COVID-19
Visualizaciones Interactivas con Python Bokeh
(Cerrado)
Introducción
Este es un proyecto 100% reproducible en el que creamos visualizaciones interactivas sobre la evolución de la pandemia del Coronavirus COVID-19.
Los datos son tomados de
"Our World in Data: Coronavirus Source Data" y se actualizan cada día.
Paquetes Python
In [2]:
import datetime
import pandas as pd
import numpy as np
import itertools
from os import listdir
from bokeh import plotting
from bokeh.io import output_notebook, show
from bokeh.models import HoverTool, FactorRange, CustomJS, Div, Row, ImageURL
from bokeh.plotting import figure, output_file, show
from bokeh.layouts import gridplot
from IPython.display import display, HTML
from bokeh.models import ColumnDataSource
from bokeh.palettes import Category20c
output_notebook()
In [3]:
print("Última actualización: " +
str(datetime.datetime.now().strftime("%Y-%b-%d %H:%M")))
Preparación de Datos
In [4]:
data = pd.read_csv("https://covid.ourworldindata.org/data/ecdc/full_data.csv")
#data = pd.read_csv("full_data.csv")
data['date'] = pd.to_datetime(data['date'], format='%Y-%m-%d')
Totales
Casos en el Mundo
In [5]:
a = int(data['total_cases'][data['location'] == 'World'].max())
62,271,031
Decesos en el Mundo
In [6]:
b = int(data['total_deaths'][data['location'] == 'World'].max())
1,453,531
Casos en México
In [7]:
c = int(data['total_cases'][data['location'] == 'Mexico'].max())
1,100,683
Decesos en México
In [8]:
d = int(data['total_deaths'][data['location'] == 'Mexico'].max())
105,459
Casos y Decesos en México
In [9]:
dataM = data[(data['location'] == 'Mexico') & (data['date'] >= '2020-03-12')]
In [10]:
def vis_1():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
sourceM = plotting.ColumnDataSource(dataM)
p = figure(title="",
x_axis_label='Fecha',
y_axis_label='Número Casos',
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
x_axis_type='datetime',
tools="box_zoom, reset, wheel_zoom, save")
plot1 = p.line(x='date',
y='total_cases',
line_width=2,
source=sourceM,
color='red')
p.circle(x='date',
y='total_cases',
size=6,
source=sourceM,
fill_color=None,
color='red')
plot2 = p.line(x='date',
y='total_deaths',
line_width=2,
source=sourceM,
color='black')
p.circle(x='date',
y='total_deaths',
size=6,
source=sourceM,
fill_color=None,
color='black')
p.add_tools(
HoverTool(renderers=[plot1],
tooltips=[
("País", "@location"),
("Fecha", "@date{%F}"),
("Casos Totales", "@total_cases"),
],
formatters={'@date': 'datetime'}))
p.add_tools(
HoverTool(renderers=[plot2],
tooltips=[
("País", "@location"),
("Fecha", "@date{%F}"),
("Decesos Totales", "@total_deaths"),
],
formatters={'@date': 'datetime'}))
p.toolbar.active_drag = None
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Casos y Decesos Totales en México
In [12]:
def vis_2():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
sourceM = plotting.ColumnDataSource(dataM)
p = figure(title="",
x_axis_label='Fecha',
y_axis_label='Número Casos',
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
x_axis_type='datetime',
tools="box_zoom, reset, wheel_zoom, save")
plot1 = p.line(x='date',
y='new_cases',
line_width=2,
source=sourceM,
color='red')
p.circle(x='date',
y='new_cases',
size=6,
source=sourceM,
fill_color=None,
color='red')
plot2 = p.line(x='date',
y='new_deaths',
line_width=2,
source=sourceM,
color='black')
p.circle(x='date',
y='new_deaths',
size=6,
source=sourceM,
fill_color=None,
color='black')
p.add_tools(
HoverTool(renderers=[plot1],
tooltips=[
("País", "@location"),
("Fecha", "@date{%F}"),
("Casos Diarios", "@new_cases"),
],
formatters={'@date': 'datetime'}))
p.add_tools(
HoverTool(renderers=[plot2],
tooltips=[
("País", "@location"),
("Fecha", "@date{%F}"),
("Decesos Diarios", "@new_deaths"),
],
formatters={'@date': 'datetime'}))
p.toolbar.active_drag = None
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Casos y Decesos Diarios en México
Casos y Decesos Totales en los Estados
Los datos son extraídos diariamente del portal oficial de datos sobre Covid-19 del gobierno de México.
