def macro_cons_opec_near_change():
"""
欧佩克报告-变动, 数据区间从20170118-至今
:return: pandas.Series
阿尔及利亚 安哥拉 厄瓜多尔 加蓬 伊朗 伊拉克 科威特 利比亚 尼日利亚 \
2017-01-18 -0.87 3.56 -0.25 -0.87 0.95 4.26 0.20 3.13 -11.35
2017-02-13 -4.17 -2.32 -1.67 -1.00 5.02 -16.57 -14.12 6.47 10.18
2017-03-14 -0.02 -1.82 -0.44 -0.69 3.61 -6.20 -0.93 -1.11 5.80
2017-04-12 0.45 -1.87 -0.28 0.19 -2.87 -0.85 -0.95 -6.08 -2.98
2017-05-11 -0.75 9.71 -0.06 0.88 -3.47 -3.91 0.03 -6.16 5.08
2017-06-13 0.96 -5.42 0.22 -0.13 0.45 4.44 0.00 17.82 17.42
2017-07-12 -0.09 6.60 -0.21 -0.77 1.67 6.06 -0.02 12.70 9.67
2017-08-10 -0.10 -1.93 0.85 0.71 0.69 -3.31 -0.74 15.43 3.43
2017-09-12 0.41 0.83 -0.03 -3.23 -0.23 -2.31 0.01 -11.23 13.83
2017-10-11 -0.85 -0.29 -0.05 1.44 0.09 3.16 -0.17 5.39 5.08
2017-11-13 -3.84 6.98 0.71 0.18 -1.13 -13.10 -0.37 4.23 -5.44
2017-12-13 1.41 -10.87 -0.51 -0.47 -0.22 0.10 -0.53 0.61 9.58
2018-01-18 3.03 4.48 -0.72 -0.01 1.32 0.79 -0.25 -0.70 7.57
2018-04-12 -4.95 -8.17 0.26 -0.91 0.33 -1.31 0.23 -3.72 1.82
2018-05-14 1.77 -0.78 0.31 -0.93 1.00 -0.07 0.08 0.69 -0.83
2018-06-12 3.90 1.40 0.06 0.18 0.56 2.77 -0.57 -2.43 -5.35
2018-07-11 0.46 -8.83 -0.09 0.35 -2.27 7.15 2.73 -25.43 2.78
2018-08-13 1.38 1.17 0.42 -0.34 -5.63 2.41 7.85 -5.67 7.05
2018-09-12 -1.40 -0.80 0.40 18.80 -15.00 9.00 0.80 25.60 7.40
2018-10-11 -0.80 5.70 53.10 -0.10 -15.00 0.80 0.60 10.30 2.60
2018-11-13 -0.40 2.20 -0.30 0.30 -15.60 465.30 -3.30 6.00 -1.70
2018-12-12 -0.50 0.30 0.10 -1.10 -38.00 -2.30 4.50 -1.10 -3.00
2019-03-14 0.20 2.20 0.50 0.70 1.20 -7.00 -1.40 2.30 1.00
2019-04-10 -0.70 0.70 52.40 0.90 -2.80 -12.60 -0.10 19.60 1.10
2019-06-13 0.60 7.40 -0.10 2.30 -22.70 9.40 1.30 -0.30 -9.20
沙特 阿联酋 委内瑞拉 欧佩克产量
2017-01-18 -14.93 -0.63 -4.52 -22.09
2017-02-13 -49.62 -15.93 -3.05 -89.02
2017-03-14 -6.81 -3.69 -1.60 -13.95
2017-04-12 4.16 -3.27 -2.59 -15.27
2017-05-11 4.92 -6.23 -2.60 -1.82
2017-06-13 0.23 -1.80 -0.77 33.61
2017-07-12 5.13 -0.07 -1.36 39.35
2017-08-10 3.18 -0.67 -1.58 17.26
2017-09-12 -1.03 -2.02 -3.19 -7.91
2017-10-11 -0.07 -0.84 -5.19 8.85
2017-11-13 1.69 -0.60 -4.36 -15.09
2017-12-13 -4.54 -3.55 -4.16 -13.35
2018-01-18 -1.09 -0.70 -8.22 4.24
2018-04-12 -4.69 4.49 -5.53 -20.14
2018-05-14 4.65 0.61 -4.17 1.21
2018-06-12 8.55 -0.63 -4.25 3.54
2018-07-11 40.54 3.51 -4.75 17.34
2018-08-13 -5.28 6.92 -4.77 4.07
2018-09-12 3.80 1.20 -3.60 27.80
2018-10-11 10.80 3.00 -4.20 13.20
2018-11-13 12.70 14.20 -4.00 12.70
2018-12-12 37.70 7.10 -5.20 -1.10
2019-03-14 -8.60 -0.40 -14.20 -22.10
2019-04-10 -32.40 -0.90 -28.90 -53.40
2019-06-13 -7.60 0.30 -3.50 -23.60
"""
t = time.time()
res = requests.get(
JS_CONS_OPEC_URL.format(str(int(round(t * 1000))),
str(int(round(t * 1000)) + 90)))
json_data = json.loads(res.text[res.text.find("{"):res.text.rfind("}") +
1])
date_list = [item["date"] for item in json_data["list"]]
