someone wrote:
> ....
> I want to put this table into an appropriate container
> such that afterwards I want to:
>
> 1) Put the data into a mySql-table
> 2) Be able to easily plot column 1 vs. either of the other columns
> using matplotlib etc...
> ....
Consider editing your data file
into a csv file named someone.csv ....
20130315T071500,39000.,10,26,48000.,1,40
20130315T071501,39000.,10,26,48000.,2,42
20130315T071501,39000.,10,26,47520.,15,69
20130315T071501,39000.,10,26,47160.,1,70
20130315T071501,39000.,10,26,47000.,1,72
20130315T071501,39000.,10,26,47000.,2,81
20130315T071501,39000.,10,26,47000.,6,85
20130315T071501,39000.,10,26,46520.,10,95
20130315T071501,43000.,10,36,46520.,10,95
20130315T071501,43200.,4,43,46520.,10,104
20130315T071501,44040.,1,45,46520.,10,108
20130315T071501,44080.,3,48,46520.,10,109
20130315T071501,44080.,3,48,46520.,11,113
20130315T071501,44080.,3,48,46400.,2,131
20130315T071501,45080.,1,51,46400.,2,145
20130315T071501,45080.,1,51,46200.,1,147
20130315T071501,45080.,1,60,46120.,1,182
20130315T071501,45520.,1,65,46120.,1,225
20130315T071501,45520.,1,73,46120.,2,247
20130315T080000,45760.,1,133,46120.,2,378
20130315T080241,45760.,2,199,46120.,2,453
20130315T080945,45760.,3,217,46120.,2,456
20130315T081103,45760.,3,217,46080.,1,457
20130315T081105,45760.,3,218,46080.,2,458
20130315T081106,45760.,4,222,46080.,2,458
20130315T081107,45800.,1,229,46080.,2,458
20130315T082754,45800.,8,266,46080.,2,514
# -----------------------------------------------
#
# The csv data can be loaded using the csv module
#
# named tuples might be used
# for convenience to access
# individual columns
#!/usr/bin/env python
import csv
from collections import namedtuple as NT
file_source = open( 'someone.ssv' )
# -------------------> individual column names ---------------
nt = NT( 'csv_data' , 'date time col1 col2 col3 col4 col5 col6' )
list_tuples = [ ]
for this_row in csv.reader( file_source ) :
# unpack the current row
zed , one , two , tre , fur , fiv , six = this_row
# split the date and time
d , t = zed.split( 'T' )
# convert individual columns in row to a named tuple
this_tuple = nt( d ,
t ,
float( one ) ,
int( two ) ,
int( tre ) ,
float( fur ) ,
int( fiv ) ,
int( six ) )
# save the current named tuple into a list
list_tuples.append( this_tuple )
# update_data_base( this_tuple )
# .... or ....
# update_data_base( choose individual columns )
# individual elements of the named tuples
# can be accessed by name
#
# this might be convenient for settup up
# data for plots of diffeent columns
print
for row in list_tuples :
print ' ' , row.date , row.time , row.col1 , row.col3 , row.col4
file_source.close()
--
Stanley C. Kitching
Human Being
Phoenix, Arizona
--
http://mail.python.org/mailman/listinfo/python-list