Covid-19 México
In [14]:
csv_s = [
file for file in listdir(
'/home/pakin/Documents/desarrolloWeb/PakinV5/me/cov19-estados/')
if file.endswith('.csv')
]
In [15]:
data_edosC = pd.read_csv(
"/home/pakin/Documents/desarrolloWeb/PakinV5/me/cov19-estados/{}".format(
[s for s in csv_s if 'Confirmados' in s][0]))
In [16]:
data_edosC = pd.read_csv(
"/home/pakin/Documents/desarrolloWeb/PakinV5/me/cov19-estados/{}".format(
[s for s in csv_s if 'Confirmados' in s][0]))
data_edosCT = data_edosC.melt(id_vars=["cve_ent", "poblacion", "nombre"],
var_name="FECHA",
value_name="CASOS")
data_edosCTT = data_edosCT.pivot(index='FECHA',
columns='nombre',
values='CASOS').rename_axis(None, axis=1)
data_edosCTT.reset_index(inplace=True)
data_edosCTT['FECHA'] = pd.to_datetime(data_edosCTT['FECHA'],
format='%d-%m-%Y')
data_edosCTT = data_edosCTT.sort_values(by=['FECHA'])
data_edosCTT = data_edosCTT[(data_edosCTT['FECHA'] >= '2020-03-01')]
data_edosCTT.columns = data_edosCTT.columns.str.strip().str.replace(' ', '_')
colms = data_edosCTT.columns.to_list()[1:]
data_edosCTT.loc[:, colms] = data_edosCTT.loc[:, colms].cumsum(axis=0)
cols = [col for col in data_edosCTT.columns if col not in ['Nacional']]
data_edosCTT = data_edosCTT[cols]
estados_1 = data_edosCTT.columns.tolist()[1:16]
estados_2 = data_edosCTT.columns.tolist()[16:]
n1 = len(estados_1)
n2 = len(estados_2)
def color_gen1():
yield from itertools.cycle(Category20c[n1])
color1 = color_gen1()
def color_gen2():
yield from itertools.cycle(Category20c[n2])
color2 = color_gen2()
In [17]:
def vis_3():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = ColumnDataSource(data_edosCTT)
col_names = estados_1
p = figure(title="",
x_axis_type="datetime",
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
toolbar_location='right',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(data_edosCTT.loc[:, estados_1], color1,
col_names, estados_1):
p_dict[col_name] = p.line('FECHA',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('FECHA',
col,
source=source,
color=c,
size=6,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[('Estado', col), ('Fecha', '@FECHA{%F}'),
('Casos Acumulados', f'@{col}')],
formatters={'@FECHA': 'datetime'}))
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.spacing = 15
p.legend.padding = 20
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Casos Totales en Estados
Parte 1
In [19]:
def vis_4():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = ColumnDataSource(data_edosCTT)
col_names = estados_2
p = figure(title="",
x_axis_type="datetime",
plot_width=800,
plot_height=450,
sizing_mode='scale_width',
toolbar_location='right',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(data_edosCTT.loc[:, estados_2], color2,
col_names, estados_2):
p_dict[col_name] = p.line('FECHA',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('FECHA',
col,
source=source,
color=c,
size=6,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[('Estado', col), ('Fecha', '@FECHA{%F}'),
('Casos Acumulados', f'@{col}')],
formatters={'@FECHA': 'datetime'}))
p.legend.spacing = 15
p.legend.padding = 20
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Casos Totales en Estados
Parte 2
In [21]:
data_edosD = pd.read_csv(
"/home/pakin/Documents/desarrolloWeb/PakinV5/me/cov19-estados/{}".format(
[s for s in csv_s if 'Defunciones' in s][0]))
data_edosDT = data_edosD.melt(id_vars=["cve_ent", "poblacion", "nombre"],
var_name="FECHA",
value_name="CASOS")
data_edosDTT = data_edosDT.pivot(index='FECHA',
columns='nombre',
values='CASOS').rename_axis(None, axis=1)
data_edosDTT.reset_index(inplace=True)
data_edosDTT['FECHA'] = pd.to_datetime(data_edosDTT['FECHA'],
format='%d-%m-%Y')
data_edosDTT = data_edosDTT.sort_values(by=['FECHA'])
data_edosDTT = data_edosDTT[(data_edosDTT['FECHA'] >= '2020-03-01')]
data_edosDTT.columns = data_edosDTT.columns.str.strip().str.replace(' ', '_')
colms = data_edosDTT.columns.to_list()[1:]
data_edosDTT.loc[:, colms] = data_edosDTT.loc[:, colms].cumsum(axis=0)
data_edosDTT = data_edosDTT[cols]
In [22]:
def vis_5():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = ColumnDataSource(data_edosDTT)
col_names = estados_1
p = figure(title="",
x_axis_type="datetime",
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
toolbar_location='right',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(data_edosDTT.loc[:, estados_1], color1,
col_names, estados_1):
p_dict[col_name] = p.line('FECHA',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('FECHA',
col,
source=source,
color=c,
size=6,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[('Estado', col), ('Fecha', '@FECHA{%F}'),
('Decesos Acumulados', f'@{col}')],
formatters={'@FECHA': 'datetime'}))
p.legend.click_policy = "hide"
p.legend.spacing = 15
p.legend.padding = 20
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Decesos Totales en Estados
Parte 1
In [24]:
def vis_6():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = ColumnDataSource(data_edosDTT)
col_names = estados_2
p = figure(title="",
x_axis_type="datetime",
plot_width=800,
plot_height=450,
sizing_mode='scale_width',
toolbar_location='right',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(data_edosDTT.loc[:, estados_2], color2,
col_names, estados_2):
p_dict[col_name] = p.line('FECHA',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('FECHA',
col,
source=source,
color=c,
size=6,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[('Estado', col), ('Fecha', '@FECHA{%F}'),
('Decesos Acumulados', f'@{col}')],
formatters={'@FECHA': 'datetime'}))
p.legend.spacing = 15
p.legend.padding = 20
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Decesos Totales en Estados
Parte 2
Casos y Decesos en Diferentes Países
In [26]:
n = 18
def color_gen():
yield from itertools.cycle(Category20c[n])
color = color_gen()
paises = data.groupby(['location']).max().sort_values(
'total_cases', ascending=False).head(n).iloc[1:].index.tolist()
col_names = paises
In [27]:
def vis_7():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
dataTCDP = data.pivot(index='date',
columns='location',
values='total_cases').rename_axis(None, axis=1)
dataTCDP = dataTCDP.loc[(dataTCDP.index >= '2020-02-01')]
dataTCDP17 = dataTCDP.loc[:, paises]
dataTCDP17.columns = dataTCDP17.columns.str.strip().str.replace(' ', '_')
output_notebook()
source = ColumnDataSource(dataTCDP17)
p = figure(title="",
x_axis_label='Fecha',
y_axis_label='Número de Casos',
x_axis_type="datetime",
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(dataTCDP17.columns, color, col_names,
paises):
p_dict[col_name] = p.line('date',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('date',
col,
source=source,
color=c,
size=6,
line_width=0.5,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[
('País', col),
('Fecha', '@date{%F}'),
('Casos Totales', f'@{col}'),
],
formatters={'@date': 'datetime'}))
p.legend.spacing = 10
p.legend.padding = 15
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Casos Totales Diferentes Países
In [29]:
def vis_8():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
dataTDDP = data.pivot(index='date',
columns='location',
values='total_deaths').rename_axis(None, axis=1)
dataTDDP = dataTDDP.loc[(dataTDDP.index >= '2020-02-01')]
dataTDDP17 = dataTDDP.loc[:, paises]
dataTDDP17.columns = dataTDDP17.columns.str.strip().str.replace(' ', '_')
output_notebook()
source = ColumnDataSource(dataTDDP17)
p = figure(title="",
x_axis_label='Fecha',
y_axis_label='Número de Decesos',
x_axis_type="datetime",
plot_width=900,
plot_height=450,
sizing_mode='scale_width',
tools="box_zoom, reset, wheel_zoom, save")
p_dict = dict()
for col, c, col_name, leg in zip(dataTDDP17.columns, color, col_names,
paises):
p_dict[col_name] = p.line('date',
col,
source=source,
color=c,
line_width=2,
legend_label=leg)
p_dict[col_name] = p.circle('date',
col,
source=source,
color=c,
size=6,
line_width=0.5,
fill_color=None,
legend_label=leg)
p.add_tools(
HoverTool(toggleable=False,
renderers=[p_dict[col_name]],
tooltips=[
('País', col),
('Fecha', '@date{%F}'),
('Decesos Totales', f'@{col}'),
],
formatters={'@date': 'datetime'}))
p.legend.spacing = 10
p.legend.padding = 15
p.toolbar.active_drag = None
p.legend.click_policy = "hide"
p.legend.label_text_font_size = "1vw"
p.legend.location = 'top_left'
p.left[0].formatter.use_scientific = False
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1vw"
show(p)
Decesos Totales Diferentes Países
Top 30 Casos Totales
In [31]:
dataTC = data.groupby(['location'
]).max().sort_values('total_cases',
ascending=False).head(31).iloc[1:]
dataTC = dataTC.reset_index()
In [32]:
def vis_9():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = plotting.ColumnDataSource(dataTC)
p = figure(title='',
x_axis_label='',
y_axis_label='',
plot_width=900,
plot_height=450,
x_range=FactorRange(factors=list(dataTC['location'])),
sizing_mode='scale_width',
tools="box_zoom, reset, wheel_zoom, save")
plot1 = p.vbar(x='location',
width=0.5,
bottom=0,
top='total_cases',
source=source,
color='#B22222')
p.add_tools(
HoverTool(
renderers=[plot1],
tooltips=[
("País", "@location"),
("Casos Totales", "@total_cases"),
],
))
p.toolbar.active_drag = None
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1.3vw"
p.xaxis.major_label_orientation = np.pi / 5
show(p)
Top 30 Países Casos Totales
Top 30 Decesos Totales
In [34]:
dataTD = data.groupby(['location'
]).max().sort_values('total_deaths',
ascending=False).head(31).iloc[1:]
dataTD = dataTD.reset_index()
In [35]:
def vis_10():
'''
Autor: Francisco Jaramillo
https://www.pakin.lat/
'''
source = plotting.ColumnDataSource(dataTD)
p = figure(title='',
x_axis_label='',
y_axis_label='',
plot_width=900,
plot_height=450,
x_range=FactorRange(factors=list(dataTD['location'])),
sizing_mode='scale_width',
tools="box_zoom, reset, wheel_zoom, save")
plot1 = p.vbar(x='location',
width=0.5,
bottom=0,
top='total_deaths',
source=source,
color='#000000')
p.add_tools(
HoverTool(
renderers=[plot1],
tooltips=[
("País", "@location"),
("Decesos Totales", "@total_deaths"),
],
))
p.toolbar.active_drag = None
p.left[0].formatter.use_scientific = False
p.title.text_font_size = '3vw'
p.xaxis.axis_label_text_font_size = "2vw"
p.yaxis.axis_label_text_font_size = "2vw"
p.xaxis.major_label_text_font_size = "1.3vw"
p.yaxis.major_label_text_font_size = "1.3vw"
p.xaxis.major_label_orientation = np.pi / 5
show(p)
