Looping in a url or scrape data from variation in Url - python

My goal is to have all latitudes and longitude range for canada being automatically inputted into the code below and it scraping the locations that come up automatically. I know canada range is latitudes of 42°N to 83°N and longitude of 53°W to 141°W. I understand how to scrape this type of data but never had to loop information within a url.I have a fear I will somehow make a loop that does nothing but get me ban from the website. So any help would be great!
import requests
url = "https://www.circlek.com/stores_new.php?lat=43.6529&lng=-79.3849&services=&region=global"
payload={}
headers = {
'Connection': 'keep-alive',
'sec-ch-ua': '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"',
'Accept': '*/*',
'X-Requested-With': 'XMLHttpRequest',
'sec-ch-ua-mobile': '?0',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.106 Safari/537.36',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Dest': 'empty',
'Referer': 'https://www.circlek.com/store-locator?Canada&lat=43.6529&lng=-79.3849',
'Accept-Language': 'en-GB,en-US;q=0.9,en;q=0.8',
'dnt': '1'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.text)


As you commented you can put your code like this , i am guessing your different latitude and longitude store in list like this if not share the range of lat_lng with difference
lat_lng = [(lat,long) for lat,long in zip(range(43,83),range(-141,-53))] #store or create range of latitude and longitude
for latitude,longitude in lat_lng:
url = f"https://www.circlek.com/stores_new.php?lat={latitude}&lng={longitude}&services=&region=global"
payload={}
headers = {
'Connection': 'keep-alive',
'sec-ch-ua': '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"',
'Accept': '*/*',
'X-Requested-With': 'XMLHttpRequest',
'sec-ch-ua-mobile': '?0',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.106 Safari/537.36',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Dest': 'empty',
'Referer': 'https://www.circlek.com/store-locator?Canada&lat=43.6529&lng=-79.3849',
'Accept-Language': 'en-GB,en-US;q=0.9,en;q=0.8',
'dnt': '1'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.json())
you wrap around in function also .
as you commented , for negative arrange range should be like this , it is working
lat_lng = [(lat,long) for lat,long in zip(range(43,83),range(-141,-53))]
#[(43, -141), (44, -140), (45, -139), (46, -138), (47, -137), (48, -136),.....]
In above output to have notice that in zip we have one to one like one latitude point to one longitude but if you want one to many see
itertools module it will help.
for more accurate use i will suggest see np.arange you can use for float also like
np.arange(43,83,0.001)
#array([43. , 43.001, 43.002, ..., 82.997, 82.998, 82.999])

Related

Scraping data through Api from json

I would like to limit the data they receive to the first 8 links on the website. As shown in the picture, there is no data available beyond the 8th link, as seen in the CSV file. How can I apply this limit so that they only receive data from the first 8 links? The website link is https://www.linkedin.com/learning/search?keywords=data%20science,
JSON API
CSV File
Code part
import requests
import pandas as pd
url = "https://www.linkedin.com/learning-api/searchV2?keywords=data%20science&q=keywords&searchRequestId=RW4AuZRJT22%2BUeXnsZJGQA%3D%3D"
payload={}
headers = {
'authority': 'www.linkedin.com',
'accept': 'application/vnd.linkedin.normalized+json+2.1',
'accept-language': 'en-GB,en-US;q=0.9,en;q=0.8,pt;q=0.7',
'cookie': 'bscookie="v=1&202108281231498ed9b977-a15a-4647-83ff-d0ef12adfbfbAQFdf9p_GSaBPrFkmyztJ8zyOnqVND-D"; li_theme=light; li_theme_set=app; li_sugr=4752e3dd-9232-4bb9-9dbb-b29c1a127f77; bcookie="v=2&9fb3a4d0-1139-4e2b-89ba-e5374eeb9735"; aam_uuid=08800810176251362264578372297522883472; _gcl_au=1.1.240501668.1664707206; li_rm=AQELLfU3ZqmMhAAAAYQ_tPjGK8ONpN3EEUxH1P4M6Czq5fk6EXaEXSzKwoNSXoSZ7KgO5uSTE9iZ30fuhs6ju1rLH1VgXYyRM3nNuiTQEx1k2ca6SR0Hk1d5-NBafeE0zv65QetFY5Yrx2ufzRlfEXUkJJSoO9Z2o7MeuX-3Go7P4dI-m5HQM7VOKLiK_TD-ZWzj_OkdkR75K31QKGq8bxPLa0JpkGUzhDIVGWzl6vqkcl6BJEK2s-keIZjsiH5MZ9sbLXEVOxLg4vD21TTJBNshE6zaiWrSnxx_PEm44eDPqjvXRMVWFeX7VZfIe2KFshWXLRc4SY8hAQINymU; visit=v=1&M; G_ENABLED_IDPS=google; JSESSIONID="ajax:7673827752327651374"; timezone=Asia/Karachi; _guid=0f0d3402-80be-4bef-9baf-18d281f68921; mbox=session^#965dfb20b29e4f2688eedcf643d2e5ab^#1671620169|PC^#965dfb20b29e4f2688eedcf643d2e5ab.38_0^#1687170309; __ssid=db28305b-28da-4f8b-ad3a-54dea10b9eb9; dfpfpt=da2e5dde482a41b09cf7178ba1bcec7e; g_state={"i_l":0}; liap=true; li_at=AQEDATKxuC8DTVh9AAABhaytidQAAAGGZN5q6E0AdHv14xrDnsngkfFuMyIIbGYccHR15UrPQ8rb3qpS0_-mpCFm9pXQkoNYGdk87LiGVIqiw4oXuJ9tqflCEOev71_L83JoJ-fkbOfZwdG0RICtuIHn; AnalyticsSyncHistory=AQKUIualgILMBgAAAYZHP2t3mvejt25dMqUMRmrpyhaQMe1cucNiAMliFNRUf4cu4aKnZ1z1kQ_FGeqFr2m04Q; lms_ads=AQEr9ksNAL4kugAAAYZHP2z8QK26stPkoXe2TgJZW3Fnrl4dCzbC2DtithS1-zp5Ve85QwxzRhPvP9okaC0kbu40FYX7EqIk; lms_analytics=AQEr9ksNAL4kugAAAYZHP2z8QK26stPkoXe2TgJZW3Fnrl4dCzbC2DtithS1-zp5Ve85QwxzRhPvP9okaC0kbu40FYX7EqIk; fid=AQGWcXnO5AffyAAAAYZRr6tph6cekZ9ZD66e1xdHhumlVvJ3cKYzZLwfK-I3nJyeRyLQs3LRnowKjQ; lil-lang=en_US; lang=v=2&lang=en-us; _dd_l=1; _dd=ff90da3c-aa07-4491-9106-b226eba1c09c; AMCVS_14215E3D5995C57C0A495C55%40AdobeOrg=1; AMCV_14215E3D5995C57C0A495C55%40AdobeOrg=-637568504%7CMCIDTS%7C19403%7CMCMID%7C09349215808923073694559483836331055195%7CMCAAMLH-1677084815%7C3%7CMCAAMB-1677084815%7CRKhpRz8krg2tLO6pguXWp5olkAcUniQYPHaMWWgdJ3xzPWQmdj0y%7CMCOPTOUT-1676487215s%7CNONE%7CMCCIDH%7C1076847823%7CvVersion%7C5.1.1; s_cc=true; UserMatchHistory=AQJJ3j-efkcQeQAAAYZWAETxBE44VVBGzo_i-gr5nEGPOK85mS3kDScLdGC24_GeNx-GEeCNDrPOjkQde_MGT4iPc7vJV4sT_nPL8Tv4WMTLarIEliLYPkCvou8zFlb3dFNkbXZjVV_KTVeDvUSJ5WJTeStLNXmzV3_EV5mI9dbSRpoTFlJ94vi_zxcCmnLTaGAYGQAdymMv4SbaMgtnt3QcY8Zj9-hnwxdsIEmJloq47_QTP7sfl-SG-vw8xvhl9KYb0ZPKCnQ6ioJhu3G4cFpKJiSUbULkYMADSo0; lidc="b=VB23:s=V:r=V:a=V:p=V:g=4060:u=105:x=1:i=1676480108:t=1676566269:v=2:sig=AQEz2UktgVcQuJwMoVRgKgnUuKtCEm9C"; s_sq=%5B%5BB%5D%5D; gpv_pn=www.linkedin.com%2Flearning%2Fsearch; s_ips=615; s_plt=7.03; s_pltp=www.linkedin.com%2Flearning%2Fsearch; s_tp=6116; s_ppv=www.linkedin.com%2Flearning%2Fsearch%2C47%2C10%2C2859%2C7%2C18; s_tslv=1676480356388',
'csrf-token': 'ajax:7673827752327651374',
'referer': 'https://www.linkedin.com/learning/search?keywords=data%20science',
'sec-ch-ua': '"Chromium";v="110", "Not A(Brand";v="24", "Google Chrome";v="110"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36',
'x-li-lang': 'en_US',
'x-li-page-instance': 'urn:li:page:d_learning_search;gNOg2MJoSqWv2XNAh4ukiQ==',
'x-li-pem-metadata': 'Learning Exp - Search=search',
'x-li-track': '{"clientVersion":"1.1.2236","mpVersion":"1.1.2236","osName":"web","timezoneOffset":5,"timezone":"Asia/Karachi","mpName":"learning-web","displayDensity":1,"displayWidth":1366,"displayHeight":768}',
'x-lil-intl-library': 'en_US',
'x-restli-protocol-version': '2.0.0'
}
res = requests.request("GET", url, headers=headers, data=payload).json()
product=[]
items=res['included']
for item in items:
try:
title=item['headline']['title']['text']
except:
title=''
try:
url='https://www.linkedin.com/learning/'+item['slug']
except:
url=''
try:
rating=item['rating']['ratingCount']
except:
rating=''
wev={
'title':title,
'instructor':name,
'review':rating,
'url':url
}
product.append(wev)
df=pd.DataFrame(product)
df.to_csv('learning.csv')

