Minor Fixes.

Author: aouinizied

docs/design.md

@@ -91,7 +91,7 @@ each time a new NFPacket is mapped to the flow entry. Finally, on_expire is perf
 expired. Consequently, extending NFStream is simple. Adding new flow features or ML model outcomes can be achieved 
 in just a few lines.
 
-## Socket collector
+## Socket Collector
 Socket collector probes the Operating System logs to construct a view of the active connections table.
 It is only activated when system visibility mode is set for end-host ground truth generation. The collector detects 
 creation and closing of connections and send these state updates to the streamer.

index.html

@@ -1,5 +1,5 @@
 ---
-title: NFStream - a Flexible Network Data Analysis Framework.
+title: NFStream - a Flexible Network Flow Data Analysis Framework.
 layout: generic-page
 nav_exclude: true
 ---
@@ -8,8 +8,8 @@
   <header class="lp-header">
     <meta name="image" property="og:image" content="https://www.nfstream.org/resources/preview.png">
     <div class="lp-center">
-      <h1 style="font-weight: bold">NFStream: Flexible Network Data Analysis Framework</h1>
-      <h2 style="padding-bottom: 30px">a multiplatform Python framework providing fast, flexible, and expressive data structures designed to make working with online or offline network data easy and intuitive.</h2>
+      <h1 style="font-weight: bold">NFStream: Flexible Network Flow Data Analysis Framework</h1>
+      <h2 style="padding-bottom: 30px">NFStream is a multiplatform Python framework providing fast, flexible, and expressive data structures designed to make working with network flow data easy and intuitive.</h2>
       <a href="https://mybinder.org/v2/gh/aouinizied/nfstream-tutorials/master?filepath=demo_notebook.ipynb" class="btn btn-blue fs-5 mb-3 mb-md-5 mr-5">Live Notebook</a>
       <a href="{{ site.baseurl }}/docs/" class="btn btn-blue fs-5 mb-3 mb-md-5">Get Started</a>
     </div>
@@ -50,8 +50,8 @@ <h2>Network Flow aggregation and statistical features extraction</h2>
                               splt_analysis=10)
 
 df = offline_streamer.to_pandas(columns_to_anonymize=())
-total_flows = offline_streamer.to_csv(flows_per_file=10000,
-                                      columns_to_anonymize=())
+n_flows = offline_streamer.to_csv(flows_per_file=10000,
+                                  columns_to_anonymize=())
 
 {% endhighlight %}
       </div>