big_df = pd.DataFrame()
for country in [item["datas"] for item in json_data["list"]][0].keys():
try:
value_list = [item["datas"][country] for item in json_data["list"]]
value_df = pd.DataFrame(value_list)
value_df.columns = json_data["kinds"]
value_df.index = pd.to_datetime(date_list)
temp_df = value_df["最近差异"]
temp_df.name = country
big_df = big_df.append(temp_df)
except:
continue
return big_df.T
def _macro_cons_opec_month():
"""
欧佩克报告-月度, 数据区间从 20170118-至今
这里返回的具体索引日期的数据为上一个月的数据, 由于某些国家的数据有缺失,
只选择有数据的国家返回
:return: pandas.Series
阿尔及利亚 安哥拉 厄瓜多尔 加蓬 伊朗 伊拉克 科威特 利比亚 尼日利亚 \
2017-01-18 108.0 172.4 54.5 21.3 372.0 463.2 281.2 60.8 154.2
2017-02-13 104.5 165.1 52.7 19.9 377.5 447.6 271.8 67.5 157.6
2017-03-14 105.3 164.1 52.6 19.4 381.4 441.4 270.9 66.9 160.8
2017-04-12 105.6 161.4 52.6 19.8 379.0 440.2 270.2 62.2 154.5
2017-05-11 104.7 169.2 52.4 20.6 375.9 437.3 270.2 55.0 150.8
2017-06-13 105.9 161.3 52.8 20.4 379.5 442.4 270.5 73.0 168.0
2017-07-12 106.0 166.8 52.7 19.7 379.0 450.2 270.9 85.2 173.3
2017-08-10 105.9 164.6 53.6 20.5 382.4 446.8 270.3 100.1 174.8
2017-09-12 106.5 164.6 53.7 17.3 382.8 444.8 270.2 89.0 186.1
2017-10-11 104.6 164.1 53.6 20.1 382.7 449.4 270.0 92.3 185.5
2017-11-13 101.2 171.1 54.1 20.3 382.3 438.3 270.8 96.2 173.8
2017-12-13 101.3 158.1 53.3 19.7 381.8 439.6 270.3 97.3 179.0
2018-01-18 103.7 163.3 52.6 19.7 382.9 440.5 270.0 96.2 186.1
2018-04-12 98.4 152.4 51.8 18.3 381.4 442.6 270.4 96.8 181.0
2018-05-14 99.7 151.5 52.0 18.3 382.3 442.9 270.5 98.2 179.1
2018-06-12 103.1 152.5 51.9 18.9 382.9 445.5 270.1 95.5 171.1
2018-07-11 103.9 143.1 51.9 19.0 379.9 453.3 273.1 70.8 166.0
2018-08-13 106.2 145.6 52.5 18.8 373.7 455.6 279.1 66.4 166.7
2018-09-12 104.5 144.8 52.9 18.7 358.4 464.9 280.2 92.6 172.5
2018-10-11 104.9 151.9 53.1 18.7 344.7 465.0 281.2 105.3 174.8
2018-11-13 105.4 153.3 52.5 18.6 329.6 465.4 276.4 111.4 175.1
2018-12-12 105.2 152.1 52.5 17.6 295.4 463.1 280.9 110.4 173.6
2019-03-14 102.6 145.7 52.2 20.3 274.3 463.3 270.9 90.6 174.1
2019-04-10 101.8 145.4 52.4 21.4 269.8 452.2 270.9 109.8 173.3
2019-06-13 102.9 147.1 52.9 21.1 237.0 472.4 271.0 117.4 173.3
沙特 阿联酋 委内瑞拉 欧佩克产量
2017-01-18 1047.4 307.1 202.1 3308.5
2017-02-13 994.6 293.1 200.4 3213.9
2017-03-14 979.7 292.5 198.7 3195.8
2017-04-12 999.4 289.5 197.2 3192.8
2017-05-11 995.4 284.2 195.6 3173.2
2017-06-13 994.0 288.5 196.3 3213.9
2017-07-12 995.0 289.8 193.8 3261.1
2017-08-10 1006.7 290.5 193.2 3286.9
2017-09-12 1002.2 290.1 191.8 3275.5
2017-10-11 997.5 290.5 189.0 3274.8
2017-11-13 1000.0 291.1 186.3 3258.9
2017-12-13 999.6 288.3 183.4 3244.8
2018-01-18 991.8 287.8 174.5 3241.6
2018-04-12 993.4 286.4 148.8 3195.8
2018-05-14 995.9 287.2 143.6 3193.0
2018-06-12 998.7 286.5 139.2 3186.9
2018-07-11 1042.0 289.7 134.0 3232.7
2018-08-13 1038.7 295.9 127.8 3232.3
2018-09-12 1040.1 297.2 123.5 3256.5
2018-10-11 1051.2 300.4 119.7 3276.1
2018-11-13 1063.0 316.0 117.1 3290.0
2018-12-12 1101.6 324.6 113.7 3296.5
2019-03-14 1008.7 307.2 100.8 3054.9
2019-04-10 979.4 305.9 73.2 3002.2
2019-06-13 969.0 306.1 74.1 2987.6
"""
t = time.time()
res = requests.get(
JS_CONS_OPEC_URL.format(str(int(round(t * 1000))),
str(int(round(t * 1000)) + 90)))
json_data = json.loads(res.text[res.text.find("{"):res.text.rfind("}") +
1])
date_list = [item["date"] for item in json_data["list"]]
big_df = pd.DataFrame()
for country in [item["datas"] for item in json_data["list"]][0].keys():
try:
value_list = [item["datas"][country] for item in json_data["list"]]
value_df = pd.DataFrame(value_list)
value_df.columns = json_data["kinds"]
value_df.index = pd.to_datetime(date_list)
temp_df = value_df["上个月"]
temp_df.name = country
big_df = big_df.append(temp_df)
except:
continue
headers = {
"accept": "*/*",
"accept-encoding": "gzip, deflate, br",
"accept-language": "zh-CN,zh;q=0.9,en;q=0.8",
"cache-control": "no-cache",
"origin": "https://datacenter.jin10.com",
"pragma": "no-cache",
"referer": "https://datacenter.jin10.com/reportType/dc_opec_report",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-site",
"user-agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.117 Safari/537.36",
"x-app-id": "rU6QIu7JHe2gOUeR",
"x-csrf-token": "",
"x-version": "1.0.0",
}
res = requests.get(
f"https://datacenter-api.jin10.com/reports/dates?category=opec&_={str(int(round(t * 1000)))}",
headers=headers) # 日期序列
all_date_list = res.json()["data"]
need_date_list = [
item for item in all_date_list if item.split("-")[0] +
item.split("-")[1] + item.split("-")[2] not in date_list
]
for item in reversed(need_date_list):
res = requests.get(
f"https://datacenter-api.jin10.com/reports/list?category=opec&date={item}&_={str(int(round(t * 1000)))}",
headers=headers)
temp_df = pd.DataFrame(
res.json()["data"]["values"],
columns=pd.DataFrame(
res.json()["data"]["keys"])["name"].tolist()).T
temp_df.columns = temp_df.iloc[0, :]
temp_df = temp_df[[
'阿尔及利亚', '安哥拉', '厄瓜多尔', '加蓬', '伊朗', '伊拉克', '科威特', '利比亚', '尼日利亚',
'沙特', '阿联酋', '委内瑞拉', '欧佩克产量'
]].iloc[-2, :]
big_df[item] = temp_df
return big_df.T
def macro_cons_opec_month(month_type="上个月"):
"""
欧佩克报告-月度, 数据区间从20170118-至今
:param month_type: ["上上上上个月", "上上上个月", "上上个月", "上个月"]
:return: pandas.Series
阿尔及利亚 安哥拉 厄瓜多尔 加蓬 伊朗 伊拉克 科威特 利比亚 尼日利亚 \
2017-01-18 108.0 172.4 54.5 21.3 372.0 463.2 281.2 60.8 154.2
2017-02-13 104.5 165.1 52.7 19.9 377.5 447.6 271.8 67.5 157.6
2017-03-14 105.3 164.1 52.6 19.4 381.4 441.4 270.9 66.9 160.8
2017-04-12 105.6 161.4 52.6 19.8 379.0 440.2 270.2 62.2 154.5
2017-05-11 104.7 169.2 52.4 20.6 375.9 437.3 270.2 55.0 150.8
2017-06-13 105.9 161.3 52.8 20.4 379.5 442.4 270.5 73.0 168.0
