#!/usr/bin/env python
# coding: utf-8

# In[1]:


import pandas as pd

# Download and prepare the data.
climate = pd.read_csv('climate_data.csv')
climate['Average temperature (°C)'] = (climate['Average temperature (°F)']-32)/1.800
climate['Year'] = climate['Date'].str[:4]
climate = climate[climate['Year']=='2020']

shrimps = pd.read_csv('shrimp-prices.csv')
shrimps['Year'] = shrimps['Month'].str[-4:]
shrimps = shrimps.groupby(['Year']).mean().reset_index(drop=False)

population = pd.read_csv('population_by_country_2020.csv')
population = population.sort_values(['Density (P/Km²)'], ascending=False)[:10]


import toyplot
x = climate['Average temperature (°C)']
y = climate['Average humidity (%)']
canvas = toyplot.Canvas(width=500, height=350)
axes = canvas.cartesian()
mark = axes.scatterplot(x, y)


# ### *Fig. 1*
# ***

# In[2]:


canvas, axes, mark = toyplot.scatterplot(x, y, width=500, height=350,
                                         label='Temperature vs. Humidity (Estes Park, 2020)',
                                         xlabel='Temperature, °C', 
                                         ylabel='Humidity, %',
                                         size=10, opacity=0.4,
                                         color='slateblue', marker='s')
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15


# ### *Fig. 2*
# ***

# In[3]:


y1 = climate['Average humidity (%)']
y2 = climate['Minimum humidity (%)']
canvas = toyplot.Canvas(width=500, height=350)
axes = canvas.cartesian(label='Temperature vs. Humidity (Estes Park, 2020)', 
                        xlabel='Temperature, °C',
                        ylabel='Humidity, %')
mark = axes.scatterplot(x, y1, 
                        size=10, opacity=0.4, 
                        title='Average humidity')
mark = axes.scatterplot(x, y2, 
                        size=10, opacity=0.4, 
                        title='Minimum humidity')
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15


# ### *Fig. 3*
# ***

# In[4]:


canvas = toyplot.Canvas(width=600, height=300)

axes = canvas.cartesian(grid=(1,2,0),
                        label='Temperature vs. Average humidity', 
                        xlabel='Temperature, °C',
                        ylabel='Average humidity, %', 
                        ymin=0, ymax=100)
mark = axes.scatterplot(x, y1, size=10, opacity=0.4)
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15

axes = canvas.cartesian(grid=(1,2,1),
                        label='Temperature vs. Minimum humidity', 
                        xlabel='Temperature, °C',
                        ylabel='Minimum humidity, %', 
                        ymin=0, ymax=100)
mark = axes.scatterplot(x, y2, size=10, opacity=0.4)
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15


# ### *Fig. 4*
# ***

# In[5]:


x = shrimps['Year']
y = shrimps['Price']
canvas, axes, mark = toyplot.plot(x, y, width=550, height=350,
                                  label='Shrimp prices by year',
                                  xlabel='Year',
                                  ylabel='Price, USD/kg')
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15


# ### *Fig. 5*
# ***

# In[6]:


canvas, axes, mark = toyplot.plot(x, y, width=550, height=350,
                                  label='Shrimp prices by year',
                                  xlabel='Year', 
                                  ylabel='Price, USD/kg',
                                  style={'stroke':'dodgerblue', 
                                         'stroke-dasharray':'5',
                                         'stroke-width':'4'})
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 15


# ### *Fig. 6*
# ***

# In[7]:


heights = population['Density (P/Km²)']
canvas, axes, mark = toyplot.bars(heights, width=550, height=350,
                                  label='TOP10 countries by population density in 2020',
                                  xlabel='Countries', 
                                  ylabel='Population density, P/km²')


# ### *Fig. 7*
# ***

# In[8]:


countries = list(population['Country (or dependency)'])
canvas, axes, mark = toyplot.bars(heights, width=500, height=350, 
                                  along='y',
                                  margin=(45,20,45,62), 
                                  label='TOP10 countries by population density in 2020', 
                                  xlabel='Population density, P/km²')
axes.y.ticks.locator = toyplot.locator.Explicit(labels=countries)
axes.y.ticks.labels.angle = 270
axes.y.ticks.labels.offset = 52
axes.y.spine.show = False


# ### *Fig. 8*