Repository: mwouts/easyplotly (language: python)

Issue:
Sunburst plots only work when the data has type 'int'
To reproduce:
```
sample = pd.Series({('A29', 'B13', 'C12'): 5.493773959272917,
 ('A29', 'B13', 'C26'): 2.2714461834768,
 ('A29', 'B21', 'C0'): 88.58984469930006,
 ('A29', 'B21', 'C10'): 49.917348529753944,
 ('A29', 'B21', 'C11'): 36.98928975179809,
 ('A29', 'B21', 'C15'): 121.99673244630752,
 ('A29', 'B21', 'C16'): 206.97254210656655,
 ('A29', 'B21', 'C17'): 63.85640681578763,
 ('A29', 'B21', 'C19'): 57.01853927100491,
 ('A29', 'B21', 'C20'): 6.763690315612155,
 ('A29', 'B21', 'C22'): 265.08813270574456,
 ('A29', 'B21', 'C23'): 9.5107439614563,
 ('A29', 'B21', 'C25'): 9.317356993442678,
 ('A29', 'B21', 'C27'): 200.59786382112475,
 ('A29', 'B21', 'C28'): 23.34446288198481,
 ('A29', 'B21', 'C5'): 23.26127917763646,
 ('A29', 'B21', 'C6'): 579.8444286101725,
 ('A29', 'B21', 'C7'): 87.78781070421874,
 ('A29', 'B21', 'C8'): 301.84979651884726,
 ('A29', 'B21', 'C9'): 56.83442956265254,
 ('A29', 'B3', 'C1'): 1.5845332508786036,
 ('A29', 'B3', 'C31'): 5.8081384631896515,
 ('A4', 'B14', 'C18'): 5.6594222679697905,
 ('A4', 'B14', 'C30'): 87.03101418066653,
 ('A4', 'B24', 'C2'): 14.643236457824742}, 
                   index=[('A4', 'B24', 'C2'),
 ('A4', 'B14', 'C18'),
 ('A4', 'B14', 'C30'),
 ('A29', 'B21', 'C11'),
 ('A29', 'B21', 'C6'),
 ('A29', 'B21', 'C0'),
 ('A29', 'B21', 'C16'),
 ('A29', 'B21', 'C5'),
 ('A29', 'B21', 'C20'),
 ('A29', 'B21', 'C9'),
 ('A29', 'B21', 'C8'),
 ('A29', 'B21', 'C7'),
 ('A29', 'B21', 'C19'),
 ('A29', 'B21', 'C15'),
 ('A29', 'B21', 'C17'),
 ('A29', 'B21', 'C10'),
 ('A29', 'B21', 'C28'),
 ('A29', 'B21', 'C25'),
 ('A29', 'B21', 'C23'),
 ('A29', 'B21', 'C22'),
 ('A29', 'B21', 'C27'),
 ('A29', 'B13', 'C12'),
 ('A29', 'B13', 'C26'),
 ('A29', 'B3', 'C1'),
 ('A29', 'B3', 'C31')])
```

Then 
```
go.Figure(ep.Treemap(sample))
```
displays nothing, while
```
go.Figure(ep.Treemap(sample.astype(int))
```
works.

The treemap object that corresponds to the first case is
```
Treemap({
    'branchvalues': 'total',
    'ids': [/A4/B24/C2, /A4/B14/C18, /A4/B14/C30, /A29/B21/C11, /A29/B21/C6,
            /A29/B21/C0, /A29/B21/C16, /A29/B21/C5, /A29/B21/C20, /A29/B21/C9,
            /A29/B21/C8, /A29/B21/C7, /A29/B21/C19, /A29/B21/C15, /A29/B21/C17,
            /A29/B21/C10, /A29/B21/C28, /A29/B21/C25, /A29/B21/C23, /A29/B21/C22,
            /A29/B21/C27, /A29/B13/C12, /A29/B13/C26, /A29/B3/C1, /A29/B3/C31,
            /A4/B24, /A4, /A4/B14, /A29/B21, /A29, /A29/B13, /A29/B3],
    'labels': [C2, C18, C30, C11, C6, C0, C16, C5, C20, C9, C8, C7, C19, C15, C17,
               C10, C28, C25, C23, C22, C27, C12, C26, C1, C31, B24, A4, B14, B21,
               A29, B13, B3],
    'parents': [/A4/B24, /A4/B14, /A4/B14, /A29/B21, /A29/B21, /A29/B21, /A29/B21,
                /A29/B21, /A29/B21, /A29/B21, /A29/B21, /A29/B21, /A29/B21,
                /A29/B21, /A29/B21, /A29/B21, /A29/B21, /A29/B21, /A29/B21,
                /A29/B21, /A29/B21, /A29/B13, /A29/B13, /A29/B3, /A29/B3, /A4,
                None, /A4, /A29, None, /A29, /A29],
    'values': [14.643236457824742, 5.6594222679697905, 87.03101418066653,
               36.98928975179809, 579.8444286101725, 88.58984469930006,
               206.97254210656655, 23.26127917763646, 6.763690315612155,
               56.83442956265254, 301.84979651884726, 87.78781070421874,
               57.01853927100491, 121.99673244630752, 63.85640681578763,
               49.917348529753944, 23.34446288198481, 9.317356993442678,
               9.5107439614563, 265.08813270574456, 200.59786382112475,
               5.493773959272917, 2.2714461834768, 1.5845332508786036,
               5.8081384631896515, 14.643236457824742, 107.33367290646106,
               92.69043644863632, 2189.5406988734117, 2204.698590730229,
               7.765220142749717, 7.392671714068255]
})
```


Discussion / hints:
Actually this must be an issue with float comparison, as `go.Figure(ep.Treemap(sample.round(12)))` works! I'll report that on the plotly community forum.
I've filed this issue in plotly.js https://github.com/plotly/plotly.js/issues/4405 :)
Awesome! Thank you @nicolaskruchten .

Fix patch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index d1b7963..e3908cf 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,10 +1,10 @@
-0.1.2 (2019-12-??)
+0.1.2 (2019-12-04)
 ==================
 
 Fixed
 -----
 - Sunburst and Treemap charts also work with dictionaries and pandas Series with a one-dimensional index (#4)
-
+- Add epsilon when summing floats to fix the issue of Sunburst and Treemap not shown (#3)
 
 0.1.1 (2019-12-02)
 ==================
diff --git a/README.md b/README.md
index f6e254e..239457c 100644
--- a/README.md
+++ b/README.md
@@ -164,3 +164,5 @@ sankey = ep.Sankey(
 
 go.Figure(sankey, layout)
 ```
+
+<script async defer src="https://buttons.github.io/buttons.js"></script>
diff --git a/easyplotly/internals.py b/easyplotly/internals.py
index 596d56c..e25868d 100644
--- a/easyplotly/internals.py
+++ b/easyplotly/internals.py
@@ -3,6 +3,12 @@
 import pandas as pd
 import numpy as np
 
+"""When computing the sum of weights, we had an epsilon to make sure that the JS code
+will see a total larger than the sum. See #3. Note that the example reported at #3 is
+fixed already with EPS=1e-16. But, since (0.1+0.2-0.3)*10=5.5e-16, we prefer to take
+a larger value here."""
+EPS = 1e-15
+
 
 def tree_like_structure_to_dict(values):
     """Transform a series, a dict, or a collection of such objects, into a dictionary index by tuples"""
@@ -51,7 +57,12 @@ def sunburst_or_treemap(values, root_label=None, branchvalues='total', **kwargs)
 
                 if branchvalues == 'total' and not np.isnan(value):
                     # Sum the descendent weights onto the parents (skip nans)
-                    tree[parent] += value
+                    if isinstance(value, int):
+                        tree[parent] += value
+                    else:
+                        # Make sure that the parent is going to be bigger
+                        # than the sum of values, even if we change the summation order (#3)
+                        tree[parent] += value * (1 + depth * EPS)
 
     def ends_with_none_or_nan(key):
         if not key:
diff --git a/easyplotly/version.py b/easyplotly/version.py
index 7076bb0..841b103 100644
--- a/easyplotly/version.py
+++ b/easyplotly/version.py
@@ -1,3 +1,3 @@
 """version number"""
 
-__version__ = '0.1.1'
+__version__ = '0.1.2'
diff --git a/index.html b/index.html
index b054bac..eafde07 100644
--- a/index.html
+++ b/index.html
@@ -13136,10 +13136,10 @@ <h2 id="Sample-data">Sample data<a class="anchor-link" href="#Sample-data">&#182
 
 
 
-<div id="2b2619b3-5fba-403f-af95-9e077caca765"></div>
+<div id="9dada81c-ea55-40f3-b588-f22dedab8abe"></div>
 <div class="output_subarea output_javascript ">
 <script type="text/javascript">
-var element = $('#2b2619b3-5fba-403f-af95-9e077caca765');
+var element = $('#9dada81c-ea55-40f3-b588-f22dedab8abe');
 require.config({
     paths: {
         datatables: 'https://cdn.datatables.net/1.10.19/js/jquery.dataTables.min',
@@ -13218,7 +13218,7 @@ <h2 id="Sample-data">Sample data<a class="anchor-link" href="#Sample-data">&#182
 
 
 <div class="output_html rendered_html output_subarea output_execute_result">
-<div><table id="8e92614e-f28b-41e6-a79a-519ac15455fb" class="display"><thead>
+<div><table id="1b93f9f0-0dfe-4bb8-ad1e-9eda27a970bb" class="display"><thead>
     <tr style="text-align: right;">
       <th></th>
       <th></th>
@@ -13237,7 +13237,7 @@ <h2 id="Sample-data">Sample data<a class="anchor-link" href="#Sample-data">&#182
     $(document).ready(function () {        
         var dt_args = {"columnDefs": [{"width": "70px", "targets": "_all"}], "data": [["East Asia & Pacific", "American Samoa", 55465.0, NaN], ["East Asia & Pacific", "Australia", 24992370.0, 82.497561], ["East Asia & Pacific", "Brunei Darussalam", 428962.0, 75.585], ["East Asia & Pacific", "Cambodia", 16249800.0, 69.289], ["East Asia & Pacific", "China", 1392730000.0, 76.47], ["East Asia & Pacific", "Fiji", 883483.0, 67.252], ["East Asia & Pacific", "French Polynesia", 277679.0, 77.251], ["East Asia & Pacific", "Guam", 165768.0, 79.631], ["East Asia & Pacific", "Hong Kong SAR, China", 7451000.0, 84.680488], ["East Asia & Pacific", "Indonesia", 267663400.0, 71.282], ["East Asia & Pacific", "Japan", 126529100.0, 84.099756], ["East Asia & Pacific", "Kiribati", 115847.0, 67.851], ["East Asia & Pacific", "Korea, Dem. People\u2019s Rep.", 25549820.0, 71.91], ["East Asia & Pacific", "Korea, Rep.", 51635260.0, 