Maksym Kozlenko maxim75

## exif.html
<!DOCTYPE html>
<html lang="en">
	<head>
		<title>h5</title>
		<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.6.1/jquery.js"></script>
		<script src="exif.js"></script>
		<style>
			#holder { border: 1px dashed #ccc; width: 100px; height: 100px; margin: 20px auto;}
			#holder.hover { border: 1px dashed #333; }
			#result .property { width: 100px; }

## gps_map.py
import matplotlib.pyplot as plt
import contextily as ctx

fig = plt.figure(figsize=(20,20))
ax = plt.axes()
gdf[gdf.gps_qual > 0].plot(ax=ax, alpha=.2, edgecolor="#ffff", color='red')
ctx.add_basemap(ax, source=ctx.providers.Stamen.TonerLite, crs="EPSG:4326", alpha=.3)

## create_geo_data_frame.py
import pandas as pd
import geopandas as gpd

df = pd.DataFrame(coordinates_data)
gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.longitude, df.latitude, crs="EPSG:4326"))
gdf

## extract_coord_data.py
import pynmea2

nmea_data = open("data/gps_data_20220215-070028.nmea", "rb")

coordinates_data = []

for message_bytes in nmea_data.readlines():
    try:
        message = message_bytes.decode("utf-8").replace("\n", "").replace("\r", "")
        parsed_message = pynmea2.parse(message)

## pynmea.py
import pynmea2

nmea_data = open("data/gps_data_20220215-070028.nmea", "rb")
for message_bytes in nmea_data.readlines()[:10]: # read first 10 messages from file
    try:
        message = message_bytes.decode("utf-8").replace("\n", "").replace("\r", "")
        parsed_message = pynmea2.parse(message)
    except:
        # skip invalid messages
        continue

## save_nmea_data.py
import serial
import datetime

ser = serial.Serial("/dev/cu.usbserial-0001", baudrate=9600)
ser.flushInput()
ser.flushOutput()
idx = 0

nmea_data = b""

## gist:1026623

<!-- http://webdeveloperplus.com/jquery/create-a-dynamic-scrolling-content-box-using-ajax/#respond -->


<!DOCTYPE html>
<html>
	<head>
		<style>
			#container{
				width:400px;

## gist:1000135
<!DOCTYPE html>
<html>
	<head>
		<style>
			#map_canvas
			{
				width: 400px;
				height: 400px;
			}
		</style>

## gist:1037392
<!DOCTYPE html>
<html>
	<head>
		<style>

		</style>

		<!-- JQuery -->
		<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.6.1/jquery.min.js">
		</script>

## xml.html
<!DOCTYPE html>
<html>
	<head>
		<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.6.1/jquery.min.js"></script>
		<style>

		</style>
		<script>
				function loadFile() {
        var input, file, fr;
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<title>h5</title>
	<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.6.1/jquery.js"></script>
	<script src="exif.js"></script>
	<style>
	#holder { border: 1px dashed #ccc; width: 100px; height: 100px; margin: 20px auto;}
	#holder.hover { border: 1px dashed #333; }
	#result .property { width: 100px; }
	import matplotlib.pyplot as plt
	import contextily as ctx

	fig = plt.figure(figsize=(20,20))
	ax = plt.axes()
	gdf[gdf.gps_qual > 0].plot(ax=ax, alpha=.2, edgecolor="#ffff", color='red')
	ctx.add_basemap(ax, source=ctx.providers.Stamen.TonerLite, crs="EPSG:4326", alpha=.3)
	import pandas as pd
	import geopandas as gpd

	df = pd.DataFrame(coordinates_data)
	gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.longitude, df.latitude, crs="EPSG:4326"))
	gdf
	import pynmea2

	nmea_data = open("data/gps_data_20220215-070028.nmea", "rb")

	coordinates_data = []

	for message_bytes in nmea_data.readlines():
	try:
	message = message_bytes.decode("utf-8").replace("\n", "").replace("\r", "")
	parsed_message = pynmea2.parse(message)
	import serial
	import datetime

	ser = serial.Serial("/dev/cu.usbserial-0001", baudrate=9600)
	ser.flushInput()
	ser.flushOutput()
	idx = 0

	nmea_data = b""

	<!-- http://webdeveloperplus.com/jquery/create-a-dynamic-scrolling-content-box-using-ajax/#respond -->


	<!DOCTYPE html>
	<html>
	<head>
	<style>
	#container{
	width:400px;