To filter the rows that contain empty columns, specifically those with an empty title column, you can simply add the following code:
df=pd.DataFrame(product)
filter = df["title"] != ""
dfNew = df[filter]
dfNew.to_csv('learning.csv')
The entire code will be:
import requests
import pandas as pd
url = "https://www.linkedin.com/learning-api/searchV2?keywords=data%20science&q=keywords&searchRequestId=RW4AuZRJT22%2BUeXnsZJGQA%3D%3D"
payload={}
headers = {
'authority': 'www.linkedin.com',
'accept': 'application/vnd.linkedin.normalized+json+2.1',
'accept-language': 'en-GB,en-US;q=0.9,en;q=0.8,pt;q=0.7',
'cookie': 'bscookie="v=1&202108281231498ed9b977-a15a-4647-83ff-d0ef12adfbfbAQFdf9p_GSaBPrFkmyztJ8zyOnqVND-D"; li_theme=light; li_theme_set=app; li_sugr=4752e3dd-9232-4bb9-9dbb-b29c1a127f77; bcookie="v=2&9fb3a4d0-1139-4e2b-89ba-e5374eeb9735"; aam_uuid=08800810176251362264578372297522883472; _gcl_au=1.1.240501668.1664707206; li_rm=AQELLfU3ZqmMhAAAAYQ_tPjGK8ONpN3EEUxH1P4M6Czq5fk6EXaEXSzKwoNSXoSZ7KgO5uSTE9iZ30fuhs6ju1rLH1VgXYyRM3nNuiTQEx1k2ca6SR0Hk1d5-NBafeE0zv65QetFY5Yrx2ufzRlfEXUkJJSoO9Z2o7MeuX-3Go7P4dI-m5HQM7VOKLiK_TD-ZWzj_OkdkR75K31QKGq8bxPLa0JpkGUzhDIVGWzl6vqkcl6BJEK2s-keIZjsiH5MZ9sbLXEVOxLg4vD21TTJBNshE6zaiWrSnxx_PEm44eDPqjvXRMVWFeX7VZfIe2KFshWXLRc4SY8hAQINymU; visit=v=1&M; G_ENABLED_IDPS=google; JSESSIONID="ajax:7673827752327651374"; timezone=Asia/Karachi; _guid=0f0d3402-80be-4bef-9baf-18d281f68921; mbox=session^#965dfb20b29e4f2688eedcf643d2e5ab^#1671620169|PC^#965dfb20b29e4f2688eedcf643d2e5ab.38_0^#1687170309; __ssid=db28305b-28da-4f8b-ad3a-54dea10b9eb9; dfpfpt=da2e5dde482a41b09cf7178ba1bcec7e; g_state={"i_l":0}; liap=true; li_at=AQEDATKxuC8DTVh9AAABhaytidQAAAGGZN5q6E0AdHv14xrDnsngkfFuMyIIbGYccHR15UrPQ8rb3qpS0_-mpCFm9pXQkoNYGdk87LiGVIqiw4oXuJ9tqflCEOev71_L83JoJ-fkbOfZwdG0RICtuIHn; AnalyticsSyncHistory=AQKUIualgILMBgAAAYZHP2t3mvejt25dMqUMRmrpyhaQMe1cucNiAMliFNRUf4cu4aKnZ1z1kQ_FGeqFr2m04Q; lms_ads=AQEr9ksNAL4kugAAAYZHP2z8QK26stPkoXe2TgJZW3Fnrl4dCzbC2DtithS1-zp5Ve85QwxzRhPvP9okaC0kbu40FYX7EqIk; lms_analytics=AQEr9ksNAL4kugAAAYZHP2z8QK26stPkoXe2TgJZW3Fnrl4dCzbC2DtithS1-zp5Ve85QwxzRhPvP9okaC0kbu40FYX7EqIk; fid=AQGWcXnO5AffyAAAAYZRr6tph6cekZ9ZD66e1xdHhumlVvJ3cKYzZLwfK-I3nJyeRyLQs3LRnowKjQ; lil-lang=en_US; lang=v=2&lang=en-us; _dd_l=1; _dd=ff90da3c-aa07-4491-9106-b226eba1c09c; AMCVS_14215E3D5995C57C0A495C55%40AdobeOrg=1; AMCV_14215E3D5995C57C0A495C55%40AdobeOrg=-637568504%7CMCIDTS%7C19403%7CMCMID%7C09349215808923073694559483836331055195%7CMCAAMLH-1677084815%7C3%7CMCAAMB-1677084815%7CRKhpRz8krg2tLO6pguXWp5olkAcUniQYPHaMWWgdJ3xzPWQmdj0y%7CMCOPTOUT-1676487215s%7CNONE%7CMCCIDH%7C1076847823%7CvVersion%7C5.1.1; s_cc=true; UserMatchHistory=AQJJ3j-efkcQeQAAAYZWAETxBE44VVBGzo_i-gr5nEGPOK85mS3kDScLdGC24_GeNx-GEeCNDrPOjkQde_MGT4iPc7vJV4sT_nPL8Tv4WMTLarIEliLYPkCvou8zFlb3dFNkbXZjVV_KTVeDvUSJ5WJTeStLNXmzV3_EV5mI9dbSRpoTFlJ94vi_zxcCmnLTaGAYGQAdymMv4SbaMgtnt3QcY8Zj9-hnwxdsIEmJloq47_QTP7sfl-SG-vw8xvhl9KYb0ZPKCnQ6ioJhu3G4cFpKJiSUbULkYMADSo0; lidc="b=VB23:s=V:r=V:a=V:p=V:g=4060:u=105:x=1:i=1676480108:t=1676566269:v=2:sig=AQEz2UktgVcQuJwMoVRgKgnUuKtCEm9C"; s_sq=%5B%5BB%5D%5D; gpv_pn=www.linkedin.com%2Flearning%2Fsearch; s_ips=615; s_plt=7.03; s_pltp=www.linkedin.com%2Flearning%2Fsearch; s_tp=6116; s_ppv=www.linkedin.com%2Flearning%2Fsearch%2C47%2C10%2C2859%2C7%2C18; s_tslv=1676480356388',
'csrf-token': 'ajax:7673827752327651374',
'referer': 'https://www.linkedin.com/learning/search?keywords=data%20science',
'sec-ch-ua': '"Chromium";v="110", "Not A(Brand";v="24", "Google Chrome";v="110"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36',
'x-li-lang': 'en_US',
'x-li-page-instance': 'urn:li:page:d_learning_search;gNOg2MJoSqWv2XNAh4ukiQ==',
'x-li-pem-metadata': 'Learning Exp - Search=search',
'x-li-track': '{"clientVersion":"1.1.2236","mpVersion":"1.1.2236","osName":"web","timezoneOffset":5,"timezone":"Asia/Karachi","mpName":"learning-web","displayDensity":1,"displayWidth":1366,"displayHeight":768}',
'x-lil-intl-library': 'en_US',
'x-restli-protocol-version': '2.0.0'
}
res = requests.request("GET", url, headers=headers, data=payload).json()
product=[]
items=res['included']
for item in items:
try:
title=item['headline']['title']['text']
except:
title=''
try:
url='https://www.linkedin.com/learning/'+item['slug']
except:
url=''
try:
rating=item['rating']['ratingCount']
except:
rating=''
name = item.get("description", {}).get("text", "")
wev={
'title':title,
'instructor':name,
'review':rating,
'url':url
}
product.append(wev)
df=pd.DataFrame(product)
filter = df["title"] != ""
dfNew = df[filter]
dfNew.to_csv('learning.csv')
However, this is solution works because the web is structured. For complex/irregular websites I prefer to use scrapy as we use in my job.

<Response [403]> to login zalando

this is what it looks like to me | I am working on this project to connect to zalando but I am encountering this error, I really don't understand how to fix it, would someone please tell me how I could fix it and successfully connect?
`def login():
headers = {
'authority': 'accounts.zalando.com',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'accept-language': 'fr-FR,fr;q=0.9',
'referer': 'https://accounts.zalando.com/authenticate?sales_channel=733af55a-4133-4d7c-b5f3-d64d42c135fe&request=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&ui_locales=fr-FR&passwordMeterFT=true',
'sec-ch-ua': '"Not_A Brand";v="99", "Google Chrome";v="109", "Chromium";v="109"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'document',
'sec-fetch-mode': 'navigate',
'sec-fetch-site': 'same-origin',
'sec-fetch-user': '?1',
'upgrade-insecure-requests': '1',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36',
}
url = 'https://zalando.com/api'
r = requests.get(url, headers=headers)
#print(r.cookies.get_dict())
#print(r.headers)
headers = {
'authority': 'accounts.zalando.com',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'accept-language': 'fr-FR,fr;q=0.9',
'cookie': r.headers['Set-Cookie'],
'referer': 'https://accounts.zalando.com/authenticate?sales_channel=733af55a-4133-4d7c-b5f3-d64d42c135fe&request=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&ui_locales=fr-FR&passwordMeterFT=true',
'sec-ch-ua': '"Not_A Brand";v="99", "Google Chrome";v="109", "Chromium";v="109"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'document',
'sec-fetch-mode': 'navigate',
'sec-fetch-site': 'same-origin',
'sec-fetch-user': '?1',
'upgrade-insecure-requests': '1',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36',
'x-csrf-token': r.cookies.get_dict()['Zalando-Client-Id'],
'x-flow-id': r.headers['X-Zalando-Child-Request-Id']
}
params = {
'email': 'talkaboutanthopls#gmail.com',
'secret': '#Sneakers974!!?',
}
response = requests.post('https://accounts.zalando.com/api/login', json=params, headers=headers)
print(response.content)
print(response.json())
print(response.cookies.get_dict())
print(response.headers)
login()`

How to POST JSON with data payload and header with Python Requests?

I am trying to do some scraping from websites using GET and POST methods, but now I am facing a new challenge.
I am trying to get data from a credit simulator, I found this portuguese site (https://www.bancomontepio.pt/particulares/credito/pessoal/credito-pessoal-online).
As far as I know, I need to use POST method, but I have to specify the data (the Amount value, the Term...). I usually do it by creating a dictionary structure but that is not working.
I'm kinda lost to be fair, maybe the problem is on the header...
Here is my code:
import requests
import warnings
warnings.filterwarnings("ignore")
term=24
amount=5000
url = 'https://simuladores.bancomontepio.pt/ITSCredit.External/Calculator/ITSCredit.Calculator.UI.External/gateway/Calculator/api/Calculator/Calculate?hash=-1359629931'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.122 Safari/537.36',
'Accept-Language': 'pt-PT,pt;q=0.9,en-US;q=0.8,en;q=0.7'}
payload = {'Amount': amount,'Term': term,'ProductCode':"26B1129900X"}
response = requests.post(url, headers=headers, data=payload, verify=False).json()
If i take off the .json(), I get the error Response [410].
The goal is to get the TAN or TAEG that change when term ("Prazo") or amount ("Montante") values change.
Any ideias?
[EDIT]
headers = {'Accept': 'application/json, text/plain, */*' ,
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'pt-PT,pt;q=0.9,en-US;q=0.8,en;q=0.7',
'Connection': 'keep-alive',
'Content-Length': '957',
'content-type': 'text/plain',
'Cookie': '_gcl_au=1.1.911606195.1646064658; OptanonAlertBoxClosed=2022-02-28T16:45:11.586Z; _ga=GA1.2.1147601977.1646064657; _ga_8WVEJF7X11=GS1.1.1646305654.3.1.1646309750.0; _ga_63QCVBV1V3=GS1.1.1646305679.1.1.1646309750.0; ASP.NET_SessionId=wlfbf2dx4oatlio0vl1ftinq; _gid=GA1.2.449121330.1646650093; calc-cookie=; OptanonConsent=isGpcEnabled=0&datestamp=Mon+Mar+07+2022+11%3A38%3A48+GMT%2B0000+(Hora+padr%C3%A3o+da+Europa+Ocidental)&version=6.30.0&isIABGlobal=false&consentId=6caccc97-6af1-4b55-9049-5694835d9f7a&interactionCount=2&landingPath=NotLandingPage&groups=C0001%3A1%2CC0002%3A1%2CC0003%3A1%2CC0004%3A1&hosts=H10%3A1%2CH20%3A1%2CH7%3A1%2CH8%3A1%2CH23%3A1%2CH11%3A1%2CH24%3A1%2CH13%3A1%2CH25%3A1&genVendors=&geolocation=ES%3B&AwaitingReconsent=false; _gali=slider-container; _gat_UA-186811106-6=1',
'Host': 'simuladores.bancomontepio.pt',
'Origin': 'https://simuladores.bancomontepio.pt',
'Referer': 'https://simuladores.bancomontepio.pt/',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="90", "Google Chrome";v="90"',
'sec-ch-ua-mobile': '?0',
'Sec-Fetch-Dest': 'empty',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Site': 'same-origin',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'}headers = {'Accept': 'application/json, text/plain, */*' ,
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'pt-PT,pt;q=0.9,en-US;q=0.8,en;q=0.7',
'Connection': 'keep-alive',
'Content-Length': '957',
'content-type': 'text/plain',
'Cookie': '_gcl_au=1.1.911606195.1646064658; OptanonAlertBoxClosed=2022-02-28T16:45:11.586Z; _ga=GA1.2.1147601977.1646064657; _ga_8WVEJF7X11=GS1.1.1646305654.3.1.1646309750.0; _ga_63QCVBV1V3=GS1.1.1646305679.1.1.1646309750.0; ASP.NET_SessionId=wlfbf2dx4oatlio0vl1ftinq; _gid=GA1.2.449121330.1646650093; calc-cookie=; OptanonConsent=isGpcEnabled=0&datestamp=Mon+Mar+07+2022+11%3A38%3A48+GMT%2B0000+(Hora+padr%C3%A3o+da+Europa+Ocidental)&version=6.30.0&isIABGlobal=false&consentId=6caccc97-6af1-4b55-9049-5694835d9f7a&interactionCount=2&landingPath=NotLandingPage&groups=C0001%3A1%2CC0002%3A1%2CC0003%3A1%2CC0004%3A1&hosts=H10%3A1%2CH20%3A1%2CH7%3A1%2CH8%3A1%2CH23%3A1%2CH11%3A1%2CH24%3A1%2CH13%3A1%2CH25%3A1&genVendors=&geolocation=ES%3B&AwaitingReconsent=false; _gali=slider-container; _gat_UA-186811106-6=1',
'Host': 'simuladores.bancomontepio.pt',
'Origin': 'https://simuladores.bancomontepio.pt',
'Referer': 'https://simuladores.bancomontepio.pt/',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="90", "Google Chrome";v="90"',
'sec-ch-ua-mobile': '?0',
'Sec-Fetch-Dest': 'empty',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Site': 'same-origin',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'}
payload = {'CCRDCalculateInput':{},'MultifunctionsCalculateInput':{},'Device':{'Browser':'chrome','BrowserVersion':'90.0.4430.212','Device':'Desktop','Os':'windows','OsVersion':'windows-10','UserAgent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'},'IsCustomer':'true','Amount':7500,'Term':60,'ConditionCode':'26B1129900X-01-I-129900-F','CreditDestinationCode':'129900','ProductCode':'26B1129900X','FinancedExpenses':'false','FrequencyTrancheCode':'null','GoalCode':'C006','GoalDescription':'PROJETOS PESSOAIS','FrequencyTypeCode':'M','FamilyCode':'CP','Proponents':[{'Position':1,
'Birthday':'1992-03-07T13:03:30.000Z','State':'true','EntityType':{'ID':1,'CompanyID':1,'Code':'P','Description':'Proponente','Value':'null','ValueString':'null','State':'true','Imported':'null'},'ExpenseCodes':['009']}],'Counterparts':0,'OptionalExpenses':[{'Code':'009','Factor':1}],'ResidualValue':0,'InterestOnly':0,'Deferment':0}
Now I'm getting a empty json()... Response 200 but I got this structure:
{'Status': 'Unknown',
'Error': {'VisibleToHuman': False, 'Code': '0', 'Message': ''},
'Result': None}
As far as I know, the status should be "OK" to get some info on the Result.
Cheers