82.626829], ["East Asia & Pacific", "Lao PDR", 7061507.0, 67.277], ["East Asia & Pacific", "Macao SAR, China", 631636.0, 83.989], ["East Asia & Pacific", "Malaysia", 31528580.0, 75.828], ["East Asia & Pacific", "Marshall Islands", 58413.0, NaN], ["East Asia & Pacific", "Micronesia, Fed. Sts.", 112640.0, 67.618], ["East Asia & Pacific", "Mongolia", 3170208.0, 69.509], ["East Asia & Pacific", "Myanmar", 53708400.0, 66.558], ["East Asia & Pacific", "Nauru", 12704.0, NaN], ["East Asia & Pacific", "New Caledonia", 284060.0, 77.14878], ["East Asia & Pacific", "New Zealand", 4885500.0, 81.658537], ["East Asia & Pacific", "Northern Mariana Islands", 56882.0, NaN], ["East Asia & Pacific", "Palau", 17907.0, NaN], ["East Asia & Pacific", "Papua New Guinea", 8606316.0, 64.01], ["East Asia & Pacific", "Philippines", 106651900.0, 70.952], ["East Asia & Pacific", "Samoa", 196130.0, 73.046], ["East Asia & Pacific", "Singapore", 5638676.0, 82.895122], ["East Asia & Pacific", "Solomon Islands", 652858.0, 72.645], ["East Asia & Pacific", "Taiwan, China", NaN, NaN], ["East Asia & Pacific", "Thailand", 69428520.0, 76.683], ["East Asia & Pacific", "Timor-Leste", 1267972.0, 69.007], ["East Asia & Pacific", "Tonga", 103197.0, 70.701], ["East Asia & Pacific", "Tuvalu", 11508.0, NaN], ["East Asia & Pacific", "Vanuatu", 292680.0, 70.172], ["East Asia & Pacific", "Vietnam", 95540400.0, 75.241], ["Europe & Central Asia", "Albania", 2866376.0, 78.333], ["Europe & Central Asia", "Andorra", 77006.0, NaN], ["Europe & Central Asia", "Armenia", 2951776.0, 74.797], ["Europe & Central Asia", "Austria", 8847037.0, 81.641463], ["Europe & Central Asia", "Azerbaijan", 9942334.0, 72.693], ["Europe & Central Asia", "Belarus", 9485386.0, 74.129268], ["Europe & Central Asia", "Belgium", 11422070.0, 81.439024], ["Europe & Central Asia", "Bosnia and Herzegovina", 3323929.0, 77.128], ["Europe & Central Asia", "Bulgaria", 7024216.0, 74.812195], ["Europe & Central Asia", "Channel Islands", 170499.0, 82.766], ["Europe & Central Asia", "Croatia", 4089400.0, 77.826829], ["Europe & Central Asia", "Cyprus", 1189265.0, 80.672], ["Europe & Central Asia", "Czech Republic", 10625700.0, 79.47561], ["Europe & Central Asia", "Denmark", 5797446.0, 81.004878], ["Europe & Central Asia", "Estonia", 1320884.0, 77.641463], ["Europe & Central Asia", "Faroe Islands", 48497.0, 82.4], ["Europe & Central Asia", "Finland", 5518050.0, 81.429268], ["Europe & Central Asia", "France", 66987240.0, 82.52439], ["Europe & Central Asia", "Georgia", 3731000.0, 73.414], ["Europe & Central Asia", "Germany", 82927920.0, 80.990244], ["Europe & Central Asia", "Gibraltar", 33718.0, NaN], ["Europe & Central Asia", "Greece", 10727670.0, 81.387805], ["Europe & Central Asia", "Greenland", 56025.0, NaN], ["Europe & Central Asia", "Hungary", 9768785.0, 76.063415], ["Europe & Central Asia", "Iceland", 353574.0, 82.204878], ["Europe & Central Asia", "Ireland", 4853506.0, 81.956098], ["Europe & Central Asia", "Isle of Man", 84077.0, NaN], ["Europe & Central Asia", "Italy", 60431280.0, 83.243902], ["Europe & Central Asia", "Kazakhstan", 18276500.0, 72.95], ["Europe & Central Asia", "Kosovo", 1845300.0, 71.946341], ["Europe & Central Asia", "Kyrgyz Republic", 6315800.0, 