The First Use Case
Learn how to use SQL in the application code for Python.
We'll cover the following
The Intercontinental Exchange provides a chart with daily NYSE group volumes. We can fetch the Excel file, which is a CSV file that uses tab spacing as a separator, remove the headings, and load it into a PostgreSQL table.
Loading the data set
Here’s what the data looks like with comma-separated thousands and dollar signs, so we can’t readily process the figures as numbers:
2010 1/4/2010 1,425,504,460 4,628,115 $38,495,460,645
2010 1/5/2010 1,754,011,750 5,394,016 $43,932,043,406
2010 1/6/2010 1,655,507,953 5,494,460 $43,816,749,660
2010 1/7/2010 1,797,810,789 5,674,297 $44,104,237,184
We create an ad-hoc table definition, and once the data is loaded, we then transform it into a proper SQL data type, with the help of the alter table
command.
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