![]() ![]() Then I brought in the data with: \copy hlc_cmyk from '/home/gregp/HLC_Atlas_CMYK_SampleData.csv' with (header, format CSV) My first step was to create the database with: Create table hlc_cmyk (color varchar(40), c decimal, m decimal, y decimal, k decimal) Fortunately, PostgreSQL has a command for this. I did not want to enter all of this data manually-I don't think I could without errors (and headaches). This is where PostgreSQL comes into play. The file consisted of 1,793 colors, and I wanted a way to analyze the information to get a sense of the range of values. In each line, the first item is the color name, and it's followed by its C, M, Y, and K color values. (CSV files are also very useful because they can be imported easily into a spreadsheet program.) I transformed it into a CSV (comma-separated value) file, which I prefer to use with Python. This is slightly modified from the original, which separated the data with tabs. Type commands like the following to add items to your list: Create a simple shopping listįirst, enter the database with the psql command, then create a table for your list with: Create table groc (item varchar(20), comment varchar(10)) ![]() Instead, with PostgreSQL, I can enter bits when I think of them as the week goes on and print out the whole thing right before I go shopping. ![]() So, I had to wait to make my list all at once, and by then I usually forgot some items we need or I want. Initially, I made an HTML form page to manage my shopping list, but it couldn't save my entries. I go to several places to buy the things on my list because each store offers a particular selection or quality or maybe a better price. I do most of the grocery shopping in our home, and the bulk of it happens once a week. Free online course: RHEL technical overviewįor example, I use Postgres to keep track of my grocery shopping list. ![]()
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