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emmanuelle · emmanuelle · commit 21882a5363fd · 2019-11-13T16:17:33.000-05:00
diff --git a/python/histograms.md b/python/histograms.md
@@ -34,9 +34,13 @@ jupyter:
     thumbnail: thumbnail/histogram.jpg
 ---
 
+In statistics, a [histogram](https://en.wikipedia.org/wiki/Histogram) is representation of the distribution of numerical data, where the data are binned and the count for each bin is represented. More generally, in plotly a histogram is an aggregated bar chart, with several possible aggregation functions (e.g. sum, average, count...). Also, the data to be binned can be numerical data but also categorical or date data.
+
+If you're looking instead for bar charts, i.e. representing data with rectangular
+bar, go to the [Bar Chart tutorial](/python/bar-charts/).
+
 ## Histogram with Plotly Express
 
-In statistics, a [histogram](https://en.wikipedia.org/wiki/Histogram) is representation of the distribution of numerical data, where the data are binned and the count for each bin is represented. More generally, in plotly a histogram is an aggregated bar chart, with several possible aggregation functions (e.g. sum, average, count...). Also, the data to be binned can be numerical data but also categorical or date data.
 
 [Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/).
 
diff --git a/python/pie-charts.md b/python/pie-charts.md
@@ -35,7 +35,10 @@ jupyter:
 
 ### Basic Pie Chart ###
 
-A pie chart ``go.Pie`` object is a circular statistical chart, which is divided into sectors to illustrate numerical proportion. Data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors`.
+A pie chart ``go.Pie`` object is a circular statistical chart, which is divided into sectors to illustrate numerical proportion. Data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors`. 
+
+If you're looking instead for a multilevel hierarchical pie-like chart, go to the
+[Sunburst tutorial](/python/sunburst-charts/).
 
 ```python
 import plotly.graph_objects as go
