我是 python 新手，正在尝试循环数据:
我正在使用 sendgrid api 类别统计端点，并且成功获取一个 API key 的输出。
我的代码:
import pandas as pd
import json
from pandas.io.json import json_normalize
import datetime
yesterday = datetime.date.fromordinal(datetime.date.today().toordinal()-1).strftime("%F")
import http.client
conn = http.client.HTTPSConnection("api.sendgrid.com")
payload = "{}"
keys = {
#"CF_APHI_marketing" : "SG.UdhzjmjYR**",
# "CF_APHI_operational": "SG.FO0b2O*",
# "CF_HPI_marketing": "SG._dnhFlnrSL-**",
# "CF_HPI_operational": "SG.4duN1bHiT9G1**",
# "CF_PPI_operational": "SG.F3zH1XEB**",
# "CF_PP_operational": "SG.9TcrDUAkSLWT**",
# "CF_PP_marketing" : "SG.GD5wMhE_**",
"CF_SandBox" : "SG.eDU7TY**",
# "CF_PKN_operational" : "SG.JsIws8hLT5iYxry0oJlGqw.**",
# "CF_PTC_operational" : "SG.2-dxeY8BRsabipDlRuvZMg.-**",
# "CF_SP_operational" : "SG.tSF_YmxlRkmmsiHNrK2CWQ.xtyhO4UX3U--**",
# "CF_SP_marketing" : "SG.KDuHYR-bRq-T74UexS4WpA.**-**",
# "CF_EI_operational" : "SG.2TRc1VQMT-WDirJG-U-PtQ.sAx-**",
# "CF_D_operational" : "SG.KNFxNavYQ1yJwGTpnIDKxA.**-**"
}
df = [] # Create new Dataframe
for name, value in keys.items():
headers = { 'authorization': "Bearer " + value }
conn.request("GET", "/v3/categories/stats/sums?aggregated_by=&start_date={d}&end_date={d}".format(d=yesterday).format(d=yesterday), payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))
d = json.loads(data.decode("utf-8"))
c=d['stats']
# row = d['stats'][0]['name']
# Add Brand to data row here with 'name'
df.append(c) # Load data row into df
当我调用 df 时，我的输出是:
df 输出[8]:
[[{'type': 'category',
'name': 'Claim Notification Email',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 5,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 5,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Records Request 2',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 1,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 1,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Records Request 1',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 1,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 1,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Appeal Received Email',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 0,
'invalid_emails': 0,
'opens': 1,
'processed': 0,
'requests': 0,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}}]]
我需要我的最终数据框看起来像:
Brand CF_APHI_marketing
name blocks bounce_drops bounces ... unique_opens unsubscribe_dropsunsubscribes
Appeal Received Email 0 7 14 9 ... 1240 0
Records Request 18 12 7 2000 0 0
Records Request2 2 10 8 3333 1 0
基本上想要按品牌(键)获取上述 13 个品牌中每个品牌的所有类别名称的输出。有没有更好的方法来创建这个数据框？
我试过了
sendgrid = pd.DataFrame(df)
但是当我将其导出到 csv 时，我没有收到上面那样的输出，只是得到了一些 json 文本
最佳答案
如果:
df = [[{'type': 'category',
'name': 'Claim Notification Email',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 5,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 5,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Records Request 2',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 1,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 1,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Records Request 1',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 1,
'invalid_emails': 0,
'opens': 0,
'processed': 0,
'requests': 1,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}},
{'type': 'category',
'name': 'Appeal Received Email',
'metrics': {'blocks': 0,
'bounce_drops': 0,
'bounces': 0,
'clicks': 0,
'deferred': 0,
'delivered': 0,
'invalid_emails': 0,
'opens': 1,
'processed': 0,
'requests': 0,
'spam_report_drops': 0,
'spam_reports': 0,
'unique_clicks': 0,
'unique_opens': 0,
'unsubscribe_drops': 0,
'unsubscribes': 0}}]]
试试这个:
df = pd.DataFrame(df[0])
df_new = df[['type', 'name']]
df_metric =pd.DataFrame(list(df['metrics'].values))
sendgrid = pd.concat([df_new, df_metric], axis=1, sort=False)
sendgrid.set_index('name', inplace = True)
sendgrid.to_csv("sendgrid.csv")
你应该得到:
type blocks bounce_drops bounces clicks \
name
Claim Notification Email category 0 0 0 0
Records Request 2 category 0 0 0 0
Records Request 1 category 0 0 0 0
Appeal Received Email category 0 0 0 0
deferred delivered invalid_emails opens \
name
Claim Notification Email 0 5 0 0
Records Request 2 0 1 0 0
Records Request 1 0 1 0 0
Appeal Received Email 0 0 0 1
processed requests spam_report_drops \
name
Claim Notification Email 0 5 0
Records Request 2 0 1 0
Records Request 1 0 1 0
Appeal Received Email 0 0 0
spam_reports unique_clicks unique_opens \
name
Claim Notification Email 0 0 0
Records Request 2 0 0 0
Records Request 1 0 0 0
Appeal Received Email 0 0 0
unsubscribe_drops unsubscribes
name
Claim Notification Email 0 0
Records Request 2 0 0
Records Request 1 0 0
Appeal Received Email 0 0
关于python - 如何循环遍历字典以在最终数据帧的单独行中获取它们的输出？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/60100167/