import matplotlib.pyplot as plt
AUSTRALIAN_CITIES = [
"Sydney",
"Melbourne",
"Brisbane",
"Perth",
"Adelaide",
]
FOREIGN_CITIES = [
"Auckland", "Hong Kong", "Singapore", "Kuala Lumpur", "Tokyo"
]
if __name__ == "__main__":
# Load Data
combined = util.load_cdf("Visualization/international.nc")
# Setup the graph
fig, axes = plt.subplots(nrows=len(AUSTRALIAN_CITIES),
ncols=len(FOREIGN_CITIES))
plt.rcParams.update({"font.size": 14})
# Plot each incoming/outgoing pair
for xx, incoming in enumerate(AUSTRALIAN_CITIES):
for yy, outgoing in enumerate(FOREIGN_CITIES):
test = combined.sel(AustralianPort=incoming,
ForeignPort=outgoing)[["PaxIn", "PaxOut"]]
test.to_dataframe().plot(ax=axes[xx, yy], legend=False)
axes[xx, yy].legend(loc="upper right", fontsize=10)
import util
import numpy as np
import datetime
import matplotlib.pyplot as plt
import calendar
AUSTRALIAN_CITIES = ["SYD", "MEL", "BNE", "PER", "ADL", "DRW"]
if __name__ == "__main__":
combined = util.load_cdf("Visualization/domestic.nc")
years = [x for x in range(2004, 2020)]
months = [x for x in range(1, 13)]
# We need the format of the data to be in a 2D-array format
# Each column is a month, while each row is a year
data = [
np.zeros(shape=(len(years), len(months)))
for i in range(len(AUSTRALIAN_CITIES))
]
# Generate the dataset
# Each city gets one array
for i, city in enumerate(AUSTRALIAN_CITIES):
city_data_origin = combined.sel(Origin=city)
try:
city_data_destination = combined.sel(Destination=city)
for xx, year in enumerate(years):
for yy, month in enumerate(months):
date = datetime.datetime(year, month, 1)
monthly_total1 = city_data_origin.sel(Month=date).sum(
["Destination"])