Update notebooks/v2/Analyzing_Census_Data_with_Data_Commons.ipynb

Co-authored-by: Christie Ellks <[email protected]>

Author: kmoscoe

notebooks/v2/Analyzing_Census_Data_with_Data_Commons.ipynb

@@ -49,7 +49,7 @@
         "\n",
         "The [Python API](https://github.com/datacommonsorg/api-python/tree/master/datacommons_client) provides functions for users to extract structured information from Data Commons programmatically and view them in different formats such as Python `dict`s and [pandas](https://pandas.pydata.org/) DataFrames. DataFrames allow access to all the data processing, analytical and visualization tools provided by packages such as pandas, NumPy, SciPy, and Matplotlib.\n",
         "\n",
-        "Note: Before you can use the API, you must obtain a Data Commons API key. Please see [Obtain an API key](https://docs.datacommons.org/api/#obtain-an-api-key] for details. In this Colab, we'll use a trial key. You may use it for a limited number of requests, but you will need to get your own key for longer use.\n",
+        "Note: Before you can use the API, you must obtain a Data Commons API key. Please see [Obtain an API key](https://docs.datacommons.org/api/#obtain-an-api-key) for details. In this Colab, we'll use a trial key. You may use it for a limited number of requests, but you will need to get your own key for longer use.\n",
         "\n",
         "Let's begin by loading the Data Commons Python API and the standard data science libraries:"
       ]