Skip to content

Latest commit

 

History

History
39 lines (26 loc) · 1.65 KB

README.md

File metadata and controls

39 lines (26 loc) · 1.65 KB
Raw

GSoC_Task

Task's Readme Page

The .dat files downloaded from the internet is processed using preProcess.py to generate a DST_DATA.csv file, which contains the data as per the format shown here alt text

Step - 1 =>

pip install mysql-connector pip install pandas

Step - 2 =>

  1. Run preProcess.py after modifying the location in which you have kept .dat file downloaded from github in this case or the internet from here dst webpage

Step - 3 =>

Code used to convert CSV file's data to a database table in mysql.

  1. mysql [username] [password] or mysql -p -u root

  2. Enter the following into mysql console from your local directory i.e., where DST_DATA.csv file is saved => CREATE TABLE dstdata (dat LONG not null,mont LONG not null,yea LONG,star VARCHAR(20),quicklook VARCHAR(20),inde VARCHAR(20),versio VARCHAR(20),basevalue VARCHAR(20),hourlyvalue VARCHAR(200), meanvalue VARCHAR(100));

  3. Follow up => load data local infile
    'DST_DATA.csv'
    INTO TABLE dstdata FIELDS TERMINATED BY ',' ENCLOSED BY '"' LINES TERMINATED BY '\n' (dat, mont, yea, star, quicklook, inde, versio, basevalue, hourlyvalue, meanvalue);

Step - 4 =>

  1. Run QueryDST.py file and enter the query you want to run, please take help from the internet if you are not familiar with MySQL database queries, the "Field in DB" column printed in output shows the name of the columns in table "dstdata" which will be used to do queries.

Result =>

alt text

Still some changes left to be done. Thank You.