In other words, keep columns 1 (climate station), 2 (date), and 4 (temperature recorded). Limit the number of columns by eliminating column 3 (since all the data is average temperature) and column 5 onward. The data has more information than you need. The head command is a utility for displaying the first several lines (by default, 10 lines) of a file. Here are the first few lines for TAVG_US_2010.csv: $ head TAVG_US_2010.csv Grep "TAVG" $csv_file | grep "^US" > TAVG_US_$csv_file # > TAVG_US_$csv_file: Save xtracted lines to file TAVG_US_$csv_file # grep "^US": From those extract lines that begin with text "US" # grep "TAVG" $csv_file: Extract lines in file with text "TAVG" # Example: 2010.csv extracted to TAVG_US_2010.csv # Message that says file name $csv_file is extracted to file TAVG_US_$csv_file # For each file with name that starts with "20" and ens with ".csv" Extract average temperaturesĮxtract the TAVG (average temperature) data from the CSVs for US regions: Use ls 20*.csv to list all your files with names beginning with 20 and ending with. The ls command lists the contents of a folder. Run this script to download, extract, and make 10 years' worth of data available as CSVs: $. Make sure you have gzip, a utility used for compression and decompression.If Wget is not installed on your system, download it. Wget is a utility for connecting to web servers from the command line.If you are behind a proxy server, consult Mark Grennan's how-to, and use:Įxport Make sure all standard commands are already in your PATH (such as /bin or /usr/bin).# For all years one by one starting from FROM_YEAR=2010 upto TO_YEAR=2019 # If not specified, a program to execute the script must be specified. # In this case, the script is executed by shell itself. It identifies the executor used to run this file. The comments in the code explain what the commands do: #!/bin/sh Use your favorite text editor to create a file named download.sh and paste in the code below. csv format and gzipped.ĭownload and unzip the data using a shell script. The data source is at, and the data is in. You will train your model using the last 10 complete years of data. The data for this tutorial comes from the US National Oceanic and Atmospheric Administration (NOAA). Now that your shell is set up, you can start preparing data for the machine learning temperature-prediction problem.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |