i = 2
time = []
day_night = []
water = []
hills = []
m = []
lat = []
lon = []
while i < len(dane1):
time.append (parser.parse (dane1[i][1]))
day_night.append (float (dane1[i][8]))
water.append (float (dane1[i][9]))
hills.append (float(dane1[i][10]))
m.append (float (dane1[i][7]))
lat.append (to_coord(dane1[i][2]))
lon.append (to_coord(dane1[i][3]))
i+=3
suntime = [parser.parse (data[0]) for data in dane2]
sunm = [float (data [4]) for data in dane2]
#print (sunm)
#time = [parser.parse (data[1]) for data in dane1] # [..,'2021-04-...','fdsfdsf'] => [2021-04-16...]
#lat = [to_coord(data[2]) for data in dane1]
#print(lat)
#lon = [to_coord(data[3]) for data in dane1]
#day_night = [print (len(data[8])) for data in dane1]
#water = [float (data [9]) for data in dane1]
#hills = [float (data [10]) for data in dane1]
#x = [float (cases[4]) for cases in dane2]
#y = [float (cases[5]) for cases in dane2]
from csv import reader
from dateutil import parser
from matplotlib import pyplot
from latconv import to_coord
with open("all_photos_classified.csv", 'r') as f:
dane1 = list(reader(f))[1:]
#dane2 = [data[0].split(',') for data in dane1]
#print(dane1[1:5])
time = [parser.parse(data[1]) for data in dane1
] # [..,'2021-04-...','fdsfdsf'] => [2021-04-16...]
lat = [to_coord(data[2]) for data in dane1]
#print(lat)
lon = [to_coord(data[3]) for data in dane1]
#x = [float (cases[4]) for cases in dane2]
#y = [float (cases[5]) for cases in dane2]
#z = [float (cases[6]) for cases in dane2]
m = [float(cases[7]) for cases in dane1]
#m2 = [float(data[7] +float(data[2].split(':')[0]) ) for data in dane2]
fig, ax = pyplot.subplots(3) # ax = axis
#fig, ax = pyplot.subplots(2) # ax = [axis0, axis2]
#ax.plot(time, x, label='x')#m2 = m-(lon*0.1)
#ax.plot(time, y, label='y')
#ax.plot(time, z, label='z')
#ax[0].plot(time, m, label='m')
#ax[0].plot(time, lon, label='lon')#lon wygląda tak -107:07:22.5
#ax[0].plot(time, lat, label='lat')
#ax[0].set_xlabel('x label') # Add an x-label to the axes.