如何使用python读取nmea文件

Question

我尝试读取由GPS记录器编写的nmea文件。我只能找到很多关于串行连接的解决方案，但我已经写好了完整的文件。

有没有办法读取nmea文件并获取pandas DataFrame？

Answer 1

您可以使用以下代码将nmea文件转换为csv：

https://gis.stackexchange.com/questions/180523/nmea-to-csv-with-timestamp-using-gpsbabel

import csv
from datetime import datetime
import math

# adapt this to your file
INPUT_FILENAME = 'in.nmea'
OUTPUT_FILENAME = 'out.csv'

# open the input file in read mode
with open(INPUT_FILENAME, 'r') as input_file:

    # open the output file in write mode
    with open(OUTPUT_FILENAME, 'wt') as output_file:

        # create a csv reader object from the input file (nmea files are basically csv)
        reader = csv.reader(input_file)

        # create a csv writer object for the output file
        writer = csv.writer(output_file, delimiter=',', lineterminator='\n')

        # write the header line to the csv file
        writer.writerow(['date_and_time', 'lat', 'lon', 'speed'])

        # iterate over all the rows in the nmea file
        for row in reader:

            # skip all lines that do not start with $GPRMC
            if not row[0].startswith('$GPRMC'):
                continue

            else:

                # for each row, fetch the values from the row's columns
                # columns that are not used contain technical GPS stuff that you are probably not interested in
                time = row[1]
                warning = row[2]
                lat = row[3]
                lat_direction = row[4]
                lon = row[5]
                lon_direction = row[6]
                speed = row[7]
                date =  row[9]

                # if the "warning" value is "V" (void), you may want to skip it since this is an indicator for an incomplete data row)
                if warning == 'V':
                    continue

                # merge the time and date columns into one Python datetime object (usually more convenient than having both separately)
                date_and_time = datetime.strptime(date + ' ' + time, '%d%m%y %H%M%S.%f')

                # convert the Python datetime into your preferred string format, see http://www.tutorialspoint.com/python/time_strftime.htm for futher possibilities
                date_and_time = date_and_time.strftime('%y-%m-%d %H:%M:%S.%f')[:-3] # [:-3] cuts off the last three characters (trailing zeros from the fractional seconds)

                # lat and lon values in the $GPRMC nmea sentences come in an rather uncommon format. for convenience, convert them into the commonly used decimal degree format which most applications can read.
                # the "high level" formula for conversion is: DDMM.MMMMM => DD + (YY.ZZZZ / 60), multiplicated with (-1) if direction is either South or West
                # the following reflects this formula in mathematical terms.
                # lat and lon have to be converted from string to float in order to do calculations with them.
                # you probably want the values rounded to 6 digits after the point for better readability.
                lat = round(math.floor(float(lat) / 100) + (float(lat) % 100) / 60, 6)
                if lat_direction == 'S':
                    lat = lat * -1

                lon = round(math.floor(float(lon) / 100) + (float(lon) % 100) / 60, 6)
                if lon_direction == 'W':
                    lon = lon * -1

                # speed is given in knots, you'll probably rather want it in km/h and rounded to full integer values.
                # speed has to be converted from string to float first in order to do calculations with it.
                # conversion to int is to get rid of the tailing ".0".
                speed = int(round(float(speed) * 1.852, 0))

                # write the calculated/formatted values of the row that we just read into the csv file
                writer.writerow([date_and_time, lat, lon, speed])

然后和熊猫一起打开csv

import pandas as pd 

data = pd.read_csv("out.csv")