extracting latitude from a string

[arunaskuciauskas]

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[arunaskuciauskas]

Hi: I am trying to extract the latitude from hundreds of files that contain the following listing:

%TITLE%
STC 190313/034000 -0.1,-27.46

       LEVEL       HGHT       TEMP       DWPT       WDIR       WSPD
-------------------------------------------------------------------
%RAW%
     1011.44,      0.00,     30.37,     24.46,      9.60,      0.01
      986.07,    227.06,     27.65,     22.99,      9.50,      0.01
      958.59,    477.68,     25.43,     21.13,      9.40,      0.01
      931.52,    730.00,     23.50,     19.20,      9.30,      0.01

I perform the following read:
df = pd.read_csv(fn, sep ='s,', skiprows=0, nrows = 1)

resulting in output:

%TITLE%
0  STC 190313/034000 -0.36,-25.61

where the latitude is -0.36, my intended value. In reading multiple files, the latitude value in the files can vary
in format from 0.0 (2 char), to -25.67 (6 char)

I applied a split on the '/' as:

    coord = df.iloc[0,0]
    print('Coord ',coord)

resulting in output:

Coord:  STC 190313/034000 -0.36,-25.61

lat = coord.split('/')
lati = lat[1][7:12]
print('lati: ', lati)

resulting in output:
lati: -0.1,

The start of the latitude value always starts in the 7th position
Question: How can I make sure that I grab the entire latitude value?

[dopplershift]

Apologies for the delayed response. I wouldn't use parse_csv to handle any of that header, only the later data. This is what I wrote to parse what you provided:

with open(fn, 'rt') as infile:
    # skip "%TITLE%
    infile.readline()

    # Get the siteid, date string, and lat/lon group by splitting on whitespace
    site, date, latlon = infile.readline().split()

    # Split the lat/lon group on a comma and convert to floats
    lat, lon = map(float, latlon.split(','))

    # Skip blank
    infile.readline()

    # Get the column names from the names that *don't* have commas
    columns = infile.readline().split()

    # Let pandas parse the rest of the file
    df = pd.read_csv(infile, skiprows=2, names=columns)