Looks like you need to expand the payload to include more (all) of the parameters (including the cookies, specifically the ASP.NET_SessionId).
import requests
import warnings
warnings.filterwarnings("ignore")
term=24
amount=5000
url = 'https://simuladores.bancomontepio.pt/ITSCredit.External/Calculator/ITSCredit.Calculator.UI.External/gateway/Calculator/api/Calculator/Calculate?hash=-1359629931'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.122 Safari/537.36',
'Accept-Language': 'pt-PT,pt;q=0.9,en-US;q=0.8,en;q=0.7',
'Cookie':'ASP.NET_SessionId=fhkyn1vn5knlw3uhdnh50nii;'}
payload = {
"CCRDCalculateInput":{},
"MultifunctionsCalculateInput":{},
"Device":{
"Browser":"chrome",
"BrowserVersion":"96.0.4664.110",
"Device":"Desktop",
"Os":"windows",
"OsVersion":"windows-10",
"UserAgent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36"},
"IsCustomer":'true',
"Amount":amount,
"Term":term,
"ConditionCode":"26B1129900X-01-I-129900-F",
"CreditDestinationCode":"129900",
"ProductCode":"26B1129900X",
"FinancedExpenses":'false',
"FrequencyTrancheCode":'null',
"GoalCode":"C006",
"GoalDescription":"PROJETOS PESSOAIS",
"FrequencyTypeCode":"M",
"FamilyCode":"CP",
"Proponents":[{
"Position":'1',
"Birthday":"1992-03-10T13:03:24.000Z",
"State":'true',
"EntityType":{
"ID":'1',
"CompanyID":'1',
"Code":"P",
"Description":"Proponente",
"Value":'null',
"ValueString":'null',
"State":'true',
"Imported":'null'},
"ExpenseCodes":[
"009"]}],
"Counterparts":'0',
"OptionalExpenses":[{
"Code":"009",
"Factor":'1'}],
"ResidualValue":'0',
"InterestOnly":'0',
"Deferment":'0'}
jsonData = requests.post(url, headers=headers, json=payload, verify=False).json()
results = jsonData['Result']
mtic = results['MTIC']
installment = results['PeriodInstallment'][0]['Installment']
taeg = results['TAEG']
tan = results['PeriodInstallment'][0]['TAN']
print(f'Installment: {installment}\nTAEG: {taeg}\nTAN: {tan}\nMTIC: {mtic}')
Output:
Installment: 224.5
TAEG: 14.8
TAN: 7.0
MTIC: 5708.2

Need help isolating results from xhr request

When I run the code below, it's giving me a lot of information I don't want. I only want to capture the data circled starting with 4. Does anyone know how to isolate the data in the request to get rid of everything but what is circled? Also, if anyone knows how to bring the results to a csv or xlsx file, that would be even better.
Working code:
import requests
url = "https://www.stockrover.com/stock_infos/grid?_dc=1644769629231"
data = {
"ticker": 4,
"rank": "5",
}
payload = "state=%7B%22sortInfo%22%3A%7B%7D%2C%22columns%22%3A%5B77%2C32%2C498%2C500%2C31%2C27%2C499%2C30%2C578%2C28%2C29%2C544%2C181%2C185%2C186%5D%2C%22view%22%3A281%2C%22priorPrimaryColumn%22%3A170%2C%22filterData%22%3A%5B%5D%2C%22name%22%3A%22New%201%22%2C%22cType%22%3A%22Screener%22%2C%22cNode%22%3A%22s_39%22%2C%22cIsFolder%22%3Afalse%2C%22gridSelection%22%3A%22BTU%22%2C%22lastActive%22%3A1396898415%2C%22primaryColumn%22%3A76%2C%22folderDisabledParams%22%3A%7B%22filterData%22%3A%5B%5D%7D%2C%22mainGridDateRange%22%3A%22ytd%22%2C%22groupState%22%3Anull%2C%22moversGridDateRange%22%3A%221_day%22%2C%22peersGridDateRange%22%3A%221_day%22%2C%22lastGridSelections%22%3A%5B%22BTU%22%5D%2C%22lastQuantNode%22%3A%5B%5D%2C%22includeQuotesInTable%22%3Afalse%2C%22includeAllQuotesLastValue%22%3Afalse%2C%22markets%22%3A%7B%22panel%22%3A%22summary%22%7D%2C%22researchPanel%22%3A%22tablePanel%22%2C%22recentSearchTickers%22%3A%5B%22SPY%22%2C%22AMZN%22%2C%22AAPL%22%2C%22s_32%22%2C%22%5ENDX%22%2C%22AXP%22%2C%22XOM%22%2C%22AFL%22%2C%22%5EDJX%22%2C%22AIT%22%2C%22ADVC%22%5D%2C%22quotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22checkedQuotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22dashboard%22%3A%7B%22buttonRef%22%3A%22272%22%7D%2C%22tickerSelectedFeeds%22%3A%5B%22Benzinga%20News%22%2C%22Yahoo%20News%22%5D%2C%22marketSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Stock%20Market%20News%20-%20Investing.com%22%5D%2C%22bondsSelectedFeeds%22%3A%5B%22Bonds%20Strategy%20-%20Investing.com%22%5D%2C%22commoditiesSelectedFeeds%22%3A%5B%22Commodities%20%26%20Futures%20News%20-%20Investing.com%22%2C%22Commodities%20Fundamental%20Analysis%20-%20Investing.com%22%2C%22Commodities%20Strategy%20Analysis%20-%20Investing.com%22%5D%2C%22stocksSelectedFeeds%22%3A%5B%22CNNMoney%20News%22%2C%22Google%20News%22%2C%22Seeking%20Alpha%20Top%20Stories%22%5D%2C%22etfsSelectedFeeds%22%3A%5B%22Economy%20News%20-%20Investing.com%22%2C%22ETF%20Analysis%20-%20Investing.com%22%2C%22Investing%20Ideas%20-%20Investing.com%22%5D%2C%22topPanel%22%3A%22researchPanel%22%2C%22maxRecordsNode%22%3Afalse%2C%22version%22%3A7%2C%22lastGridSelectionsRaw%22%3A%5B%22BTU%22%5D%2C%22lastSelectionScreeners%22%3A%22s_39%22%2C%22quotesDisabled%22%3Atrue%2C%22lastSelectionPortfolios%22%3A%22p_2%22%2C%22comparisonPanels%22%3A%7B%22Portfolio%22%3A%22p_2%22%2C%22Index%22%3A%22%5EDJX%22%2C%22Watchlist%22%3A%22Watchlists%22%2C%22Screener%22%3A%22s_39%22%7D%2C%22lastSelectionWatchlists%22%3A%22w_26%22%2C%22indicesSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Yahoo%20News%22%5D%2C%22newsActive%22%3A%22tickerNews%22%2C%22recentSearchMetrics%22%3A%5B%22Price%22%2C%22EPS%22%2C%22Sales%22%5D%2C%22editPanel%22%3A%22positionsPanel%22%2C%22newsType%22%3A%22marketNews%22%2C%22tableColumns%22%3A%5B%22ticker%22%2C%22rank%22%2C%22score_rank%22%2C%22filter_score%22%2C%22company%22%2C%22cash%22%2C%22currentassets%22%2C%22netppe%22%2C%22intangibles%22%2C%22totalassets%22%2C%22currentliabilities%22%2C%22longtermdebt%22%2C%22totaldebt%22%2C%22totalliabilities%22%2C%22equity%22%2C%22tangiblebookvalue%22%2C%22cash_short_term_p%22%2C%22net_ppe_p%22%2C%22intangibles_p%22%5D%2C%22last_save%22%3A1644769379%2C%22panels%22%3A%7B%22collapsed%22%3A%7B%22chp%22%3Atrue%2C%22ip%22%3Atrue%2C%22mp%22%3Afalse%2C%22qp%22%3Afalse%2C%22conp%22%3Atrue%2C%22fsp%22%3Afalse%7D%2C%22viewportWidth%22%3A%221920%22%2C%22viewportHeight%22%3A%221069%22%2C%22chartPanelHeight%22%3A483%2C%22controlPanelWidth%22%3A296%2C%22insightPanelWidth%22%3A%22485%22%2C%22quoteBoxHeight%22%3A200%2C%22navigationPanelWidth%22%3A277%7D%7D&updateMarket=true&page=1&start=0&limit=250"
headers = {
'authority': 'www.stockrover.com',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="98", "Google Chrome";v="98"',
'x-csrf-token': '7yR4pfI0kAArtjJak535+NJrpB0L212PAbXCg0kbyE4SyjFaQ73sMHJLiqAkPb5nGzfC8KvAa3kTADLAEQXyOQ==',
'sec-ch-ua-mobile': '?0',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'accept': 'application/json',
'x-requested-with': 'XMLHttpRequest',
'sec-ch-ua-platform': '"Windows"',
'origin': 'https://www.stockrover.com',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.stockrover.com/research/table/281/s_39/BTU',
'accept-language': 'en-US,en;q=0.9',
'cookie': 'remember_me_pref=0; user_name=test11964; plan=3; premiumBraintreeKey=MIIBCgKCAQEAzM4LJfrNnBOgRFB1dDJkmqTFCWT2Y%2BksOydD8xDH4R033WUzxbffMZb%2B3dqEyQvOVjLcwFIHByDc4Xwej7enas2E%2FVRyh7Cvyadn7M5zQeRyLcI9Ys5KCozMwxJPc0x76FlXPwiAo1Qlz3RcLb9wGHBag2R51FuTie%2BhVDCgzWajqDCREzRhi%2Fqlt3D%2FxXNo%2FiwJlpOUr%2Fx1QnkkILxgKlq1dD7KJ767O5ojYKXsO%2BV2Bfu7sSD3djsOxQJ1%2FRbaDm2E96EDkWhhOeOpPndQ6IuSl4NmnJg%2Fcq6f8csW8M3Ys%2BMZPFkdxPC4%2FfRM1XC9o76PjpVNBIO%2ByJEELKZedwIDAQAB; lr=1644769628; _Ruby2_session=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%3D--1439f36a7f9362aee4b5b666747a2d63d72e81bd'
}
response = requests.request("POST", url, headers=headers, data=payload)
print(response.json())

