {"o_col_h":[dataset["col_order"].indexOf(item)], "command_h":"func", "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
// add the new column to the table
n_data[new_col_name] = [];
ordered.push(new_col_name);
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_h":[1+i], "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
});
}
// phase two is get unique values
var uniq = new Set(data[column]);
// highlight the group column in original table
// display the uniq values of text
var unique_str = "Unique values: [" + Array.from(uniq).join(', ') + "]";
var state = {"o_col_h":[dataset["col_order"].indexOf(column)], "text":unique_str, "n_col_ord":JSON.parse(JSON.stringify(ordered)), "n_data":JSON.parse(JSON.stringify(n_data))};
states.push(state);
// phase three is step through the original table and generate the arrays
var n_data_real = JSON.parse(JSON.stringify(n_data));
uniq.forEach((item, i) => {
// highlight the items in original table and add value to column
var idx_to_highlight = data[column].map(function(x, j) {return j}).filter(function(x) {
return data[column][x] === item;
});
// highlight all the rows and add the value to the new table
n_data[column].push(item);
n_data_real[column].push(item);
var state = {"o_row_h":JSON.parse(JSON.stringify(idx_to_highlight)), "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
if (func_name === "count") {
var new_columns = [column, "count"];
// set the value in grouped count column to num rows
var num = idx_to_highlight.length;
// add the num to the state
n_data["count"].push(num);
var state = {"o_row_h":JSON.parse(JSON.stringify(idx_to_highlight)), "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
} else {
columns.forEach((item, i) => {
if (item == column) {
return;
}
// highlight the specific column in original table and highlight the row values
var cell_highlights = [];
var cell_values = [];
var new_col_name = item + " " + func_name;
idx_to_highlight.forEach((value, j) => {
// step through the rest of the columns
var cell = [value, i];
cell_highlights.push(cell);
cell_values.push(data[item][value]);
});
n_data[new_col_name].push("[" + Array.from(cell_values).join(", ") +"]");
var real_value;
if (func_name === "sum") {
real_value = cell_values.reduce((a, b) => a +b, 0);
} else if (func_name === "average" || func_name === "mean") {
real_value = cell_values.reduce((a, b) => a +b, 0) / cell_values.length;
} else if (func_name === "first") {
real_value = cell_values[0];
} else if (func_name === "identity") {
real_value = "[" + Array.from(cell_values) +"]"
} else if (func_name === "max") {
real_value = Math.max.apply(null, cell_values);
} else if (func_name === "min") {
real_value = Math.min.apply(null, cell_values);
}
if (func_name !== "identity" && func_name !== "first" && func_name !== "count" && typeof cell_values[0] === "string") {
real_value = "";
}
n_data_real[new_col_name].push(real_value);
var state = {"o_col_h":[dataset["col_order"].indexOf(item)], "o_row_h":JSON.parse(JSON.stringify(idx_to_highlight)), "o_cell_h":JSON.parse(JSON.stringify(cell_highlights)), "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
});
}
});
if (func_name !== "count") {
// highlight the func name
var state = {"command_h":"func", "text":"Call the function on Arrays", "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered)), "display_with_function":true};
states.push(state);
var state = {"n_data":JSON.parse(JSON.stringify(n_data_real)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
} else {
var state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
}
return states
}
function pivot(data, pivot_column, group_column, collect_column, func_name) {
var o_ordered = data["col_order"];
var data = data["data"]
