Creating graphs using data form .csv file
Yesterday I was talking to a friend and he told me that he has some work that he needs to complete by the following night. He asked me for the help and I decided to help as my exam was postponed. He said that he had a .csv file( comma separated values) and want to shift the whole data into postgresql database.
I told him that I will like to help him and ask him to send me the files. First task was to install postgresql.
$ sudo apt-get install postgresql postgresql-contrib
Now use the following command to start postgresql terminal and start typing postgresql commands which are somewhat similar to MySQL.
$ sudo -u postgres psql postgres
After this a terminal will open up where you put all your commands. If this does not work use the following command.
$ sudo /etc/init.d/postgresql restart
Now use the earlier command again and it will definitely work.
After this I created a table in postgresql using simple create table command.
Now to copy the data of .csv file into postgresql table use the following command.
postgres=# `COPY zip_codes FROM '/path/to/csv/ZIP_CODES.txt' DELIMITER ',' CSV HEADER;`
Now you can use the command like select * from table_name; and watch the table on your screen populated with the new data.
Here is the link for creating graphs from the input of .csv file.
Now as the .csv file had many comma separated values my friend went forward and asked me to create a script that can create different files with the required data for this I told him that it will require some time. I came back to my room and started making a python script that can keep two comma separated values in each file.
Here is the part that created the first file.
target = open("stat3112.csv", 'r+') temp1 = 0 for line in target: index = line.find(",") resttext = line[index + 1:] print resttext index_rest_text = resttext.find(",") net_index = index + index_rest_text + 1 newfile = "file" + str(temp1) + ".csv" files = open(newfile, 'a') print index_rest_text files.write(line[:net_index] + "\n") files.close() target.close()
Therefore, The task was completed.