The data structure in this case is rather unusual but this looks like it might work for you:
import requests
url = "https://www.stockrover.com/stock_infos/grid?_dc=1644769629231"
payload = "state=%7B%22sortInfo%22%3A%7B%7D%2C%22columns%22%3A%5B77%2C32%2C498%2C500%2C31%2C27%2C499%2C30%2C578%2C28%2C29%2C544%2C181%2C185%2C186%5D%2C%22view%22%3A281%2C%22priorPrimaryColumn%22%3A170%2C%22filterData%22%3A%5B%5D%2C%22name%22%3A%22New%201%22%2C%22cType%22%3A%22Screener%22%2C%22cNode%22%3A%22s_39%22%2C%22cIsFolder%22%3Afalse%2C%22gridSelection%22%3A%22BTU%22%2C%22lastActive%22%3A1396898415%2C%22primaryColumn%22%3A76%2C%22folderDisabledParams%22%3A%7B%22filterData%22%3A%5B%5D%7D%2C%22mainGridDateRange%22%3A%22ytd%22%2C%22groupState%22%3Anull%2C%22moversGridDateRange%22%3A%221_day%22%2C%22peersGridDateRange%22%3A%221_day%22%2C%22lastGridSelections%22%3A%5B%22BTU%22%5D%2C%22lastQuantNode%22%3A%5B%5D%2C%22includeQuotesInTable%22%3Afalse%2C%22includeAllQuotesLastValue%22%3Afalse%2C%22markets%22%3A%7B%22panel%22%3A%22summary%22%7D%2C%22researchPanel%22%3A%22tablePanel%22%2C%22recentSearchTickers%22%3A%5B%22SPY%22%2C%22AMZN%22%2C%22AAPL%22%2C%22s_32%22%2C%22%5ENDX%22%2C%22AXP%22%2C%22XOM%22%2C%22AFL%22%2C%22%5EDJX%22%2C%22AIT%22%2C%22ADVC%22%5D%2C%22quotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22checkedQuotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22dashboard%22%3A%7B%22buttonRef%22%3A%22272%22%7D%2C%22tickerSelectedFeeds%22%3A%5B%22Benzinga%20News%22%2C%22Yahoo%20News%22%5D%2C%22marketSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Stock%20Market%20News%20-%20Investing.com%22%5D%2C%22bondsSelectedFeeds%22%3A%5B%22Bonds%20Strategy%20-%20Investing.com%22%5D%2C%22commoditiesSelectedFeeds%22%3A%5B%22Commodities%20%26%20Futures%20News%20-%20Investing.com%22%2C%22Commodities%20Fundamental%20Analysis%20-%20Investing.com%22%2C%22Commodities%20Strategy%20Analysis%20-%20Investing.com%22%5D%2C%22stocksSelectedFeeds%22%3A%5B%22CNNMoney%20News%22%2C%22Google%20News%22%2C%22Seeking%20Alpha%20Top%20Stories%22%5D%2C%22etfsSelectedFeeds%22%3A%5B%22Economy%20News%20-%20Investing.com%22%2C%22ETF%20Analysis%20-%20Investing.com%22%2C%22Investing%20Ideas%20-%20Investing.com%22%5D%2C%22topPanel%22%3A%22researchPanel%22%2C%22maxRecordsNode%22%3Afalse%2C%22version%22%3A7%2C%22lastGridSelectionsRaw%22%3A%5B%22BTU%22%5D%2C%22lastSelectionScreeners%22%3A%22s_39%22%2C%22quotesDisabled%22%3Atrue%2C%22lastSelectionPortfolios%22%3A%22p_2%22%2C%22comparisonPanels%22%3A%7B%22Portfolio%22%3A%22p_2%22%2C%22Index%22%3A%22%5EDJX%22%2C%22Watchlist%22%3A%22Watchlists%22%2C%22Screener%22%3A%22s_39%22%7D%2C%22lastSelectionWatchlists%22%3A%22w_26%22%2C%22indicesSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Yahoo%20News%22%5D%2C%22newsActive%22%3A%22tickerNews%22%2C%22recentSearchMetrics%22%3A%5B%22Price%22%2C%22EPS%22%2C%22Sales%22%5D%2C%22editPanel%22%3A%22positionsPanel%22%2C%22newsType%22%3A%22marketNews%22%2C%22tableColumns%22%3A%5B%22ticker%22%2C%22rank%22%2C%22score_rank%22%2C%22filter_score%22%2C%22company%22%2C%22cash%22%2C%22currentassets%22%2C%22netppe%22%2C%22intangibles%22%2C%22totalassets%22%2C%22currentliabilities%22%2C%22longtermdebt%22%2C%22totaldebt%22%2C%22totalliabilities%22%2C%22equity%22%2C%22tangiblebookvalue%22%2C%22cash_short_term_p%22%2C%22net_ppe_p%22%2C%22intangibles_p%22%5D%2C%22last_save%22%3A1644769379%2C%22panels%22%3A%7B%22collapsed%22%3A%7B%22chp%22%3Atrue%2C%22ip%22%3Atrue%2C%22mp%22%3Afalse%2C%22qp%22%3Afalse%2C%22conp%22%3Atrue%2C%22fsp%22%3Afalse%7D%2C%22viewportWidth%22%3A%221920%22%2C%22viewportHeight%22%3A%221069%22%2C%22chartPanelHeight%22%3A483%2C%22controlPanelWidth%22%3A296%2C%22insightPanelWidth%22%3A%22485%22%2C%22quoteBoxHeight%22%3A200%2C%22navigationPanelWidth%22%3A277%7D%7D&updateMarket=true&page=1&start=0&limit=250"
headers = {
'authority': 'www.stockrover.com',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="98", "Google Chrome";v="98"',
'x-csrf-token': '7yR4pfI0kAArtjJak535+NJrpB0L212PAbXCg0kbyE4SyjFaQ73sMHJLiqAkPb5nGzfC8KvAa3kTADLAEQXyOQ==',
'sec-ch-ua-mobile': '?0',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'accept': 'application/json',
'x-requested-with': 'XMLHttpRequest',
'sec-ch-ua-platform': '"Windows"',
'origin': 'https://www.stockrover.com',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.stockrover.com/research/table/281/s_39/BTU',
'accept-language': 'en-US,en;q=0.9',
'cookie': 'remember_me_pref=0; user_name=test11964; plan=3; premiumBraintreeKey=MIIBCgKCAQEAzM4LJfrNnBOgRFB1dDJkmqTFCWT2Y%2BksOydD8xDH4R033WUzxbffMZb%2B3dqEyQvOVjLcwFIHByDc4Xwej7enas2E%2FVRyh7Cvyadn7M5zQeRyLcI9Ys5KCozMwxJPc0x76FlXPwiAo1Qlz3RcLb9wGHBag2R51FuTie%2BhVDCgzWajqDCREzRhi%2Fqlt3D%2FxXNo%2FiwJlpOUr%2Fx1QnkkILxgKlq1dD7KJ767O5ojYKXsO%2BV2Bfu7sSD3djsOxQJ1%2FRbaDm2E96EDkWhhOeOpPndQ6IuSl4NmnJg%2Fcq6f8csW8M3Ys%2BMZPFkdxPC4%2FfRM1XC9o76PjpVNBIO%2ByJEELKZedwIDAQAB; lr=1644769628; _Ruby2_session=Q1drcmlhazYvUFZLd0NydnRXUGpoUzArZDlxYWRCcW9sRUx5VDBydWVWRHdGWDZlMnlESURzbldwbFV1L0drbUlKaWt5MXRtaS9iR0ZYZEpPVHQ1N25qRnR1d3FrY0tzQW1qQm9CdTZ3MSs0d2c3MlpuMjRiQWhCOHI1cGNWekZ4cUdJd0ZFcGtpeng3MFlqZjFDUW9RYmpFMU9DeGdGMVZKR1EwMjVhSE9yVHl4VXFtQm9aYVBtNHF5d0pwMjJ1aVlNMUVRUzdnVFZWZ1AxQkY5Q0p6a2RKay9QL05tOWk4cHZiSERtaGRxeTlxTWZnV3Q0cjdwR3RndUtmeUp3QThhMnJaV2dGZjlPUUtjcGRidDhiajRxK2g0RUZTMWNZUDBaeGNCcUVxSDJ1QnZVRlRkWk9tUExJNWN3TDN5T1BQcmhVVGsycStVTzJRaUwvSkk2TnNVZldTOGU3Tm5wQ3RUMy9nazFqbzdrUWtvYzRwQWRpV3dnTVB3YzhodFV2U0FRR3VKdllMY01NZmdOdGtmOEJ4UT09LS1nTXBrYldhQ0pEeWJ3ak9qQjcrTGV3PT0%3D--1439f36a7f9362aee4b5b666747a2d63d72e81bd'
}
response = requests.request("POST", url, headers=headers, data=payload)
stock_info = response.json()['stock_infos']
for info in stock_info:
key = info[0]
for i, sub in enumerate(info[1:], 1):
if sub == key:
print(info[i:])
break
Output:
['AA', 1452.0, 4285.0, 6679.0, 0.0, 14197.0, 2929.0, 1724.0, 1725.0, 8736.0, 3878.0, 3878.0, 10.23, 47.05, None]
['ACH', 1773.84, 7909.0, 18758.17, 788.41, 30523.38, 9252.6, 8782.1, 14242.28, 18580.33, 9038.55, 8250.17, 5.81, 61.46, 2.58]
...and the values for all observed tickers

