我已经从世界卫生组织以JSON格式调用了一些数据，我想将其读入Pandas DataFrame中。
我在此页面中称此为：
WHO Measles First Dose Rate
{u'dimension': [{u'display': u'Indicator', u'label': u'GHO'},
{u'display': u'PUBLISH STATES', u'label': u'PUBLISHSTATE'},
{u'display': u'Year', u'label': u'YEAR'},
{u'display': u'WHO region', u'label': u'REGION'},
{u'display': u'World Bank income group', u'label': u'WORLDBANKINCOMEGROUP'},
{u'display': u'Country', u'label': u'COUNTRY'}],
u'fact': [{u'Value': u'25',
u'dim': {u'COUNTRY': u'Afghanistan',
u'GHO': u'Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%)',
u'PUBLISHSTATE': u'Published',
u'REGION': u'Eastern Mediterranean',
u'WORLDBANKINCOMEGROUP': u'Low-income',
u'YEAR': u'1993'}},
{u'Value': u'57',
u'dim': {u'COUNTRY': u'Afghanistan',
u'GHO': u'Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%)',
u'PUBLISHSTATE': u'Published',
u'REGION': u'Eastern Mediterranean',
u'WORLDBANKINCOMEGROUP': u'Low-income',
u'YEAR': u'2013'}},
{u'Value': u'62',
u'dim': {u'COUNTRY': u'Angola',
u'GHO': u'Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%)',
u'PUBLISHSTATE': u'Published',
u'REGION': u'Africa',
u'WORLDBANKINCOMEGROUP': u'Upper-middle-income',
u'YEAR': u'1996'}},
{u'Value': u'94',
u'dim': {u'COUNTRY': u'Andorra',
u'GHO': u'Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%)',
u'PUBLISHSTATE': u'Published',
u'REGION': u'Europe',
u'WORLDBANKINCOMEGROUP': u'High-income',
u'YEAR': u'2005'}},
{u'Value': u'34',
u'dim': {u'COUNTRY': u'United Arab Emirates',
u'GHO': u'Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%)',
u'PUBLISHSTATE': u'Published',
u'REGION': u'Eastern Mediterranean',
u'WORLDBANKINCOMEGROUP': u'High-income',
u'YEAR': u'1980'}},
我试过了
#Setting Up and loading JSON into object ready to turn into dataframe
url = "http://apps.who.int/gho/athena/data/GHO/WHS8_110.json?profile=simple&filter=COUNTRY:*"
response = requests.get(url)
response_json = response.content
json.loads(response_json)
whoDataSetVaccinationRate = json.loads(response_json)
#Attempt to load JSON Data into Pandas Dataframe
whoDataSetVaccinationRateDF = pd.DataFrame(whoDataSetVaccinationRate['fact']
, columns=['COUNTRY', 'YEAR','REGION'])
whoDataSetVaccinationRateDF
似乎可以理解-但我在COUNTRY和YEAR的数据框中仅获得NaN值：
而且我意识到我仍然希望它在数据帧中的布局有所不同-我不确定如何调用它。这就是我希望数据框看起来的样子：
最佳答案
将json_normalize与pivot一起使用：
from pandas.io.json import json_normalize
import urllib.request, json
#https://stackoverflow.com/a/12965254
url = "http://apps.who.int/gho/athena/data/GHO/WHS8_110.json?profile=simple&filter=COUNTRY:*"
with urllib.request.urlopen(url) as url:
data = json.loads(url.read().decode())
df = json_normalize(data['fact']).pivot('dim.COUNTRY','dim.YEAR','Value').astype(float)
print (df.head())
dim.YEAR 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... \
dim.COUNTRY ...
Afghanistan 11.0 NaN 8.0 9.0 14.0 14.0 14.0 31.0 34.0 22.0 ...
Albania 90.0 90.0 93.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 ...
Algeria NaN NaN NaN NaN NaN 68.0 67.0 73.0 81.0 82.0 ...
Andorra NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ...
Angola NaN NaN NaN 26.0 35.0 44.0 44.0 55.0 56.0 48.0 ...
dim.YEAR 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
dim.COUNTRY
Afghanistan 55.0 59.0 60.0 62.0 64.0 59.0 57.0 60.0 62.0 62.0
Albania 97.0 98.0 97.0 99.0 99.0 98.0 99.0 98.0 97.0 96.0
Algeria 92.0 88.0 92.0 95.0 95.0 95.0 95.0 95.0 95.0 94.0
Andorra 94.0 98.0 98.0 99.0 99.0 98.0 95.0 96.0 96.0 97.0
Angola 71.0 61.0 57.0 72.0 64.0 72.0 66.0 60.0 55.0 49.0
[5 rows x 37 columns]
关于python - 如何将此JSON数据读入Python，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/49752547/