71.2], ["Europe & Central Asia", "Latvia", 1926542.0, 74.680488], ["Europe & Central Asia", "Liechtenstein", 37910.0, 82.258537], ["Europe & Central Asia", "Lithuania", 2789533.0, 74.670732], ["Europe & Central Asia", "Luxembourg", 607728.0, 82.685366], ["Europe & Central Asia", "Moldova", 3545883.0, 71.717], ["Europe & Central Asia", "Monaco", 38682.0, NaN], ["Europe & Central Asia", "Montenegro", 622345.0, 76.667], ["Europe & Central Asia", "Netherlands", 17231020.0, 81.560976], ["Europe & Central Asia", "North Macedonia", 2082958.0, 75.589], ["Europe & Central Asia", "Norway", 5314336.0, 82.509756], ["Europe & Central Asia", "Poland", 37978550.0, 77.85122], ["Europe & Central Asia", "Portugal", 10281760.0, 81.12439], ["Europe & Central Asia", "Romania", 19473940.0, 75.309756], ["Europe & Central Asia", "Russian Federation", 144478000.0, 72.119024], ["Europe & Central Asia", "San Marino", 33785.0, NaN], ["Europe & Central Asia", "Serbia", 6982084.0, 76.087805], ["Europe & Central Asia", "Slovak Republic", 5447011.0, 77.165854], ["Europe & Central Asia", "Slovenia", 2067372.0, 81.17561], ["Europe & Central Asia", "Spain", 46723750.0, 83.329268], ["Europe & Central Asia", "Sweden", 10183180.0, 82.307317], ["Europe & Central Asia", "Switzerland", 8516543.0, 83.602439], ["Europe & Central Asia", "Tajikistan", 9100837.0, 70.647], ["Europe & Central Asia", "Turkey", 82319720.0, 77.161], ["Europe & Central Asia", "Turkmenistan", 5850908.0, 67.956], ["Europe & Central Asia", "Ukraine", 44622520.0, 71.780976], ["Europe & Central Asia", "United Kingdom", 66488990.0, 81.156098], ["Europe & Central Asia", "Uzbekistan", 32955400.0, 71.388], ["Latin America & Caribbean ", "Antigua and Barbuda", 96286.0, 76.752], ["Latin America & Caribbean ", "Argentina", 44494500.0, 76.372], ["Latin America & Caribbean ", "Aruba", 105845.0, 76.01], ["Latin America & Caribbean ", "Bahamas, The", 385640.0, 73.554], ["Latin America & Caribbean ", "Barbados", 286641.0, 78.981], ["Latin America & Caribbean ", "Belize", 383071.0, 74.365], ["Latin America & Caribbean ", "Bolivia", 11353140.0, 70.945], ["Latin America & Caribbean ", "Brazil", 209469300.0, 75.456], ["Latin America & Caribbean ", "British Virgin Islands", 29802.0, NaN], ["Latin America & Caribbean ", "Cayman Islands", 64174.0, NaN], ["Latin America & Caribbean ", "Chile", 18729160.0, 79.909], ["Latin America & Caribbean ", "Colombia", 49648680.0, 76.925], ["Latin America & Caribbean ", "Costa Rica", 4999441.0, 79.914], ["Latin America & Caribbean ", "Cuba", 11338140.0, 78.662], ["Latin America & Caribbean ", "Curacao", 159849.0, 78.017073], ["Latin America & Caribbean ", "Dominica", 71625.0, NaN], ["Latin America & Caribbean ", "Dominican Republic", 10627160.0, 73.689], ["Latin America & Caribbean ", "Ecuador", 17084360.0, 76.584], ["Latin America & Caribbean ", "El Salvador", 6420744.0, 72.872], ["Latin America & Caribbean ", "Grenada", 111454.0, 72.388], ["Latin America & Caribbean ", "Guatemala", 17247810.0, 73.81], ["Latin America & Caribbean ", "Guyana", 779004.0, 69.624], ["Latin America & Caribbean ", "Haiti", 11123180.0, 63.29], ["Latin America & Caribbean ", "Honduras", 9587522.0, 74.898], ["Latin America & Caribbean ", "Jamaica", 