var states = [];
// phase one is generate the new table with columns and rows
var original_columns = Object.keys(data);
var pivot_uniq = Array.from(new Set(data[pivot_column]));
var group_uniq = Array.from(new Set(data[group_column]));
var new_columns = [group_column].concat(pivot_uniq);
// display the new columns
var states = [];
// highlight the pivot column
var state = {"o_col_h":[o_ordered.indexOf(pivot_column)], "text":"Unique Value(s) in Pivot Column are: [" + pivot_uniq.join(", ") + "]"};
states.push(state);
var n_data = {};
new_columns.forEach((item, i) => {
n_data[item] = [];
});
// add the columns
var ordered = new_columns;
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
// add the rows
n_data[group_column] = JSON.parse(JSON.stringify(group_uniq));
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered)), text:"Unique Value(s) in group column are: [" + group_uniq.join(", ") + "]", "o_col_h":[o_ordered.indexOf(group_column)]};
states.push(state);
// iterate through the pairings highlighting the pivot column and row value, the group column and row value in n
// if there is a specified column then highlight that column in o and the cell value
// if func is count put zeros everywhere
data[group_column].forEach(function(grouped_value, i) {
// highlight the row, highlight the two columns in new
pivot_uniq.forEach((pivot_value, i) => {
var group_index = group_uniq.indexOf(grouped_value);
if (func_name === "count") {
n_data = JSON.parse(JSON.stringify(n_data));
n_data[pivot_value][group_index] = 0;
} else {
//if its a function use arrays and highlight the column
n_data[pivot_value][group_index] = [];
}
});
});
// iterate through every row
data[group_column].forEach(function(grouped_value, i) {
// highlight the row, highlight the two columns in new
var pivot_value = data[pivot_column][i];
var group_index = group_uniq.indexOf(grouped_value);
var pivot_index = pivot_uniq.indexOf(pivot_value);
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered)), "o_row_h":[i], "n_col_h":[pivot_index + 1], "n_row_h":[group_index]};
if (func_name !== "count") {
state["o_col_h"] = [o_ordered.indexOf(collect_column)];
state["display_as_arrays"] = true;
} else {
state["text"] = "By Default, pivot counts how often each pair occurs.";
}
states.push(state);
// if its counts use a counter
if (func_name === "count") {
n_data = JSON.parse(JSON.stringify(n_data));
n_data[pivot_value][group_index] = n_data[pivot_value][group_index] + 1;
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered)), "o_row_h":[i], "n_col_h":[pivot_index + 1], "n_row_h":[group_index], "text":"By Default, pivot counts how often each pair occurs."};
state["n_cell_h"] = [[group_index, pivot_index + 1]];
states.push(state);
} else {
//if its a function use arrays and highlight the column
var new_value = data[collect_column][i];
n_data[pivot_value][group_index] = JSON.parse(JSON.stringify(n_data[pivot_value][group_index])).concat([new_value])
state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered)), "o_row_h":[i], "n_col_h":[pivot_index + 1], "n_row_h":[group_index], "n_cell_h":[group_index, pivot_index+1]};
state["o_col_h"] = [o_ordered.indexOf(collect_column)];
state["o_cell_h"] = [[i, o_ordered.indexOf(collect_column)]];
state["n_cell_h"] = [[group_index, pivot_index + 1]];
state["display_as_arrays"] = true;
}
});
// finally, call the function if needed on arrays
if (func_name !== "count") {
var state = {"command_h":"func", "text":"Call the function on Arrays", "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
state["display_with_function"] = true;
state["display_as_arrays"] = true;
states.push(state);
n_data = JSON.parse(JSON.stringify(n_data));
pivot_uniq.forEach((pivot_col, i) => {