Added code and now it's not print correctly to CSV file

I have the first code that is working and printing to csv, however it included a lot of data I didn't need. A paragraph of code was then added to only include the data I wanted. The problem is it prints to the screen correctly but still includes all the data in the CSV file. I've tried everything I could think of in this line but it won't either won't print or still prints everything.
data = pd.DataFrame(stock_info)
Could someone show me where I'm going wrong so it will print only the portion I want it to?
Old Working Code
import requests
import pandas as pd
url = "https://www.stockrover.com/stock_infos/grid?_dc=1644769629231"
def stock_data(stock_info):
data = pd.DataFrame(stock_info)
data.to_csv("data.csv", index=False)
payload = "state=%7B%22sortInfo%22%3A%7B%7D%2C%22columns%22%3A%5B77%2C32%2C498%2C500%2C31%2C27%2C499%2C30%2C578%2C28%2C29%2C544%2C181%2C185%2C186%5D%2C%22view%22%3A281%2C%22priorPrimaryColumn%22%3A170%2C%22filterData%22%3A%5B%5D%2C%22name%22%3A%22New%201%22%2C%22cType%22%3A%22Screener%22%2C%22cNode%22%3A%22s_39%22%2C%22cIsFolder%22%3Afalse%2C%22gridSelection%22%3A%22BTU%22%2C%22lastActive%22%3A1396898415%2C%22primaryColumn%22%3A76%2C%22folderDisabledParams%22%3A%7B%22filterData%22%3A%5B%5D%7D%2C%22mainGridDateRange%22%3A%22ytd%22%2C%22groupState%22%3Anull%2C%22moversGridDateRange%22%3A%221_day%22%2C%22peersGridDateRange%22%3A%221_day%22%2C%22lastGridSelections%22%3A%5B%22BTU%22%5D%2C%22lastQuantNode%22%3A%5B%5D%2C%22includeQuotesInTable%22%3Afalse%2C%22includeAllQuotesLastValue%22%3Afalse%2C%22markets%22%3A%7B%22panel%22%3A%22summary%22%7D%2C%22researchPanel%22%3A%22tablePanel%22%2C%22recentSearchTickers%22%3A%5B%22SPY%22%2C%22AMZN%22%2C%22AAPL%22%2C%22s_32%22%2C%22%5ENDX%22%2C%22AXP%22%2C%22XOM%22%2C%22AFL%22%2C%22%5EDJX%22%2C%22AIT%22%2C%22ADVC%22%5D%2C%22quotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22checkedQuotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22dashboard%22%3A%7B%22buttonRef%22%3A%22272%22%7D%2C%22tickerSelectedFeeds%22%3A%5B%22Benzinga%20News%22%2C%22Yahoo%20News%22%5D%2C%22marketSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Stock%20Market%20News%20-%20Investing.com%22%5D%2C%22bondsSelectedFeeds%22%3A%5B%22Bonds%20Strategy%20-%20Investing.com%22%5D%2C%22commoditiesSelectedFeeds%22%3A%5B%22Commodities%20%26%20Futures%20News%20-%20Investing.com%22%2C%22Commodities%20Fundamental%20Analysis%20-%20Investing.com%22%2C%22Commodities%20Strategy%20Analysis%20-%20Investing.com%22%5D%2C%22stocksSelectedFeeds%22%3A%5B%22CNNMoney%20News%22%2C%22Google%20News%22%2C%22Seeking%20Alpha%20Top%20Stories%22%5D%2C%22etfsSelectedFeeds%22%3A%5B%22Economy%20News%20-%20Investing.com%22%2C%22ETF%20Analysis%20-%20Investing.com%22%2C%22Investing%20Ideas%20-%20Investing.com%22%5D%2C%22topPanel%22%3A%22researchPanel%22%2C%22maxRecordsNode%22%3Afalse%2C%22version%22%3A7%2C%22lastGridSelectionsRaw%22%3A%5B%22BTU%22%5D%2C%22lastSelectionScreeners%22%3A%22s_39%22%2C%22quotesDisabled%22%3Atrue%2C%22lastSelectionPortfolios%22%3A%22p_2%22%2C%22comparisonPanels%22%3A%7B%22Portfolio%22%3A%22p_2%22%2C%22Index%22%3A%22%5EDJX%22%2C%22Watchlist%22%3A%22Watchlists%22%2C%22Screener%22%3A%22s_39%22%7D%2C%22lastSelectionWatchlists%22%3A%22w_26%22%2C%22indicesSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Yahoo%20News%22%5D%2C%22newsActive%22%3A%22tickerNews%22%2C%22recentSearchMetrics%22%3A%5B%22Price%22%2C%22EPS%22%2C%22Sales%22%5D%2C%22editPanel%22%3A%22positionsPanel%22%2C%22newsType%22%3A%22marketNews%22%2C%22tableColumns%22%3A%5B%22ticker%22%2C%22rank%22%2C%22score_rank%22%2C%22filter_score%22%2C%22company%22%2C%22cash%22%2C%22currentassets%22%2C%22netppe%22%2C%22intangibles%22%2C%22totalassets%22%2C%22currentliabilities%22%2C%22longtermdebt%22%2C%22totaldebt%22%2C%22totalliabilities%22%2C%22equity%22%2C%22tangiblebookvalue%22%2C%22cash_short_term_p%22%2C%22net_ppe_p%22%2C%22intangibles_p%22%5D%2C%22last_save%22%3A1644769379%2C%22panels%22%3A%7B%22collapsed%22%3A%7B%22chp%22%3Atrue%2C%22ip%22%3Atrue%2C%22mp%22%3Afalse%2C%22qp%22%3Afalse%2C%22conp%22%3Atrue%2C%22fsp%22%3Afalse%7D%2C%22viewportWidth%22%3A%221920%22%2C%22viewportHeight%22%3A%221069%22%2C%22chartPanelHeight%22%3A483%2C%22controlPanelWidth%22%3A296%2C%22insightPanelWidth%22%3A%22485%22%2C%22quoteBoxHeight%22%3A200%2C%22navigationPanelWidth%22%3A277%7D%7D&updateMarket=true&page=1&start=0&limit=250"
headers = {
'authority': 'www.stockrover.com',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="98", "Google Chrome";v="98"',
'x-csrf-token': '7yR4pfI0kAArtjJak535+NJrpB0L212PAbXCg0kbyE4SyjFaQ73sMHJLiqAkPb5nGzfC8KvAa3kTADLAEQXyOQ==',
'sec-ch-ua-mobile': '?0',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'accept': 'application/json',
'x-requested-with': 'XMLHttpRequest',
'sec-ch-ua-platform': '"Windows"',
'origin': 'https://www.stockrover.com',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.stockrover.com/research/table/281/s_39/BTU',
'accept-language': 'en-US,en;q=0.9',
'cookie': 'remember_me_pref=0; user_name=test11964; plan=3; premiumBraintreeKey=MIIBCgKCAQEAzM4LJfrNnBOgRFB1dDJkmqTFCWT2Y%2BksOydD8xDH4R033WUzxbffMZb%2B3dqEyQvOVjLcwFIHByDc4Xwej7enas2E%2FVRyh7Cvyadn7M5zQeRyLcI9Ys5KCozMwxJPc0x76FlXPwiAo1Qlz3RcLb9wGHBag2R51FuTie%2BhVDCgzWajqDCREzRhi%2Fqlt3D%2FxXNo%2FiwJlpOUr%2Fx1QnkkILxgKlq1dD7KJ767O5ojYKXsO%2BV2Bfu7sSD3djsOxQJ1%2FRbaDm2E96EDkWhhOeOpPndQ6IuSl4NmnJg%2Fcq6f8csW8M3Ys%2BMZPFkdxPC4%2FfRM1XC9o76PjpVNBIO%2ByJEELKZedwIDAQAB; lr=1644769628; _Ruby2_session=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%3D--1439f36a7f9362aee4b5b666747a2d63d72e81bd'
