我正在尝试从OpenWeatherMap转换json数据,但它一直给我错误。当我在其他教程网站上尝试其他json文件时,它工作得很好。
Json格式:
{
"cod": "200",
"message": 0,
"cnt": 40,
"list": [
{
"dt": 1586250000,
"main": {
"temp": 303.36,
"feels_like": 306.76,
"temp_min": 303.36,
"temp_max": 303.95,
"pressure": 1006,
"sea_level": 1006,
"grnd_level": 1004,
"humidity": 61,
"temp_kf": -0.59
},
"weather": [{
"id": 500,
"main": "Rain",
"description": "light rain",
"icon": "10d"
}],
"clouds": {
"all": 97
},
"wind": {
"speed": 1.74,
"deg": 38
},
"rain": {
"3h": 0.29
},
"sys": {
"pod": "d"
},
"dt_txt": "2020-04-07 09:00:00"
}, {
"dt": 1586260800,
"main": {
"temp": 300.42,
"feels_like": 303.73,
"temp_min": 300.42,
"temp_max": 300.86,
"pressure": 1008,
"sea_level": 1008,
"grnd_level": 1006,
"humidity": 76,
"temp_kf": -0.44
},
"weather": [{
"id": 500,
"main": "Rain",
"description": "light rain",
"icon": "10n"
}],
"clouds": {
"all": 83
},
"wind": {
"speed": 2.5,
"deg": 52
},
"rain": {
"3h": 0.53
},
"sys": {
"pod": "n"
},
"dt_txt": "2020-04-07 12:00:00"
}, {
"dt": 1586271600,
"main": {
"temp": 299.85,
"feels_like": 303.12,
"temp_min": 299.85,
"temp_max": 300.15,
"pressure": 1010,
"sea_level": 1010,
"grnd_level": 1008,
"humidity": 80,
"temp_kf": -0.3
},
"weather": [{
"id": 500,
"main": "Rain",
"description": "light rain",
"icon": "10n"
}],
"clouds": {
"all": 62
},
"wind": {
"speed": 2.78,
"deg": 32
},
"rain": {
"3h": 0.16
},
"sys": {
"pod": "n"
},
"dt_txt": "2020-04-07 15:00:00"
}
],
"city": {
"id": 1880252,
"name": "Singapore",
"coord": {
"lat": 1.2897,
"lon": 103.8501
},
"country": "SG",
"population": 3547809,
"timezone": 28800,
"sunrise": 1586214152,
"sunset": 1586257828
}
}
我已经使用python创建了一个函数,以使用api调用读取JSON并使用熊猫将其转换为数据框
def _weather():
url = 'http://api.openweathermap.org/data/2.5/forecast?q=Singapore,{API}'
res = requests.get(url)
data = res.json()
return data
将其读取为json后,我尝试将其转换为数据框,但收到错误
#df = pd.dataFrame(_weather)
df = pd.read_json(_weather)
我错过了任何台阶吗?
预期的数据帧如图所示, 我正在提取16天/每日预测的数据时,试图显示16行数据。
答案 0 :(得分:1)
尝试一下,了解有关json_normalize的更多信息
def _weather_pd(url):
df1 = json_normalize(url['list'], 'weather')
df2 = json_normalize(url['list'])
df = df2.drop('weather', axis=1).join(df1)
return df
答案 1 :(得分:1)
这是问题的另一个变体,在处理嵌套数据(尤其是json)时,我更喜欢glom或jmespath
天气部分的路径是:列表键->'列表容器'->天气键->'列表容器'
列表以[]符号标识,而字典键以点(。)为前缀
import jmespath
expression = jmespath.compile('list[].weather[]')
res = expression.search(data)
pd.DataFrame(res)
id main description icon
0 500 Rain light rain 10d
1 500 Rain light rain 10n
2 500 Rain light rain 10n