all_values = n_data[pivot_col];
all_values = all_values.map(function(cell_values) {
var real_value;
if (func_name === "sum") {
real_value = cell_values.reduce((a, b) => a +b, 0);
} else if (func_name === "average" || func_name === "mean") {
real_value = cell_values.reduce((a, b) => a +b, 0) / cell_values.length;
} else if (func_name === "first") {
real_value = cell_values[0];
} else if (func_name === "identity") {
real_value = "[" + Array.from(cell_values) +"]"
} else if (func_name === "max") {
real_value = Math.max.apply(null, cell_values);
} else if (func_name === "min") {
real_value = Math.min.apply(null, cell_values);
}
if (func_name !== "identity" && func_name !== "first" && func_name !== "count" && typeof cell_values[0] === "string") {
real_value = 0;
}
if (real_value !== real_value) {
real_value = 0;
}
if (real_value === null) {
real_value = ""
}
return real_value;
});
n_data[pivot_col] = JSON.parse(JSON.stringify(all_values));
});
var state = {"command_h":"func", "text":"Call the function on Arrays", "n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
};
var state = {"n_data":JSON.parse(JSON.stringify(n_data)), "n_col_ord":JSON.parse(JSON.stringify(ordered))};
states.push(state);
return states
}
var states = [];
var cur_state_idx = -1;
var cur_state;
var header_text;
var func_name_original;
var pre_head_text;
var post_head_text;
$("#target-group" ).submit(function( event ) {
$("#grouped").empty();
$('#original').empty();
var col_name = $('#group-column').val();
var func_name = $('#group-function').val();
func_name_original = $('#group-function').val();
if (func_name === "np.average") {
func_name = "average";
}
if (func_name === "np.mean") {
func_name = "mean";
}
if (func_name === "no function (count)") {
func_name = "count";
}
var dataset_val = $('#group-dataset').val();
data = datasets[dataset_val]["data"];
var dataset_col_order = datasets[dataset_val]["col_order"];
// build original table from the rows and values
var ths = dataset_col_order.map(function(x) {
return "<th>" + x + "</th>"
}).join("\n");
var trs = data[dataset_col_order[0]].map(function(item, j) {
var tds = dataset_col_order.map(function(i) {
return "<td>" + data[i][j] + "</td>"
}).join("\n");
return "<tr>\n" + tds + "\n</tr>";
}).join("\n");
var htmlString = "<table><thead><tr>" + ths + "</tr><thead><tbody>" + trs + "<tbody><table";
$("#original").html(htmlString);
states = group(datasets[dataset_val], col_name.replace(/["']/g, ""), func_name);
cur_state_idx = -1;
$('#back').prop('disabled', true);
$('#next').prop('disabled', false);
// set the header text
if (func_name_original === "no function (count)") {
header_text = dataset_val + ".group("+ col_name + ")";
} else {
pre_head_text = dataset_val + ".group("+col_name + ", ";
post_head_text = ")";
header_text = dataset_val + ".group("+col_name + ", " + func_name_original + ")";
}
$('#code').text(header_text)
$("#target-group").hide();
event.preventDefault();
$('#nav').hide();
$('#control').show();
});
$("#target-pivot" ).submit(function( event ) {
$("#grouped").empty();
$('#original').empty();
var col_name_1 = $('#pivot-column-1').val();
var col_name_2 = $('#pivot-column-2').val();
var col_name_3 = $('#pivot-column-3').val();
var func_name = $('#pivot-function').val();
func_name_original = $('#pivot-function').val();
if (col_name_3 === "no argument") {
func_name = "count";
}
if (func_name === "np.average") {
func_name = "average";
}
if (func_name === "np.mean") {
func_name = "mean";
}
if (func_name === "no function (count)") {
func_name = "count";
}
var dataset_val = $('#pivot-dataset').val();
data = datasets[dataset_val]["data"];
var dataset_col_order = datasets[dataset_val]["col_order"];
// build original table from the rows and values