2934855.0, 74.267], ["Latin America & Caribbean ", "Mexico", 126190800.0, 74.947], ["Latin America & Caribbean ", "Nicaragua", 6465513.0, 74.068], ["Latin America & Caribbean ", "Panama", 4176873.0, 78.149], ["Latin America & Caribbean ", "Paraguay", 6956071.0, 73.992], ["Latin America & Caribbean ", "Peru", 31989260.0, 76.286], ["Latin America & Caribbean ", "Puerto Rico", 3195153.0, 79.634537], ["Latin America & Caribbean ", "Sint Maarten (Dutch part)", 40654.0, NaN], ["Latin America & Caribbean ", "St. Kitts and Nevis", 52441.0, NaN], ["Latin America & Caribbean ", "St. Lucia", 181889.0, 75.907], ["Latin America & Caribbean ", "St. Martin (French part)", 37264.0, 79.721951], ["Latin America & Caribbean ", "St. Vincent and the Grenadines", 110210.0, 72.3], ["Latin America & Caribbean ", "Suriname", 575991.0, 71.463], ["Latin America & Caribbean ", "Trinidad and Tobago", 1389858.0, 73.245], ["Latin America & Caribbean ", "Turks and Caicos Islands", 37665.0, NaN], ["Latin America & Caribbean ", "Uruguay", 3449299.0, 77.632], ["Latin America & Caribbean ", "Venezuela, RB", 28870200.0, 72.246], ["Latin America & Caribbean ", "Virgin Islands (U.S.)", 106977.0, 79.419512], ["Middle East & North Africa", "Algeria", 42228430.0, 76.499], ["Middle East & North Africa", "Bahrain", 1569439.0, 77.032], ["Middle East & North Africa", "Djibouti", 958920.0, 65.893], ["Middle East & North Africa", "Egypt, Arab Rep.", 98423600.0, 71.656], ["Middle East & North Africa", "Iran, Islamic Rep.", 81800270.0, 76.271], ["Middle East & North Africa", "Iraq", 38433600.0, 70.294], ["Middle East & North Africa", "Israel", 8883800.0, 82.602439], ["Middle East & North Africa", "Jordan", 9956011.0, 74.292], ["Middle East & North Africa", "Kuwait", 4137309.0, 75.311], ["Middle East & North Africa", "Lebanon", 6848925.0, 78.833], ["Middle East & North Africa", "Libya", 6678567.0, 72.52], ["Middle East & North Africa", "Malta", 483530.0, 82.453659], ["Middle East & North Africa", "Morocco", 36029140.0, 76.218], ["Middle East & North Africa", "Oman", 4829483.0, 77.393], ["Middle East & North Africa", "Qatar", 2781677.0, 79.981], ["Middle East & North Africa", "Saudi Arabia", 33699950.0, 74.874], ["Middle East & North Africa", "Syrian Arab Republic", 16906280.0, 70.967], ["Middle East & North Africa", "Tunisia", 11565200.0, 76.31], ["Middle East & North Africa", "United Arab Emirates", 9630959.0, 77.647], ["Middle East & North Africa", "West Bank and Gaza", 4569087.0, 73.74], ["Middle East & North Africa", "Yemen, Rep.", 28498690.0, 66.086], ["North America", "Bermuda", 63968.0, 81.441951], ["North America", "Canada", 37058860.0, 82.248976], ["North America", "United States", 327167400.0, 78.539024], ["South Asia", "Afghanistan", 37172390.0, 64.13], ["South Asia", "Bangladesh", 161356000.0, 72.052], ["South Asia", "Bhutan", 754394.0, 71.129], ["South Asia", "India", 1352617000.0, 69.165], ["South Asia", "Maldives", 515696.0, 78.325], ["South Asia", "Nepal", 28087870.0, 70.169], ["South Asia", "Pakistan", 212215000.0, 66.947], ["South Asia", "Sri Lanka", 21670000.0, 76.648], ["Sub-Saharan Africa ", "Angola", 30809760.0, 60.379], ["Sub-Saharan Africa ", "Benin", 11485050.0, 61.174], ["Sub-Saharan Africa ", "Botswana", 2254126.0, 68.812], ["Sub-Saharan Africa ", "Burkina Faso", 19751540.0, 60.768], ["Sub-Saharan Africa ", "Burundi", 11175380.0, 60.898], ["Sub-Saharan Africa ", "Cabo Verde", 543767.0, 72.57], ["Sub-Saharan Africa ", "Cameroon", 25216240.0, 58.511], ["Sub-Saharan Africa ", "Central African Republic", 4666377.0, 52.24], ["Sub-Saharan Africa ", "Chad", 15477750.0, 53.712], ["Sub-Saharan Africa ", "Comoros", 832322.0, 63.912], ["Sub-Saharan Africa ", "Congo, Dem. 