使用 pandas 从 World Bank API 获取数据

Question

我正在尝试获取一个数据表，该表仅获取来自 World Bank API 的国家、年份和价值，但我似乎无法筛选出我想要的数据。我看到已经提出过这类问题，但似乎所有答案都不起作用。

非常感谢一些帮助。谢谢！

import requests
import pandas as pd
from bs4 import BeautifulSoup
import json

url ="http://api.worldbank.org/v2/country/{}/indicator/NY.GDP.PCAP.CD?date=2015&format=json"
country = ["DZA","AGO","ARG","AUS","AUT","BEL","BRA","CAN","CHL","CHN","COL","CYP", "CZE","DNK","FIN","FRA","GEO","DEU",
          "GRC""HUN","ISL","IND","IDN","IRL","ISR","ITA","JPN","KAZ","KWT","LBN","LIE","MYS","MEX","MCO","MAR","NPL","NLD",
          "NZL","NGA","NOR","OMN","PER","PHL","POL","PRT","QAT","ROU","SGP","ZAF","ESP","SWE","CHE","TZA","THA","TUR","UKR",
          "GBR","USA","VNM","ZWE"]

html={}
for i in country:
 url_one = url.format(i)
 html[i] = requests.get(url_one).json()

my_values=[]
for i in country:

  value=html[i][1][0]['value']
  my_values.append(value)

编辑

我的数据目前看起来像这样，我正在尝试提取 '{'country': {'id': 'AO', 'value': 'Angola''} 中的国家名称，'date '和'价值'

编辑 2 得到了我正在寻找的数据，但每次重复两次

Answer 1

注意： 假设一次存储所有年份的信息而不仅仅是一年 - 使您能够在以后的处理中简单地过滤。看一下，你们国家之间少了一个“，”"GRC""HUN"

有不同的选择可以实现您的目标，只需将其中两个指向正确的方向即可。

选项 #1

从 json 响应中选择需要的信息，创建一个重构的 dict 并将 append() 它发送到 my_values：

for d in data[1]:

    my_values.append({
        'country':d['country']['value'],
        'date':d['date'],
        'value':d['value']
    })

示例

import requests
import pandas as pd


url = 'http://api.worldbank.org/v2/country/%s/indicator/NY.GDP.PCAP.CD?format=json'
countries = ["DZA","AGO","ARG","AUS","AUT","BEL","BRA","CAN","CHL","CHN","COL","CYP", "CZE","DNK","FIN","FRA","GEO","DEU",
          "GRC","HUN","ISL","IND","IDN","IRL","ISR","ITA","JPN","KAZ","KWT","LBN","LIE","MYS","MEX","MCO","MAR","NPL","NLD",
          "NZL","NGA","NOR","OMN","PER","PHL","POL","PRT","QAT","ROU","SGP","ZAF","ESP","SWE","CHE","TZA","THA","TUR","UKR",
          "GBR","USA","VNM","ZWE"]
    
my_values = []
for country in countries:
    data = requests.get(url %country).json()

    try:
        for d in data[1]:
            my_values.append({
                'country':d['country']['value'],
                'date':d['date'],
                'value':d['value']
            })
    except Exception as err:
        print(f'[ERROR] country ==> {country} error ==> {err}')

pd.DataFrame(my_values).sort_values(['country', 'date'], ascending=True)

选项 #2

直接从 json 响应创建一个数据帧，连接它们并对最终的数据帧进行一些调整：

for d in data[1]:
    my_values.append(pd.DataFrame(d))

...

pd.concat(my_values).loc[['value']][['country','date','value']].sort_values(['country', 'date'], ascending=True)

输出

country	date	value
Algeria	1971	341.389
Algeria	1972	442.678
Algeria	1973	554.293
Algeria	1974	818.008
Algeria	1975	936.79
...	...	...
Zimbabwe	2016	1464.59
Zimbabwe	2017	1235.19
Zimbabwe	2018	1254.64
Zimbabwe	2019	1316.74
Zimbabwe	2020	1214.51

Answer 2

Pandas read_json 方法需要有效的 JSON 字符串、路径对象或类似文件的对象，但您输入了字符串。 https://pandas.pydata.org/docs/reference/api/pandas.read_json.html

试试这个：

import requests
import pandas as pd


url = "http://api.worldbank.org/v2/country/%s/indicator/NY.GDP.PCAP.CD?date=2015&format=json"
countries = ["DZA","AGO","ARG","AUS","AUT","BEL","BRA","CAN","CHL","CHN","COL","CYP", "CZE","DNK","FIN","FRA","GEO","DEU",
          "GRC""HUN","ISL","IND","IDN","IRL","ISR","ITA","JPN","KAZ","KWT","LBN","LIE","MYS","MEX","MCO","MAR","NPL","NLD",
          "NZL","NGA","NOR","OMN","PER","PHL","POL","PRT","QAT","ROU","SGP","ZAF","ESP","SWE","CHE","TZA","THA","TUR","UKR",
          "GBR","USA","VNM","ZWE"]

datas = []
for country in countries:
    data = requests.get(url %country).json()
    try:
        values = data[1][0]
        datas.append(pd.DataFrame(values))
    except Exception as err:
        print(f"[ERROR] country ==> {country} with error ==> {err}")

df = pd.concat(datas)