Parse NMEA Sentences with Python Pandas
Turns this
$GPGGA,094814.40,5104.6852091,N,01345.1067321,E,5,15,0.95,130.7952,M,43.8438,M,1.4,0548*7F
$GNGST,094814.40,1.194,0.250,0.027,145.728,0.208,0.143,1.167*42
$GPGGA,094814.50,5104.6852077,N,01345.1067351,E,5,15,0.95,130.7811,M,43.8438,M,1.5,0548*76
$GNGST,094814.50,1.198,0.251,0.027,145.728,0.208,0.143,1.171*49
$GPGGA,094814.60,5104.6852059,N,01345.1067367,E,5,15,0.95,130.7693,M,43.8438,M,1.6,0548*7B
$GNGST,094814.60,1.201,0.252,0.028,145.728,0.209,0.144,1.174*46
$GPGGA,094814.70,5104.6852050,N,01345.1067398,E,5,15,0.95,130.7682,M,43.8438,M,0.7,0548*73
$GNGST,094814.70,1.165,0.244,0.027,145.737,0.203,0.139,1.138*48
into this
and with the help of heatmap and OSMViz to this
Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under CC BY SA.
as well as the RMS Position Error, depending on the Location:
