import numpy as np                         # NumPy is an array and math library
import matplotlib.pyplot as plt            # Matplotlib is a visualization (plotting) library
import pandas as pd                        # Pandas lets us work with spreadsheet (.csv) data
from datetime import datetime, timedelta   # Datetime helps us work with dates and times

filepath_0 = '/content/2023051001001_Carkeek.csv'
filepath_1 = '/content/2023051101001_Carkeek.csv'

data_0 = pd.read_csv(filepath_0,comment='#')
data_1 = pd.read_csv(filepath_1,comment='#')

display(data_0)

# For example:
data_0['density00']

# Temperature vs. depth profile
plt.plot(data_0['t090C'],data_0['depSM'],label='R/V Carson cast #1 (5/10/23)')
plt.plot(data_1['t090C'],data_1['depSM'],label='R/V Carson cast #2 (5/11/23)')
plt.legend()
plt.gca().invert_yaxis()   # This reverses the y-axis
plt.xlabel('Temperature (°C)')
plt.ylabel('Depth (m)');

# Write your code here:


filepath_2 = '/content/20230512_glider.csv'

data_2 = pd.read_csv(filepath_2,parse_dates=['time'])

display(data_2)

plt.plot(data_0['longitude'],data_0['latitude'],label='R/V Rachel Carson cast #1')
plt.plot(data_1['longitude'],data_1['latitude'],label='R/V Rachel Carson cast #2')
plt.plot(data_2['longitude'],data_2['latitude'],label='Glider')
plt.legend()
plt.xlabel('Longitude (°E)')
plt.ylabel('Latitude (°N)')
plt.title('Ship and glider tracks');

plt.scatter(data_2['time'],data_2['depth'],c=data_2['buoyancy'])
plt.colorbar(label='Buoyancy (g)')   # This adds the color bar and color label on the right
plt.gca().invert_yaxis()             # This reverses the y-axis
plt.xlabel('Time')
plt.ylabel('Depth (m)');

# Write your code here: