Add and fix colab links in Notebooks directory README (#170)

Author: tjann

notebooks/README.md

@@ -6,10 +6,12 @@ each link to see a live colab version.
 
 Notebook | Description
 -------- | -----------
-[`analyzing_census_data.ipynb`](https://colab.research.google.com/drive/1qCPZZD0MPWx6CC34wFVJc_9B2-q0F-h_)           | A notebook that analyzes the relationship between population size and median age for each State, County, and City in the United States.
+[`analyzing_census_data.ipynb`](https://colab.research.google.com/drive/1wYohDirOgVxvmL0d-oJRWdD6AXfAX_w1)           | A notebook that analyzes the relationship between population size and median age for each State, County, and City in the United States.
 [`COVID_19_Feature_Exploration_Analysis_with_Data_Commons.ipynb`](https://colab.research.google.com/drive/1LLteGjXifwSsD-YsGwBnI-i96G777Q7j)   | A notebook that explores how COVID-19 cases trends differ across different counties, and examines hundreds of variables across dozens of sources to see which variables are potentially correlated with COVID-19 mortality rate.
-[`analyzing_income_distribution.ipynb`](https://colab.research.google.com/drive/1uZtHeQ5FJoKPdjYjaHnIPXcAe0nKLcKO)   | A notebook that plots the distribution of income using statistics provided by the 2017 [American Community Survey](https://www.census.gov/programs-surveys/acs). The final result is a histogram charting the number of individuals in income brackets ranging from "0 to 10,000USD" up to "Above 200,000USD".
-[`analyzing_obesity_prevalence.ipynb`](https://colab.research.google.com/drive/1cawpFQzuoRcZX0H_kpbBvhBNZzGjBN8t)    | A notebook that analyzes the relationship between prevalence of obesity in 500 US Cities (as provided by the [CDC Wonder](https://wonder.cdc.gov/) dataset) to health and socio-economic indicators such as prevalence of high blood pressure and poverty rate.
+[`analyzing_income_distribution.ipynb`](https://colab.research.google.com/drive/1lyxb5gdD_YHKxNXLmD0poBU3G8bokWZ7)   | A notebook that plots the distribution of income using statistics provided by the 2017 [American Community Survey](https://www.census.gov/programs-surveys/acs). The final result is a histogram charting the number of individuals in income brackets ranging from "0 to 10,000USD" up to "Above 200,000USD".
+[`analyzing_obesity_prevalence.ipynb`](https://colab.research.google.com/drive/1_oZYWrrwO80DBaW0rIirTYHlfHCibXxY)    | A notebook that analyzes the relationship between prevalence of obesity in 500 US Cities (as provided by the [CDC Wonder](https://wonder.cdc.gov/) dataset) to health and socio-economic indicators such as prevalence of high blood pressure and poverty rate.
+[`Place Similarity with Data Commons.ipynb`](https://colab.research.google.com/drive/1t7dFDSpCT16QDkNuD933QgLUL9BOdCAS) | A notebook that identifies similar places given a place and one or more statistical variables from Data Commons.
+[`Missing Data Imputation Tutorial.ipynb`](https://colab.research.google.com/drive/1S_rMCyRsgygd8sV-r8aLRPcKwZPFcEGb) | A notebook that analyzes the different types of time series holes and different methods of imputing those holes.
 [`analyzing_genomic_data.ipynb`](https://colab.research.google.com/drive/1Io7EDr4LjfPLl_l2JYY8__WbfitfNlOf) | A notebook that analyzes genetic variants within RUNX1 (provided by multiple datasets from UCSC Genome Browser, NCBI/gene, and ClinVar).
 [`Drug_Discovery_With_Data_Commons.ipynb`](https://colab.research.google.com/drive/1dSKYiRMn3mbDsInorQzYM0yk7sqv6fIV) | A notebook performing drug discovery by identifying novel applications of previously approved drugs using Biomedical Data Commons.