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@@ -13341,20 +13341,20 @@ <h2 id="Sunburst-Charts">Sunburst Charts<a class="anchor-link" href="#Sunburst-C
 <div>
         
         
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@@ -13823,20 +13823,20 @@ <h2 id="Sankey-Plot">Sankey Plot<a class="anchor-link" href="#Sankey-Plot">&#182
 <div>
         
         
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0.05}, "xaxis": {"automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "zerolinecolor": "white", "zerolinewidth": 2}, "yaxis": {"automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "zerolinecolor": "white", "zerolinewidth": 2}}}, "title": {"text": "Regions income and lending type<br>Data from the World Bank"}},
                         {"responsive": true}
                     ).then(function(){
                             
-var gd = document.getElementById('251d845b-90ce-42f6-bccf-a48f544f2118');
+var gd = document.getElementById('4852c1c4-88ca-4ccb-94fc-a3c70b997471');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -13870,6 +13870,13 @@ <h2 id="Sankey-Plot">Sankey Plot<a class="anchor-link" href="#Sankey-Plot">&#182
 </div>
 </div>
 
+</div>
+<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
+</div><div class="inner_cell">
+<div class="text_cell_render border-box-sizing rendered_html">
+<script async defer src="https://buttons.github.io/buttons.js"></script>
+</div>
+</div>
 </div>
     </div>
   </div>
diff --git a/requirements-dev.txt b/requirements-dev.txt
index 626611f..a73cb79 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -6,6 +6,7 @@ jupytext
 nbconvert
 jupyter_client
 ipykernel
+mock
 
 # Examples
 world_bank_data


Test patch:
diff --git a/tests/test_sunburst.py b/tests/test_sunburst.py
index e90fe43..b819cc3 100644
--- a/tests/test_sunburst.py
+++ b/tests/test_sunburst.py
@@ -1,5 +1,10 @@
 import sys
 import pytest
+
+try:
+    import unittest.mock as mock
+except ImportError:
+    import mock
 import pandas as pd
 import plotly.graph_objects as go
 from easyplotly import Sunburst
@@ -93,3 +98,16 @@ def test_sunburst_index_none_is_removed():
 def test_negative_raise_error():
     with pytest.raises(ValueError, match='Negative'):
         Sunburst({('A', 'a'): -5})
+
+
+def test_parent_value_strictly_larger():
+    with mock.patch('easyplotly.internals.EPS', 0.01):
+        sunburst_input = {('A', 'a', '1', 'i'): 1.0}
+        sunburst_expected = go.Sunburst(
+            ids=['/A/a/1/i', '/A/a/1', '/A/a', '/A'],
+            labels=['i', '1', 'a', 'A'],
+            parents=['/A/a/1', '/A/a', '/A', None],
+            values=[1., 1.01, 1.02, 1.03],
+            branchvalues='total'
+        )
+        assert Sunburst(sunburst_input) == sunburst_expected