TypeRoor reading json

[GreenLynx]

Hi,
I’m trying to read a json url however I’ve got this error:
“TypeError: list indices must be integers or slices, not str”

This is de json url: https://servicios.ine.es/wstempus/js/es/...tip=AM&
and the idea is see it in jupyter notebook as a table with this columns
“Año”, “Municipio”, “De 0 a 4 años”, “De 5 a 9 años”, “De 10 a 14 años”, etc, but I can’t do it
Any idea or help?

Thank you

[buran]

Show your code and full traceback you get. It looks you get and parse the JSON response and then get error when try to use it.

Also show expected output because the JSON is nested

[GreenLynx]

Hi buran and thank you,

This is my code

response = requests.get(path_json_crecimientopob)
data = response.json()['data']
data

and have this error

"---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_1880\2903580319.py in <module>
1 response = requests.get(path_json_crecimientopob)
----> 2 data = response.json()['data']
3 data

TypeError: list indices must be integers or slices, not str"

I use this code for other json and then it was transformed into dataframe to work with them, but in this case don't work, I new in python and probably I can't see the solution.

The result should be a table with many columns:

'Municipio'
'Año'
'De 0 a 4 años'
'De 5 a 9 años'
'De 10 a 14 años'
'De 15 a 64 años'
'De 15 a 19 años'
'De 20 a 24 años'
'De 25 a 29 años'
'De 30 a 34 años'
'De 35 a 39 años'
'De 40 a 44 años'
'De 45 a 49 años'
'De 50 a 54 años'
'De 55 a 59 años'
'De 60 a 64 años'
'De 65 a 69 años'
'De 70 a 74 años'
'De 75 a 79 años'
'De 80 a 84 años'
'De 85 a 89 años'
'De 90 a 94 años'
'De 95 a 99 años'
'De 100 y más años'

[buran]

Your json is array of 6864 jsonobjects, that is deserialised to list of dicts, like this (one elment):

Output:
{
	"COD": "PC97987",
	"Nombre": "Todas las edades. Total. Total. Málaga. Dato base. ",
	"T3_Unidad": "Personas",
	"T3_Escala": " ",
	"MetaData": [{
		"Id": 15668,
		"Variable": {
			"Id": 356,
			"Nombre": "Totales de edad",
			"Codigo": ""
		},
		"Nombre": "Todas las edades",
		"Codigo": ""
	}, {
		"Id": 16420,
		"Variable": {
			"Id": 141,
			"Nombre": "Nacionalidad",
			"Codigo": ""
		},
		"Nombre": "Total",
		"Codigo": ""
	}, {
		"Id": 451,
		"Variable": {
			"Id": 18,
			"Nombre": "Sexo",
			"Codigo": ""
		},
		"Nombre": "Total",
		"Codigo": ""
	}, {
		"Id": 30,
		"Variable": {
			"Id": 115,
			"Nombre": "Provincias",
			"Codigo": "PROV"
		},
		"Nombre": "Málaga",
		"Codigo": "29"
	}, {
		"Id": 72,
		"Variable": {
			"Id": 3,
			"Nombre": "Tipo de dato",
			"Codigo": ""
		},
		"Nombre": "Dato base",
		"Codigo": ""
	}],
	"Data": [{
		"Fecha": "2022-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2022,
		"Valor": 1717504.0
	}, {
		"Fecha": "2021-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2021,
		"Valor": 1695651.0
	}, {
		"Fecha": "2020-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2020,
		"Valor": 1685920.0
	}, {
		"Fecha": "2019-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2019,
		"Valor": 1661785.0
	}, {
		"Fecha": "2018-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2018,
		"Valor": 1641121.0
	}, {
		"Fecha": "2017-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2017,
		"Valor": 1630615.0
	}, {
		"Fecha": "2016-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2016,
		"Valor": 1629298.0
	}, {
		"Fecha": "2015-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2015,
		"Valor": 1628973.0
	}, {
		"Fecha": "2014-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2014,
		"Valor": 1621968.0
	}, {
		"Fecha": "2013-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2013,
		"Valor": 1652999.0
	}, {
		"Fecha": "2012-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2012,
		"Valor": 1641098.0
	}, {
		"Fecha": "2011-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2011,
		"Valor": 1625827.0
	}, {
		"Fecha": "2010-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2010,
		"Valor": 1609557.0
	}, {
		"Fecha": "2009-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2009,
		"Valor": 1593068.0
	}, {
		"Fecha": "2008-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2008,
		"Valor": 1563261.0
	}, {
		"Fecha": "2007-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2007,
		"Valor": 1517523.0
	}, {
		"Fecha": "2006-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2006,
		"Valor": 1491287.0
	}, {
		"Fecha": "2005-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2005,
		"Valor": 1453409.0
	}, {
		"Fecha": "2004-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2004,
		"Valor": 1397925.0
	}, {
		"Fecha": "2003-01-01T00:00:00.000+01:00",
		"T3_TipoDato": "Definitivo",
		"T3_Periodo": "1 de enero de",
		"Anyo": 2003,
		"Valor": 1374890.0
	}]
}

I don't see which part of this goes into which column