}
response = requests.request("POST", url, headers=headers, data=payload)
stock_info = response.json()['stock_infos']
stock_data(stock_info)
New Non-Working Code
import requests
import pandas as pd
url = "https://www.stockrover.com/stock_infos/grid?_dc=1644769629231"
def stock_data(stock_info):
data = pd.DataFrame(stock_info)
data.to_csv("data.csv", index=False)
payload = "state=%7B%22sortInfo%22%3A%7B%7D%2C%22columns%22%3A%5B77%2C32%2C498%2C500%2C31%2C27%2C499%2C30%2C578%2C28%2C29%2C544%2C181%2C185%2C186%5D%2C%22view%22%3A281%2C%22priorPrimaryColumn%22%3A170%2C%22filterData%22%3A%5B%5D%2C%22name%22%3A%22New%201%22%2C%22cType%22%3A%22Screener%22%2C%22cNode%22%3A%22s_39%22%2C%22cIsFolder%22%3Afalse%2C%22gridSelection%22%3A%22BTU%22%2C%22lastActive%22%3A1396898415%2C%22primaryColumn%22%3A76%2C%22folderDisabledParams%22%3A%7B%22filterData%22%3A%5B%5D%7D%2C%22mainGridDateRange%22%3A%22ytd%22%2C%22groupState%22%3Anull%2C%22moversGridDateRange%22%3A%221_day%22%2C%22peersGridDateRange%22%3A%221_day%22%2C%22lastGridSelections%22%3A%5B%22BTU%22%5D%2C%22lastQuantNode%22%3A%5B%5D%2C%22includeQuotesInTable%22%3Afalse%2C%22includeAllQuotesLastValue%22%3Afalse%2C%22markets%22%3A%7B%22panel%22%3A%22summary%22%7D%2C%22researchPanel%22%3A%22tablePanel%22%2C%22recentSearchTickers%22%3A%5B%22SPY%22%2C%22AMZN%22%2C%22AAPL%22%2C%22s_32%22%2C%22%5ENDX%22%2C%22AXP%22%2C%22XOM%22%2C%22AFL%22%2C%22%5EDJX%22%2C%22AIT%22%2C%22ADVC%22%5D%2C%22quotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22checkedQuotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22dashboard%22%3A%7B%22buttonRef%22%3A%22272%22%7D%2C%22tickerSelectedFeeds%22%3A%5B%22Benzinga%20News%22%2C%22Yahoo%20News%22%5D%2C%22marketSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Stock%20Market%20News%20-%20Investing.com%22%5D%2C%22bondsSelectedFeeds%22%3A%5B%22Bonds%20Strategy%20-%20Investing.com%22%5D%2C%22commoditiesSelectedFeeds%22%3A%5B%22Commodities%20%26%20Futures%20News%20-%20Investing.com%22%2C%22Commodities%20Fundamental%20Analysis%20-%20Investing.com%22%2C%22Commodities%20Strategy%20Analysis%20-%20Investing.com%22%5D%2C%22stocksSelectedFeeds%22%3A%5B%22CNNMoney%20News%22%2C%22Google%20News%22%2C%22Seeking%20Alpha%20Top%20Stories%22%5D%2C%22etfsSelectedFeeds%22%3A%5B%22Economy%20News%20-%20Investing.com%22%2C%22ETF%20Analysis%20-%20Investing.com%22%2C%22Investing%20Ideas%20-%20Investing.com%22%5D%2C%22topPanel%22%3A%22researchPanel%22%2C%22maxRecordsNode%22%3Afalse%2C%22version%22%3A7%2C%22lastGridSelectionsRaw%22%3A%5B%22BTU%22%5D%2C%22lastSelectionScreeners%22%3A%22s_39%22%2C%22quotesDisabled%22%3Atrue%2C%22lastSelectionPortfolios%22%3A%22p_2%22%2C%22comparisonPanels%22%3A%7B%22Portfolio%22%3A%22p_2%22%2C%22Index%22%3A%22%5EDJX%22%2C%22Watchlist%22%3A%22Watchlists%22%2C%22Screener%22%3A%22s_39%22%7D%2C%22lastSelectionWatchlists%22%3A%22w_26%22%2C%22indicesSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Yahoo%20News%22%5D%2C%22newsActive%22%3A%22tickerNews%22%2C%22recentSearchMetrics%22%3A%5B%22Price%22%2C%22EPS%22%2C%22Sales%22%5D%2C%22editPanel%22%3A%22positionsPanel%22%2C%22newsType%22%3A%22marketNews%22%2C%22tableColumns%22%3A%5B%22ticker%22%2C%22rank%22%2C%22score_rank%22%2C%22filter_score%22%2C%22company%22%2C%22cash%22%2C%22currentassets%22%2C%22netppe%22%2C%22intangibles%22%2C%22totalassets%22%2C%22currentliabilities%22%2C%22longtermdebt%22%2C%22totaldebt%22%2C%22totalliabilities%22%2C%22equity%22%2C%22tangiblebookvalue%22%2C%22cash_short_term_p%22%2C%22net_ppe_p%22%2C%22intangibles_p%22%5D%2C%22last_save%22%3A1644769379%2C%22panels%22%3A%7B%22collapsed%22%3A%7B%22chp%22%3Atrue%2C%22ip%22%3Atrue%2C%22mp%22%3Afalse%2C%22qp%22%3Afalse%2C%22conp%22%3Atrue%2C%22fsp%22%3Afalse%7D%2C%22viewportWidth%22%3A%221920%22%2C%22viewportHeight%22%3A%221069%22%2C%22chartPanelHeight%22%3A483%2C%22controlPanelWidth%22%3A296%2C%22insightPanelWidth%22%3A%22485%22%2C%22quoteBoxHeight%22%3A200%2C%22navigationPanelWidth%22%3A277%7D%7D&updateMarket=true&page=1&start=0&limit=250"
headers = {
'authority': 'www.stockrover.com',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="98", "Google Chrome";v="98"',
'x-csrf-token': '7yR4pfI0kAArtjJak535+NJrpB0L212PAbXCg0kbyE4SyjFaQ73sMHJLiqAkPb5nGzfC8KvAa3kTADLAEQXyOQ==',
'sec-ch-ua-mobile': '?0',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'accept': 'application/json',
'x-requested-with': 'XMLHttpRequest',
'sec-ch-ua-platform': '"Windows"',
'origin': 'https://www.stockrover.com',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.stockrover.com/research/table/281/s_39/BTU',
'accept-language': 'en-US,en;q=0.9',
'cookie': 'remember_me_pref=0; user_name=test11964; plan=3; premiumBraintreeKey=MIIBCgKCAQEAzM4LJfrNnBOgRFB1dDJkmqTFCWT2Y%2BksOydD8xDH4R033WUzxbffMZb%2B3dqEyQvOVjLcwFIHByDc4Xwej7enas2E%2FVRyh7Cvyadn7M5zQeRyLcI9Ys5KCozMwxJPc0x76FlXPwiAo1Qlz3RcLb9wGHBag2R51FuTie%2BhVDCgzWajqDCREzRhi%2Fqlt3D%2FxXNo%2FiwJlpOUr%2Fx1QnkkILxgKlq1dD7KJ767O5ojYKXsO%2BV2Bfu7sSD3djsOxQJ1%2FRbaDm2E96EDkWhhOeOpPndQ6IuSl4NmnJg%2Fcq6f8csW8M3Ys%2BMZPFkdxPC4%2FfRM1XC9o76PjpVNBIO%2ByJEELKZedwIDAQAB; lr=1644769628; _Ruby2_session=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%3D--1439f36a7f9362aee4b5b666747a2d63d72e81bd'
}
response = requests.request("POST", url, headers=headers, data=payload)
stock_info = response.json()['stock_infos']
stock_data(stock_info)
for info in stock_info:
key = info[0]
for i, sub in enumerate(info[1:], 1):
if sub == key:
print(info[i:])
break

If you don't need to keep those columns just slice them out by adding a line to your original code:
data = pd.DataFrame(stock_info)
data = data.iloc[:, 4:]
In original code:
import requests
import pandas as pd
url = "https://www.stockrover.com/stock_infos/grid?_dc=1644769629231"
def stock_data(stock_info):
data = pd.DataFrame(stock_info)
data = data.iloc[:, 4:]
data.to_csv("data.csv", index=False)
payload = "state=%7B%22sortInfo%22%3A%7B%7D%2C%22columns%22%3A%5B77%2C32%2C498%2C500%2C31%2C27%2C499%2C30%2C578%2C28%2C29%2C544%2C181%2C185%2C186%5D%2C%22view%22%3A281%2C%22priorPrimaryColumn%22%3A170%2C%22filterData%22%3A%5B%5D%2C%22name%22%3A%22New%201%22%2C%22cType%22%3A%22Screener%22%2C%22cNode%22%3A%22s_39%22%2C%22cIsFolder%22%3Afalse%2C%22gridSelection%22%3A%22BTU%22%2C%22lastActive%22%3A1396898415%2C%22primaryColumn%22%3A76%2C%22folderDisabledParams%22%3A%7B%22filterData%22%3A%5B%5D%7D%2C%22mainGridDateRange%22%3A%22ytd%22%2C%22groupState%22%3Anull%2C%22moversGridDateRange%22%3A%221_day%22%2C%22peersGridDateRange%22%3A%221_day%22%2C%22lastGridSelections%22%3A%5B%22BTU%22%5D%2C%22lastQuantNode%22%3A%5B%5D%2C%22includeQuotesInTable%22%3Afalse%2C%22includeAllQuotesLastValue%22%3Afalse%2C%22markets%22%3A%7B%22panel%22%3A%22summary%22%7D%2C%22researchPanel%22%3A%22tablePanel%22%2C%22recentSearchTickers%22%3A%5B%22SPY%22%2C%22AMZN%22%2C%22AAPL%22%2C%22s_32%22%2C%22%5ENDX%22%2C%22AXP%22%2C%22XOM%22%2C%22AFL%22%2C%22%5EDJX%22%2C%22AIT%22%2C%22ADVC%22%5D%2C%22quotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22checkedQuotesBoxTickers%22%3A%5B%22AMZN%22%2C%22AAPL%22%2C%22SPY%22%5D%2C%22dashboard%22%3A%7B%22buttonRef%22%3A%22272%22%7D%2C%22tickerSelectedFeeds%22%3A%5B%22Benzinga%20News%22%2C%22Yahoo%20News%22%5D%2C%22marketSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Stock%20Market%20News%20-%20Investing.com%22%5D%2C%22bondsSelectedFeeds%22%3A%5B%22Bonds%20Strategy%20-%20Investing.com%22%5D%2C%22commoditiesSelectedFeeds%22%3A%5B%22Commodities%20%26%20Futures%20News%20-%20Investing.com%22%2C%22Commodities%20Fundamental%20Analysis%20-%20Investing.com%22%2C%22Commodities%20Strategy%20Analysis%20-%20Investing.com%22%5D%2C%22stocksSelectedFeeds%22%3A%5B%22CNNMoney%20News%22%2C%22Google%20News%22%2C%22Seeking%20Alpha%20Top%20Stories%22%5D%2C%22etfsSelectedFeeds%22%3A%5B%22Economy%20News%20-%20Investing.com%22%2C%22ETF%20Analysis%20-%20Investing.com%22%2C%22Investing%20Ideas%20-%20Investing.com%22%5D%2C%22topPanel%22%3A%22researchPanel%22%2C%22maxRecordsNode%22%3Afalse%2C%22version%22%3A7%2C%22lastGridSelectionsRaw%22%3A%5B%22BTU%22%5D%2C%22lastSelectionScreeners%22%3A%22s_39%22%2C%22quotesDisabled%22%3Atrue%2C%22lastSelectionPortfolios%22%3A%22p_2%22%2C%22comparisonPanels%22%3A%7B%22Portfolio%22%3A%22p_2%22%2C%22Index%22%3A%22%5EDJX%22%2C%22Watchlist%22%3A%22Watchlists%22%2C%22Screener%22%3A%22s_39%22%7D%2C%22lastSelectionWatchlists%22%3A%22w_26%22%2C%22indicesSelectedFeeds%22%3A%5B%22Google%20News%22%2C%22Yahoo%20News%22%5D%2C%22newsActive%22%3A%22tickerNews%22%2C%22recentSearchMetrics%22%3A%5B%22Price%22%2C%22EPS%22%2C%22Sales%22%5D%2C%22editPanel%22%3A%22positionsPanel%22%2C%22newsType%22%3A%22marketNews%22%2C%22tableColumns%22%3A%5B%22ticker%22%2C%22rank%22%2C%22score_rank%22%2C%22filter_score%22%2C%22company%22%2C%22cash%22%2C%22currentassets%22%2C%22netppe%22%2C%22intangibles%22%2C%22totalassets%22%2C%22currentliabilities%22%2C%22longtermdebt%22%2C%22totaldebt%22%2C%22totalliabilities%22%2C%22equity%22%2C%22tangiblebookvalue%22%2C%22cash_short_term_p%22%2C%22net_ppe_p%22%2C%22intangibles_p%22%5D%2C%22last_save%22%3A1644769379%2C%22panels%22%3A%7B%22collapsed%22%3A%7B%22chp%22%3Atrue%2C%22ip%22%3Atrue%2C%22mp%22%3Afalse%2C%22qp%22%3Afalse%2C%22conp%22%3Atrue%2C%22fsp%22%3Afalse%7D%2C%22viewportWidth%22%3A%221920%22%2C%22viewportHeight%22%3A%221069%22%2C%22chartPanelHeight%22%3A483%2C%22controlPanelWidth%22%3A296%2C%22insightPanelWidth%22%3A%22485%22%2C%22quoteBoxHeight%22%3A200%2C%22navigationPanelWidth%22%3A277%7D%7D&updateMarket=true&page=1&start=0&limit=250"
headers = {
'authority': 'www.stockrover.com',
'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="98", "Google Chrome";v="98"',
'x-csrf-token': '7yR4pfI0kAArtjJak535+NJrpB0L212PAbXCg0kbyE4SyjFaQ73sMHJLiqAkPb5nGzfC8KvAa3kTADLAEQXyOQ==',
'sec-ch-ua-mobile': '?0',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
'content-type': 'application/x-www-form-urlencoded; charset=UTF-8',
'accept': 'application/json',
'x-requested-with': 'XMLHttpRequest',
'sec-ch-ua-platform': '"Windows"',
'origin': 'https://www.stockrover.com',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.stockrover.com/research/table/281/s_39/BTU',
'accept-language': 'en-US,en;q=0.9',
'cookie': 'remember_me_pref=0; user_name=test11964; plan=3; premiumBraintreeKey=MIIBCgKCAQEAzM4LJfrNnBOgRFB1dDJkmqTFCWT2Y%2BksOydD8xDH4R033WUzxbffMZb%2B3dqEyQvOVjLcwFIHByDc4Xwej7enas2E%2FVRyh7Cvyadn7M5zQeRyLcI9Ys5KCozMwxJPc0x76FlXPwiAo1Qlz3RcLb9wGHBag2R51FuTie%2BhVDCgzWajqDCREzRhi%2Fqlt3D%2FxXNo%2FiwJlpOUr%2Fx1QnkkILxgKlq1dD7KJ767O5ojYKXsO%2BV2Bfu7sSD3djsOxQJ1%2FRbaDm2E96EDkWhhOeOpPndQ6IuSl4NmnJg%2Fcq6f8csW8M3Ys%2BMZPFkdxPC4%2FfRM1XC9o76PjpVNBIO%2ByJEELKZedwIDAQAB; lr=1644769628; _Ruby2_session=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%3D--1439f36a7f9362aee4b5b666747a2d63d72e81bd'
}
response = requests.request("POST", url, headers=headers, data=payload)
stock_info = response.json()['stock_infos']
stock_data(stock_info)

The added block of code is added after the csv file has already been written.
You have other problems as well but that is the most obvious at the moment.
it should be closer to...
...
for info in stock_info:
key = info[0]
for i, sub in enumerate(info[1:], 1):
if sub == key:
print(info[i:])
break
stock_data(stock_info)
Also the added block of code doesn't actually make any changes to the data, it only changes what ends up getting printed. Whatever changes you want made to the file need to be made to stock_info.

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