Criminalità Italia - Data Visualization

In [12]:

    

# Librerie
import os
import pandas as pd
import numpy as np
import folium
import matplotlib.pyplot as plt
plt.style.use('ggplot')
%pylab inline


    

    




Populating the interactive namespace from numpy and matplotlib






    




/Users/cesar/anaconda/lib/python3.6/site-packages/IPython/core/magics/pylab.py:161: UserWarning: pylab import has clobbered these variables: ['colors', 'text']
`%matplotlib` prevents importing * from pylab and numpy
  "\n`%matplotlib` prevents importing * from pylab and numpy"

In [13]:

    

# Cartelle Input/Output
dir_df = os.path.join(os.path.abspath(''),'stg')
dir_out = os.path.join(os.path.abspath(''),'output')


    

In [14]:

    

df_reg_filename = r'df_reg.pkl'
df_reg_fullpath = os.path.join(dir_df, df_reg_filename)
df_reg = pd.read_pickle(df_reg_fullpath)


    

In [4]:

    

df_reg.sum()


    

    
Out[4]:





Territorio    AbruzzoBasilicataCalabriaCampaniaEmilia-Romagn...
Value                                                       469
dtype: object

In [5]:

    

regioni_geo_filename = r'regioni.geojson'
regioni_geo = os.path.join(dir_df, regioni_geo_filename)

reg_map = folium.Map(location=[42, 12], zoom_start=5)
reg_map.choropleth(geo_path=regioni_geo, data=df_reg,
                  columns=['Territorio', 'Value'],
                  key_on='feature.properties.NOME_REG',
                  fill_color='YlOrRd')

reg_map.save(os.path.join(dir_out,r'omicidi_volontari.html'))
reg_map


    

    




/Users/cesar/anaconda/lib/python3.6/site-packages/ipykernel/__main__.py:8: FutureWarning: 'threshold_scale' default behavior has changed. Now you get a linear scale between the 'min' and the 'max' of your data. To get former behavior, use folium.utilities.split_six.






    
Out[5]:

In [15]:

    

# Top 3 Regioni
df_reg_top3=df_reg.sort_values(by='Value',ascending=False).head(3)
df_reg_top3.to_csv(os.path.join(dir_out,r'Top3_Regioni.csv'),header=True, index=False)
df_reg_top3


    

    
Out[15]:






  

    

      

      
Territorio
      
Value
    
  
  

    

      
22
      
Campania
      
67.0
    
    

      
59
      
Lombardia
      
67.0
    
    

      
53
      
Lazio
      
58.0
    
  

In [19]:

    

df_cit_top_filename = r'df_cit_top.pkl'
df_cit_top_fullpath = os.path.join(dir_df, df_cit_top_filename)
df_cit_top = pd.read_pickle(df_cit_top_fullpath)
# Report
style.use('fivethirtyeight')
# Colorblind-friendly colors
colors = [[213/255,94/255,0]]
tp = df_cit_top.plot(
        x=df_cit_top['Territorio'],
        kind='bar',
        legend = False,
        figsize = (6,4),
        color = colors)

for p in tp.patches:
    tp.annotate(str(round(p.get_height())), (p.get_x() * 1.005, p.get_height() * 1.005), ha='center', va='center', xytext=(10, 5), textcoords='offset points',fontsize=9)
    tp.plot()
    
tp.tick_params(axis = 'both', which = 'major', labelsize = 8)

tp.set_ylabel('Numero omicidi',fontsize=8)
tp.set_xlabel('Città',fontsize=8)

tp.axhline(y = 0, color = 'black', linewidth = 4, alpha = 0.7)

labels = [item.get_text() for item in tp.get_xticklabels()]
labels[9] = 'Reggio C.'

tp.set_xticklabels(labels)

text = tp.text(x = -1.3, y = -10,
    s = 'www.ildatomancante.it                                                                            Istat - 2014',
    fontsize = 10, color = '#f0f0f0', backgroundcolor = 'grey')

# Adding a title and a subtitle Reddito e aspettativa di vita
tp.text(x = -0.6, y = 57, s = "Numero Omicidi Città Italiane",
                   fontsize = 14, weight = 'bold', alpha = .75)
tp.text(x = -0.6, y = 54, 
                   s = "Top 10 città italiane per numero omicidi.",
                  fontsize = 10, alpha = .85)

plt.xticks(rotation=0)
fig_prj = tp.get_figure()

fig_prj.savefig(os.path.join(dir_out,'topcitta_2014.png'), format='png', dpi=300,bbox_inches='tight')


    

In [42]:

    

df_eur_filename = r'df_eur.pkl'
df_eur_fullpath = os.path.join(dir_df, df_eur_filename)
df_eur = pd.read_pickle(df_eur_fullpath)


    

In [44]:

    

europa_geo_filename = r'euro.geojson'
europa_geo = os.path.join(dir_df, europa_geo_filename)

eur_map = folium.Map(location=[48, 10], zoom_start=4)
eur_map.choropleth(geo_path=europa_geo, data=df_eur,
                  columns=['geo', 'Value'],
                  key_on='feature.properties.iso_a2',
                  fill_color='YlOrRd')

reg_map.save(os.path.join(dir_out,r'omicidi_volontari_eu.html'))

eur_map


    

    




/Users/cesar/anaconda/lib/python3.6/site-packages/ipykernel/__main__.py:8: FutureWarning: 'threshold_scale' default behavior has changed. Now you get a linear scale between the 'min' and the 'max' of your data. To get former behavior, use folium.utilities.split_six.






    
Out[44]:

In [45]:

    

# Top 3 Paesi
df_eur_top3=df_eur.sort_values(by='Value',ascending=False).head(3)
df_eur_top3


    

    
Out[45]:






  

    

      

      
geo
      
Value
    
  
  

    

      
104
      
FR
      
792.0
    
    

      
62
      
DE
      
645.0
    
    

      
139
      
IT
      
475.0
    
  

In [46]:

    

df_eur_cit_filename = r'df_eur_cit.pkl'
df_eur_cit_fullpath = os.path.join(dir_df, df_eur_cit_filename)
df_eur_cit = pd.read_pickle(df_eur_cit_fullpath)
# Report
tp1 = df_eur_cit.plot(
        x=df_eur_cit['City name'],
        kind='bar',
        legend = False)
for p in tp1.patches:
    tp1.annotate(str(p.get_height()), (p.get_x() * 1.005, p.get_height() * 1.005), ha='center', va='center', xytext=(10, 5), textcoords='offset points')
    tp1.plot()

fig_eur = tp1.get_figure()
fig_eur.tight_layout()
fig_eur.savefig(os.path.join(dir_out,'topeurcitta.png'), format='png', dpi=300)