var ths = dataset_col_order.map(function(x) {
return "<th>" + x + "</th>"
}).join("\n");
var trs = data[dataset_col_order[0]].map(function(item, j) {
var tds = dataset_col_order.map(function(i) {
return "<td>" + data[i][j] + "</td>"
}).join("\n");
return "<tr>\n" + tds + "\n</tr>";
}).join("\n");
var htmlString = "<table><thead><tr>" + ths + "</tr><thead><tbody>" + trs + "<tbody><table";
$("#original").html(htmlString);
states = pivot(datasets[dataset_val], col_name_1.replace(/["']/g, ""), col_name_2.replace(/["']/g, ""), col_name_3.replace(/["']/g, ""), func_name);
cur_state_idx = -1;
$('#back').prop('disabled', true);
$('#next').prop('disabled', false);
// set the header text
if (func_name_original === "no function (count)" || col_name_3 === "no argument") {
header_text = dataset_val + ".pivot("+ col_name_1 + ", " + col_name_2 + ")";
} else {
pre_head_text = dataset_val + ".pivot(" + col_name_1 + ", " + col_name_2 + ", " + col_name_3 + ", ";
post_head_text = ")";
header_text = dataset_val + ".pivot(" + col_name_1 + ", " + col_name_2 + ", " + col_name_3 + ", " + func_name_original + ")";
}
$('#code').text(header_text)
$("#target-pivot").hide();
// hide the top bar
$('#nav').hide();
$('#control').show();
event.preventDefault();
});
$('#reload-button').click(function() {
location.reload();
return false;
});
$('#next').click(function() {
if (cur_state_idx < states.length - 1) {
cur_state_idx = cur_state_idx + 1;
cur_state = states[cur_state_idx];
// redraw table
update(cur_state);
}
if (cur_state_idx >= states.length - 1) {
$('#next').prop('disabled', true);
}
if (cur_state_idx >= 0) {
$('#back').prop('disabled', false);
}
})
$('#back').click(function() {
if (cur_state_idx > 0) {
cur_state_idx = cur_state_idx - 1;
cur_state = states[cur_state_idx];
// redraw table
update(cur_state);
}
if (cur_state_idx < states.length -1) {
$('#next').prop('disabled', false);
}
if (cur_state_idx <= 0) {
$('#back').prop('disabled', true);
}
})
function update(state) {
// possible values
var text = state["text"];
if (text === undefined) {
$('#text').text('\xa0');
} else {
$('#text').text(text);
}
var command_h = state["command_h"];
if (command_h === undefined) {
$('#code').replaceWith("<h2 id=\"code\">" + header_text + "</h2>");
} else {
$('#code').replaceWith("<h2 id=\"code\">" + pre_head_text + "<u><b>" + func_name_original + "</b></u>" + post_head_text + "</h2>");
}
var o_col_h = state["o_col_h"];
var o_row_h = state["o_row_h"];
var o_cell_h = state["o_cell_h"];
if (o_col_h === undefined) {
$("#original th").removeClass("highlight-col");
$("#original td").removeClass("highlight-col");
} else {
//Add highlight class to new column
$("#original th").removeClass("highlight-col");
$("#original td").removeClass("highlight-col");
var index = o_col_h[0];
$("#original tr").each(function(i, tr) {
$(tr).find('th').eq(index).addClass("highlight-col");
$(tr).find('td').eq(index).addClass("highlight-col");
});
}
if (o_row_h === undefined) {
$("#original tr").removeClass("highlight-row");
} else {
//Add highlight class to new column
$("#original tr").removeClass("highlight-row");
var idx = o_row_h.map(function(x) {return x+1;});
$("#original tr").each(function(j, tr) {
if (idx.includes(j)) {
$(tr).addClass("highlight-row");
}
});
}
if (o_cell_h === undefined) {
$("#original td").removeClass("highlight-cell");
$("#original th").removeClass("highlight-cell");
} else {
//Add highlight class to new column
$("#original td").removeClass("highlight-cell");
$("#original tr").each(function(i, tr) {
$(tr).find('td').each(function(j, td) {
if (matrixSearch(o_cell_h, [i-1, j])) {
$(td).addClass("highlight-cell")
}
})
$(tr).find('th').each(function(j, th) {
if (matrixSearch(o_cell_h, [i-1, j])) {
$(th).addClass("highlight-cell")
}
})
});
}
var n_data = state["n_data"];
var n_col_ord = state["n_col_ord"];
var n_col_h = state["n_col_h"];
var n_row_h = state["n_row_h"];
var n_cell_h = state["n_cell_h"];
var display_as_arrays = state["display_as_arrays"];
var display_with_function = state["display_with_function"];
if (n_data === undefined) {
$("#grouped").html("");
} else {
$("#grouped").html("");
var ths = n_col_ord.map(function(x) {
return "<th>" + x + "</th>"
}).join("\n");
var trs = n_data[n_col_ord[0]].map(function(item, j) {
var tds = n_col_ord.map(function(key, i) {
if (n_data[key][j] === undefined) {
n_data[key][j] = "";
}
var value = n_data[key][j];
if (i !== 0) {
if (display_as_arrays) {
value = "[" + value.join(", ") + "]"
}
if (display_with_function) {
value = func_name_original + "(" + value + ")"
}
}
var td = "<td>" + value + "</td>";
return td;
});
return "<tr>\n" + tds.join("\n") + "</tr>";
}).join("\n");
var htmlString = "<table><thead><tr>" + ths + "</tr><thead><tbody>" + trs + "<tbody><table";
$("#grouped").html(htmlString);
}
if (n_row_h === undefined) {
$("#grouped tr").removeClass("highlight-row");
} else {
//Add highlight class to new column
$("#grouped tr").removeClass("highlight-row");
var idx = n_row_h.map(function(x) {return x+1;});
$("#grouped tr").each(function(j, tr) {
if (idx.includes(j)) {
$(tr).addClass("highlight-row");
}
});
}
if (n_col_h === undefined) {
$("#grouped th").removeClass("highlight-col");
$("#grouped td").removeClass("highlight-col");
} else {
//Add highlight class to new column
$("#grouped th").removeClass("highlight-col");
$("#grouped td").removeClass("highlight-col");
var index = n_col_h[0];
$("#grouped tr").each(function(i, tr) {
$(tr).find('td').eq(index).addClass("highlight-col");
});
$("#grouped tr").each(function(i, tr) {
$(tr).find('th').eq(index).addClass("highlight-col");
});
}
if (n_cell_h === undefined) {
$("#grouped td").removeClass("highlight-cell");
$("#grouped th").removeClass("highlight-cell");
} else {
//Add highlight class to new column
$("#grouped td").removeClass("highlight-cell");
$("#grouped tr").each(function(i, tr) {
$(tr).find('td').each(function(j, td) {
if (matrixSearch(n_cell_h, [i-1, j])) {
$(td).addClass("highlight-cell")
}
})
});
}
}
$("#group-dataset").change(function(x) {
var dataset_val = $('#group-dataset').val();
var col_options = datasets[dataset_val]["col_order"].map(function(x) {
return '\"' + x + '\"';
});
$('#group-column').empty();
$('#group-column').append(col_options.map(function(x) {
return "<option>" + x + "</option>";
}).join("\n"));
});
$("#pivot-dataset").change(function(x) {
var dataset_val = $('#pivot-dataset').val();
var col_options = datasets[dataset_val]["col_order"].map(function(x) {
return '\"' + x + '\"';
});
$('#pivot-column-1').empty();
$('#pivot-column-2').empty();
$('#pivot-column-3').empty();
$('#pivot-column-1').append(col_options.map(function(x) {
return "<option>" + x + "</option>";
}).join("\n"));
$('#pivot-column-2').append(col_options.map(function(x) {
return "<option>" + x + "</option>";
}).join("\n"));
$('#pivot-column-3').append(col_options.concat(["no argument"]).map(function(x) {
return "<option>" + x + "</option>";
}).join("\n"));
});
$("#join-dataset").change(function(x) {
var dataset_val = $('#join-dataset').val();
var join_cols = datasets[dataset_val]["join-cols"]
var join_table = datasets[dataset_val]["join-name"];
$('#join-text').empty();
$('#join-text').append(
"<h2>.join(\"" + join_cols[0] + "\", " + join_table + ", \"" + join_cols[0] + "\")</h2>"
);
});
function matrixSearch(arr, x) {
var contained = false;
arr.forEach((item, i) => {
if (JSON.stringify(item) === JSON.stringify(x)) {
contained = true;
}
});
return contained;
}
</script>
</html>