2017-07-12 106.0 166.8 52.7 19.7 379.0 450.2 270.9 85.2 173.3
2017-08-10 105.9 164.6 53.6 20.5 382.4 446.8 270.3 100.1 174.8
2017-09-12 106.5 164.6 53.7 17.3 382.8 444.8 270.2 89.0 186.1
2017-10-11 104.6 164.1 53.6 20.1 382.7 449.4 270.0 92.3 185.5
2017-11-13 101.2 171.1 54.1 20.3 382.3 438.3 270.8 96.2 173.8
2017-12-13 101.3 158.1 53.3 19.7 381.8 439.6 270.3 97.3 179.0
2018-01-18 103.7 163.3 52.6 19.7 382.9 440.5 270.0 96.2 186.1
2018-04-12 98.4 152.4 51.8 18.3 381.4 442.6 270.4 96.8 181.0
2018-05-14 99.7 151.5 52.0 18.3 382.3 442.9 270.5 98.2 179.1
2018-06-12 103.1 152.5 51.9 18.9 382.9 445.5 270.1 95.5 171.1
2018-07-11 103.9 143.1 51.9 19.0 379.9 453.3 273.1 70.8 166.0
2018-08-13 106.2 145.6 52.5 18.8 373.7 455.6 279.1 66.4 166.7
2018-09-12 104.5 144.8 52.9 18.7 358.4 464.9 280.2 92.6 172.5
2018-10-11 104.9 151.9 53.1 18.7 344.7 465.0 281.2 105.3 174.8
2018-11-13 105.4 153.3 52.5 18.6 329.6 465.4 276.4 111.4 175.1
2018-12-12 105.2 152.1 52.5 17.6 295.4 463.1 280.9 110.4 173.6
2019-03-14 102.6 145.7 52.2 20.3 274.3 463.3 270.9 90.6 174.1
2019-04-10 101.8 145.4 52.4 21.4 269.8 452.2 270.9 109.8 173.3
2019-06-13 102.9 147.1 52.9 21.1 237.0 472.4 271.0 117.4 173.3
沙特 阿联酋 委内瑞拉 欧佩克产量
2017-01-18 1047.4 307.1 202.1 3308.5
2017-02-13 994.6 293.1 200.4 3213.9
2017-03-14 979.7 292.5 198.7 3195.8
2017-04-12 999.4 289.5 197.2 3192.8
2017-05-11 995.4 284.2 195.6 3173.2
2017-06-13 994.0 288.5 196.3 3213.9
2017-07-12 995.0 289.8 193.8 3261.1
2017-08-10 1006.7 290.5 193.2 3286.9
2017-09-12 1002.2 290.1 191.8 3275.5
2017-10-11 997.5 290.5 189.0 3274.8
2017-11-13 1000.0 291.1 186.3 3258.9
2017-12-13 999.6 288.3 183.4 3244.8
2018-01-18 991.8 287.8 174.5 3241.6
2018-04-12 993.4 286.4 148.8 3195.8
2018-05-14 995.9 287.2 143.6 3193.0
2018-06-12 998.7 286.5 139.2 3186.9
2018-07-11 1042.0 289.7 134.0 3232.7
2018-08-13 1038.7 295.9 127.8 3232.3
2018-09-12 1040.1 297.2 123.5 3256.5
2018-10-11 1051.2 300.4 119.7 3276.1
2018-11-13 1063.0 316.0 117.1 3290.0
2018-12-12 1101.6 324.6 113.7 3296.5
2019-03-14 1008.7 307.2 100.8 3054.9
2019-04-10 979.4 305.9 73.2 3002.2
2019-06-13 969.0 306.1 74.1 2987.6
"""
t = time.time()
res = requests.get(
JS_CONS_OPEC_URL.format(str(int(round(t * 1000))),
str(int(round(t * 1000)) + 90)))
json_data = json.loads(res.text[res.text.find("{"):res.text.rfind("}") +
1])
date_list = [item["date"] for item in json_data["list"]]
big_df = pd.DataFrame()
for country in [item["datas"] for item in json_data["list"]][0].keys():
try:
value_list = [item["datas"][country] for item in json_data["list"]]
value_df = pd.DataFrame(value_list)
value_df.columns = json_data["kinds"]
value_df.index = pd.to_datetime(date_list)
temp_df = value_df[month_type]
temp_df.name = country
big_df = big_df.append(temp_df)
except:
continue
return big_df.T