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Showing posts from October, 2021

SQL : PostgreSQL

  Aggregate Functions Like most other relational database products,  PostgreSQL  supports  aggregate functions . An aggregate function computes a single result from multiple input rows. For example, there are aggregates to compute the  count ,  sum ,  avg  (average),  max  (maximum) and  min  (minimum) over a set of rows. As an example, we can find the highest low-temperature reading anywhere with: SELECT max(temp_lo) FROM weather; max ----- 46 (1 row) If we wanted to know what city (or cities) that reading occurred in, we might try: SELECT city FROM weather WHERE temp_lo = max(temp_lo); WRONG but this will not work since the aggregate  max  cannot be used in the  WHERE  clause. (This restriction exists because the  WHERE  clause determines which rows will be included in the aggregate calculation; so obviously it has to be evaluated before aggregate functions are computed.) However, as is o...
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Public datasets

  Exploring public datasets Open data helps create a lot of public datasets that you can access to make data-driven decisions. Here are some resources you can use to start searching for public datasets on your own: The Google Cloud Public Datasets allow data analysts access to high-demand public datasets, and make it easy to uncover insights in the cloud.  The Dataset Search can help you find available datasets online with keyword searches.  Kaggle has an Open Data search function that can help you find datasets to practice with. Finally, BigQuery hosts 150+ public datasets you can access and use.  Public health datasets Global Health Observatory data : You can search for datasets from this page or explore featured data collections from the World Health Organization.   The Cancer Imaging Archive (TCIA) dataset : Just like the earlier dataset, this data is hosted by the Google Cloud Public Datasets and can be uploaded to BigQuery. 1000 Genomes : This i...
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HOW TO R markdown

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  This is like a summary how to start to finish the R markdown notebook (RMD.file) Great! VDO https://d18ky98rnyall9.cloudfront.net/4SLdrqlNSAui3a6pTagLwA.processed/full/540p/index.webm?Expires=1635033600&Signature=CS83vA0qHrpNjPEUgCKTAVjOFFdm7eyjZdLmSxRgsUm3rj5~poqQPizOwDAxnBkTmv10ehDqXJ2rOAWPPwBNX5ZGxTdV~cE81VSR0lmvn2XPsBoHVqA5tAJlc2qI0P98IkA4C9EsKqZ0zUcrkD6RqOWEhWjYIkONHKM4nkZHA~4_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A Overview Earlier in this course, you created a visualization using the ggplot() function. You also learned how to create an R Markdown notebook. In this activity, you will combine and apply your knowledge by adding the code you used to create a visualization to a RMarkdown notebook. By the time you complete this activity, you will be able to make and format an .rmd file containing the visualizations you created using ggplot2. This will allow you to track and share analysis and also share the R code you use to create visualizations. This will prove useful if you...
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R markdown - Jupyter Notebook

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  R Markdown resources R Markdown is a useful tool that allows you to save and execute code, and generate shareable reports for stakeholders. As you learn more about how to use it, it can be helpful to bookmark some resources to refer to later. This reading explores some great online resources that will help you learn more about R Markdown and how to use it to document your analysis.  R Markdown documentation RStudio's R Markdown documentation includes a series of tutorials that will help you learn about the main features of R Markdown, including code chunks, output formats, notebooks, interactive documents, and more. The tutorials include online lessons that you can complete directly in your RStudio Cloud workspace.  R Markdown reference materials RStudio has developed a reference guide and a cheat sheet that you can bookmark and use whenever you practice writing R Markdown files.   T​he R Markdown Reference Guide contains three sections: Markdown syntax, kn...
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