In [1]:

import pandas as pd
import pylab as plt

In [2]:

import param
import datetime as dt
import panel as pn

Panel short demo¶

In [3]:

def interact_example(a=2, b=3):
    
    plot = plt.figure()
    ax = plot.add_subplot(111)
    
    pd.Series({'a':a, 'b':b}).plot(kind='bar',ax=ax)


    plt.tight_layout()
    plt.close(plot)
    return plot

In [4]:

pn.interact(interact_example)

WARNING:param.Column00005: Displaying Panel objects in the notebook requires the panel extension to be loaded. Ensure you run pn.extension() before displaying objects in the notebook.

Out[4]:

Column
    [0] Column
        [0] IntSlider(end=6, name='a', start=-2, value=2)
        [1] IntSlider(end=9, name='b', start=-3, value=3)
    [1] Row
        [0] Matplotlib(Figure, name='interactive00004')

Dashboard¶

In [5]:

import sqlite3

In [6]:

con = sqlite3.connect('../Chapter16/data/311.db')

In [9]:

Q = '''
SELECT date(created_date) as date, lower(borough) as boro, complaint_type, COUNT(*) as complaints
FROM raw WHERE borough != 'Unspecified' GROUP BY 1,2,3;
'''

In [10]:

DATA = pd.read_sql_query(Q, con)

In [11]:

DATA.head(3)

Out[11]:

	date	boro	complaint_type	complaints
0	2019-01-01	bronx	APPLIANCE	5
1	2019-01-01	bronx	Air Quality	1
2	2019-01-01	bronx	Blocked Driveway	98

In [12]:

DATA['date'] = pd.to_datetime(DATA['date'])

In [13]:

DATA['date'].describe()

Out[13]:

count                   86976
unique                    205
top       2019-05-21 00:00:00
freq                      510
first     2019-01-01 00:00:00
last      2019-07-24 00:00:00
Name: date, dtype: object

In [14]:

DATA.boro.unique()

Out[14]:

array(['bronx', 'brooklyn', 'manhattan', 'queens', 'staten island'],
      dtype=object)

In [15]:

DATA['date'].max()

Out[15]:

Timestamp('2019-07-24 00:00:00')

In [16]:

boro_total = DATA.groupby(['date', 'boro'])['complaints'].sum().unstack()

In [19]:

print(boro_total.head(5).to_string())

boro        bronx  brooklyn  manhattan  queens  staten island
date                                                         
2019-01-01    995      1657        859    1237            249
2019-01-02   1675      2444       1307    1880            649
2019-01-03   1450      2532       1420    1799            484
2019-01-04   1472      2407       1417    1835            425
2019-01-05   1085      1551        954    1250            292

In [147]:

# boro_total

In [206]:

bounds = (dt.datetime(2019,1,1), dt.datetime(2019,6,14))

class Timeline(param.Parameterized):
    dr = param.DateRange(bounds=bounds, default=bounds)    
    boros = param.ListSelector(default=['Manhattan', 'Bronx', 'Brooklyn', 'Queens', 'Staten Island'], objects=['Manhattan', 'Bronx', 'Brooklyn', 'Queens', 'Staten Island'])
                            
    @param.depends('dr', 'boros')
    def view_tl(self):
        start, end = pd.to_datetime(self.dr[0]), pd.to_datetime(self.dr[1])

        tl_data = boro_total.loc[(boro_total.index >= start) & (boro_total.index <= end), [el.lower() for el in self.boros]]
        
        plot = plt.figure(figsize=(10,5))
    
        ax = plot.add_subplot(111)
        
        tl_data.plot(ax=ax, linewidth=1)
    
        ax.legend(loc=4)
        plt.tight_layout()
        plt.close(plot)
        return plot
    
    @param.depends('dr', 'boros')
    def view_top(self, N=5):
        start, end = pd.to_datetime(self.dr[0]), pd.to_datetime(self.dr[1])
        
        boro_mask = DATA.boro.isin([el.lower() for el in self.boros])
        time_mask = (DATA.date >= start) & (DATA.date <= end)
        
        top = DATA[boro_mask & time_mask]
        
        S = top.groupby(['complaint_type', 'boro'])['complaint_type'].count().unstack()
        topN = S.iloc[S.sum(1).argsort()].tail(N)
        
        plot = plt.figure()
        ax = plot.add_subplot(111)
        
        topN.plot(kind='barh',stacked=True, ax=ax)
        plt.tight_layout()
        plt.close(plot)
        
        return plot

In [208]:

pn.extension()

T = Timeline()
panel = pn.Column( '<h1>NYC 311 dashboard</h1>',
                  T.view_tl, 
                  pn.Row(T.param, T.view_top), sizing_mode='stretch_width')

In [209]:

panel.show()

Out[209]:

<bokeh.server.server.Server at 0x1533172e8>

In [ ]: