Examen Periodismo de Datos - Parte Práctica

Diego Domínguez González - Periodismo y Humanidades Grupo 61

pip install pandas

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Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (2020.4)
Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.7.3->pandas) (1.14.0)
�[33mWARNING: You are using pip version 21.0.1; however, version 22.1.2 is available.
You should consider upgrading via the '/usr/bin/python3 -m pip install --upgrade pip' command.�[0m
Note: you may need to restart the kernel to use updated packages.

import pandas as pd

url = "https://api.covid19api.com/countries"

df = pd.read_json(url)

df

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	Country	Slug	ISO2
0	Falkland Islands (Malvinas)	falkland-islands-malvinas	FK
1	Panama	panama	PA
2	Russian Federation	russia	RU
3	Turkmenistan	turkmenistan	TM
4	Guinea	guinea	GN
...	...	...	...
243	Guyana	guyana	GY
244	Hungary	hungary	HU
245	Kazakhstan	kazakhstan	KZ
246	Liberia	liberia	LR
247	Somalia	somalia	SO

248 rows × 3 columns

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 248 entries, 0 to 247
Data columns (total 3 columns):
 #   Column   Non-Null Count  Dtype 
---  ------   --------------  ----- 
 0   Country  248 non-null    object
 1   Slug     248 non-null    object
 2   ISO2     248 non-null    object
dtypes: object(3)
memory usage: 5.9+ KB

España

url_esp = "https://api.covid19api.com/country/spain/status/confirmed/live"

df_esp = pd.read_json(url_esp)

df_esp

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status	Date
0	Spain	ES				40.46	-3.75	0	confirmed	2020-01-22 00:00:00+00:00
1	Spain	ES				40.46	-3.75	0	confirmed	2020-01-23 00:00:00+00:00
2	Spain	ES				40.46	-3.75	0	confirmed	2020-01-24 00:00:00+00:00
3	Spain	ES				40.46	-3.75	0	confirmed	2020-01-25 00:00:00+00:00
4	Spain	ES				40.46	-3.75	0	confirmed	2020-01-26 00:00:00+00:00
...	...	...	...	...	...	...	...	...	...	...
883	Spain	ES				40.46	-3.75	12613634	confirmed	2022-06-23 00:00:00+00:00
884	Spain	ES				40.46	-3.75	12681820	confirmed	2022-06-24 00:00:00+00:00
885	Spain	ES				40.46	-3.75	12681820	confirmed	2022-06-25 00:00:00+00:00
886	Spain	ES				40.46	-3.75	12681820	confirmed	2022-06-26 00:00:00+00:00
887	Spain	ES				40.46	-3.75	12681820	confirmed	2022-06-27 00:00:00+00:00

888 rows × 10 columns

df_esp.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 888 entries, 0 to 887
Data columns (total 10 columns):
 #   Column       Non-Null Count  Dtype              
---  ------       --------------  -----              
 0   Country      888 non-null    object             
 1   CountryCode  888 non-null    object             
 2   Province     888 non-null    object             
 3   City         888 non-null    object             
 4   CityCode     888 non-null    object             
 5   Lat          888 non-null    float64            
 6   Lon          888 non-null    float64            
 7   Cases        888 non-null    int64              
 8   Status       888 non-null    object             
 9   Date         888 non-null    datetime64[ns, UTC]
dtypes: datetime64[ns, UTC](1), float64(2), int64(1), object(6)
memory usage: 69.5+ KB

df_esp ["Date"][1]

Timestamp('2020-01-23 00:00:00+0000', tz='UTC')

df_esp.describe()

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	Lat	Lon	Cases
count	8.880000e+02	888.00	8.880000e+02
mean	4.046000e+01	-3.75	4.092078e+06
std	7.109432e-15	0.00	3.947626e+06
min	4.046000e+01	-3.75	0.000000e+00
25%	4.046000e+01	-3.75	4.569650e+05
50%	4.046000e+01	-3.75	3.347512e+06
75%	4.046000e+01	-3.75	5.069291e+06
max	4.046000e+01	-3.75	1.268182e+07

df_esp.set_index("Date")

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status
Date
2020-01-22 00:00:00+00:00	Spain	ES				40.46	-3.75	0	confirmed
2020-01-23 00:00:00+00:00	Spain	ES				40.46	-3.75	0	confirmed
2020-01-24 00:00:00+00:00	Spain	ES				40.46	-3.75	0	confirmed
2020-01-25 00:00:00+00:00	Spain	ES				40.46	-3.75	0	confirmed
2020-01-26 00:00:00+00:00	Spain	ES				40.46	-3.75	0	confirmed
...	...	...	...	...	...	...	...	...	...
2022-06-23 00:00:00+00:00	Spain	ES				40.46	-3.75	12613634	confirmed
2022-06-24 00:00:00+00:00	Spain	ES				40.46	-3.75	12681820	confirmed
2022-06-25 00:00:00+00:00	Spain	ES				40.46	-3.75	12681820	confirmed
2022-06-26 00:00:00+00:00	Spain	ES				40.46	-3.75	12681820	confirmed
2022-06-27 00:00:00+00:00	Spain	ES				40.46	-3.75	12681820	confirmed

888 rows × 9 columns

df_esp.set_index("Date")["Cases"]

Date
2020-01-22 00:00:00+00:00           0
2020-01-23 00:00:00+00:00           0
2020-01-24 00:00:00+00:00           0
2020-01-25 00:00:00+00:00           0
2020-01-26 00:00:00+00:00           0
                               ...   
2022-06-23 00:00:00+00:00    12613634
2022-06-24 00:00:00+00:00    12681820
2022-06-25 00:00:00+00:00    12681820
2022-06-26 00:00:00+00:00    12681820
2022-06-27 00:00:00+00:00    12681820
Name: Cases, Length: 888, dtype: int64

df_esp.set_index("Date")["Cases"].plot(title="Casos España Covid")

<AxesSubplot:title={'center':'Casos España Covid'}, xlabel='Date'>

Francia

url_fra = "https://api.covid19api.com/country/france/status/confirmed/live"

df_fra = pd.read_json(url_fra)

df_fra

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status	Date
0	France	FR	Martinique			14.64	-61.02	0	confirmed	2020-01-22 00:00:00+00:00
1	France	FR	New Caledonia			-20.90	165.62	0	confirmed	2020-01-22 00:00:00+00:00
2	France	FR	Reunion			-21.12	55.54	0	confirmed	2020-01-22 00:00:00+00:00
3	France	FR	Wallis and Futuna			-14.29	-178.12	0	confirmed	2020-01-22 00:00:00+00:00
4	France	FR	French Guiana			4.00	-53.00	0	confirmed	2020-01-22 00:00:00+00:00
...	...	...	...	...	...	...	...	...	...	...
10652	France	FR	Mayotte			-12.83	45.17	37877	confirmed	2022-06-27 00:00:00+00:00
10653	France	FR	Saint Barthelemy			17.90	-62.83	4671	confirmed	2022-06-27 00:00:00+00:00
10654	France	FR	French Guiana			3.93	-53.13	85596	confirmed	2022-06-27 00:00:00+00:00
10655	France	FR	Reunion			-21.12	55.54	421269	confirmed	2022-06-27 00:00:00+00:00
10656	France	FR				46.23	2.21	29823387	confirmed	2022-06-28 00:00:00+00:00

10657 rows × 10 columns

df_fra.describe()

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	Lat	Lon	Cases
count	10657.000000	10657.000000	1.065700e+04
mean	6.433109	-34.730791	6.325769e+05
std	23.358877	88.296378	3.279857e+06
min	-21.120000	-178.120000	0.000000e+00
25%	-14.290000	-62.830000	1.090000e+02
50%	14.640000	-56.320000	3.819000e+03
75%	18.070000	2.210000	3.595300e+04
max	46.890000	165.620000	2.982339e+07

df_fra.set_index("Date")

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status
Date
2020-01-22 00:00:00+00:00	France	FR	Martinique			14.64	-61.02	0	confirmed
2020-01-22 00:00:00+00:00	France	FR	New Caledonia			-20.90	165.62	0	confirmed
2020-01-22 00:00:00+00:00	France	FR	Reunion			-21.12	55.54	0	confirmed
2020-01-22 00:00:00+00:00	France	FR	Wallis and Futuna			-14.29	-178.12	0	confirmed
2020-01-22 00:00:00+00:00	France	FR	French Guiana			4.00	-53.00	0	confirmed
...	...	...	...	...	...	...	...	...	...
2022-06-27 00:00:00+00:00	France	FR	Mayotte			-12.83	45.17	37877	confirmed
2022-06-27 00:00:00+00:00	France	FR	Saint Barthelemy			17.90	-62.83	4671	confirmed
2022-06-27 00:00:00+00:00	France	FR	French Guiana			3.93	-53.13	85596	confirmed
2022-06-27 00:00:00+00:00	France	FR	Reunion			-21.12	55.54	421269	confirmed
2022-06-28 00:00:00+00:00	France	FR				46.23	2.21	29823387	confirmed

10657 rows × 9 columns

df_fra.set_index("Date")["Cases"]

Date
2020-01-22 00:00:00+00:00           0
2020-01-22 00:00:00+00:00           0
2020-01-22 00:00:00+00:00           0
2020-01-22 00:00:00+00:00           0
2020-01-22 00:00:00+00:00           0
                               ...   
2022-06-27 00:00:00+00:00       37877
2022-06-27 00:00:00+00:00        4671
2022-06-27 00:00:00+00:00       85596
2022-06-27 00:00:00+00:00      421269
2022-06-28 00:00:00+00:00    29823387
Name: Cases, Length: 10657, dtype: int64

df_fra.set_index("Date")["Cases"].plot(title="Casos Francia Covid")

<AxesSubplot:title={'center':'Casos Francia Covid'}, xlabel='Date'>

Italia

url_ita = "https://api.covid19api.com/country/italy/status/confirmed/live"

df_ita = pd.read_json(url_ita)

df_ita

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status	Date
0	Italy	IT				41.87	12.57	0	confirmed	2020-01-22 00:00:00+00:00
1	Italy	IT				41.87	12.57	0	confirmed	2020-01-23 00:00:00+00:00
2	Italy	IT				41.87	12.57	0	confirmed	2020-01-24 00:00:00+00:00
3	Italy	IT				41.87	12.57	0	confirmed	2020-01-25 00:00:00+00:00
4	Italy	IT				41.87	12.57	0	confirmed	2020-01-26 00:00:00+00:00
...	...	...	...	...	...	...	...	...	...	...
883	Italy	IT				41.87	12.57	18071634	confirmed	2022-06-23 00:00:00+00:00
884	Italy	IT				41.87	12.57	18128044	confirmed	2022-06-24 00:00:00+00:00
885	Italy	IT				41.87	12.57	18184917	confirmed	2022-06-25 00:00:00+00:00
886	Italy	IT				41.87	12.57	18234242	confirmed	2022-06-26 00:00:00+00:00
887	Italy	IT				41.87	12.57	18259261	confirmed	2022-06-27 00:00:00+00:00

888 rows × 10 columns

df_ita.describe()

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	Lat	Lon	Cases
count	888.00	8.880000e+02	8.880000e+02
mean	41.87	1.257000e+01	4.670686e+06
std	0.00	1.777358e-15	5.231011e+06
min	41.87	1.257000e+01	0.000000e+00
25%	41.87	1.257000e+01	2.689650e+05
50%	41.87	1.257000e+01	3.745302e+06
75%	41.87	1.257000e+01	4.885903e+06
max	41.87	1.257000e+01	1.825926e+07

df_ita.set_index("Date")

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	Country	CountryCode	Province	City	CityCode	Lat	Lon	Cases	Status
Date
2020-01-22 00:00:00+00:00	Italy	IT				41.87	12.57	0	confirmed
2020-01-23 00:00:00+00:00	Italy	IT				41.87	12.57	0	confirmed
2020-01-24 00:00:00+00:00	Italy	IT				41.87	12.57	0	confirmed
2020-01-25 00:00:00+00:00	Italy	IT				41.87	12.57	0	confirmed
2020-01-26 00:00:00+00:00	Italy	IT				41.87	12.57	0	confirmed
...	...	...	...	...	...	...	...	...	...
2022-06-23 00:00:00+00:00	Italy	IT				41.87	12.57	18071634	confirmed
2022-06-24 00:00:00+00:00	Italy	IT				41.87	12.57	18128044	confirmed
2022-06-25 00:00:00+00:00	Italy	IT				41.87	12.57	18184917	confirmed
2022-06-26 00:00:00+00:00	Italy	IT				41.87	12.57	18234242	confirmed
2022-06-27 00:00:00+00:00	Italy	IT				41.87	12.57	18259261	confirmed

888 rows × 9 columns

df_ita.set_index("Date")["Cases"]

Date
2020-01-22 00:00:00+00:00           0
2020-01-23 00:00:00+00:00           0
2020-01-24 00:00:00+00:00           0
2020-01-25 00:00:00+00:00           0
2020-01-26 00:00:00+00:00           0
                               ...   
2022-06-23 00:00:00+00:00    18071634
2022-06-24 00:00:00+00:00    18128044
2022-06-25 00:00:00+00:00    18184917
2022-06-26 00:00:00+00:00    18234242
2022-06-27 00:00:00+00:00    18259261
Name: Cases, Length: 888, dtype: int64

df_ita.set_index("Date")["Cases"].plot(title="Casos Italia Covid")

<AxesSubplot:title={'center':'Casos Italia Covid'}, xlabel='Date'>

Gráfico de los 3 países

casos_fra = df_fra.set_index("Date")["Cases"]
casos_esp = df_esp.set_index("Date")["Cases"]
casos_ita = df_ita.set_index("Date")["Cases"]

vs = pd.concat([casos_fra,casos_esp,casos_ita],axis=1)

vs

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	Cases	Cases	Cases
Date
2020-01-22 00:00:00+00:00	0.0	0	0.0
2020-01-22 00:00:00+00:00	0.0	0	0.0
2020-01-22 00:00:00+00:00	0.0	0	0.0
2020-01-22 00:00:00+00:00	0.0	0	0.0
2020-01-22 00:00:00+00:00	0.0	0	0.0
...	...	...	...
2022-06-27 00:00:00+00:00	12681820.0	37877	18259261.0
2022-06-27 00:00:00+00:00	12681820.0	4671	18259261.0
2022-06-27 00:00:00+00:00	12681820.0	85596	18259261.0
2022-06-27 00:00:00+00:00	12681820.0	421269	18259261.0
2022-06-28 00:00:00+00:00	NaN	29823387	NaN

10657 rows × 3 columns

vs.columns = ["Francia","España","Italia"]

vs

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	Francia	España	Italia
Date
2020-01-22 00:00:00+00:00	0	0.0	0.0
2020-01-22 00:00:00+00:00	0	0.0	0.0
2020-01-22 00:00:00+00:00	0	0.0	0.0
2020-01-22 00:00:00+00:00	0	0.0	0.0
2020-01-22 00:00:00+00:00	0	0.0	0.0
...	...	...	...
2022-06-27 00:00:00+00:00	37877	12681820.0	18259261.0
2022-06-27 00:00:00+00:00	4671	12681820.0	18259261.0
2022-06-27 00:00:00+00:00	85596	12681820.0	18259261.0
2022-06-27 00:00:00+00:00	421269	12681820.0	18259261.0
2022-06-28 00:00:00+00:00	29823387	NaN	NaN

10657 rows × 3 columns

vs.plot(title="Gráfico de comparación entre países")

<AxesSubplot:title={'center':'Gráfico de comparación entre países'}, xlabel='Date'>

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parte-practica.md

parte-practica.md

Examen Periodismo de Datos - Parte Práctica

Diego Domínguez González - Periodismo y Humanidades Grupo 61

España

Francia

Italia

Gráfico de los 3 países

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Examen Periodismo de Datos - Parte Práctica

Diego Domínguez González - Periodismo y Humanidades Grupo 61

España

Francia

Italia

Gráfico de los 3 países