Related
I have the following API request that I then clean and sort the data:
Base_URL = "https://api.jao.eu/OWSMP/getauctions?"
headers = {
"AUTH_API_KEY": "06e690fb-697b-4ab2-9325-4268cbd14502"
}
params = {
"horizon":"Daily",
"corridor":"IF1-FR-GB",
"fromdate":"2021-01-01"
}
data = "results"
r = requests.get(Base_URL, headers=headers, params=params, json=data)
j = r.json()
df = pd.DataFrame.from_dict(j)
df=df.explode('results')
df=df.join(pd.json_normalize(df.pop('results')).add_suffix('_new'))
df.drop(['ftroption','identification','horizonName','periodToBeSecuredStart','periodToBeSecuredStop','bidGateOpening','bidGateClosure','isBidGateOpen','atcGateOpening','atcGateClosure','marketPeriodStop','disputeSubmissionGateOpening','disputeSubmissionGateClosure','disputeProcessGateOpening','disputeProcessGateClosure','ltResaleGateOpening','ltResaleGateClosure','maintenances','xnRule','winningParties','operationalMessage','products','lastDataUpdate','cancelled','comment_new','corridorCode_new','productIdentification_new','additionalMessage_new'], axis=1, inplace=True)
df
I then sort it by the date column, which is why it is important to be able to run it for every month, as I need to repeat this process and hopefully automate it in the future:
df['new'] = pd.to_datetime(df['marketPeriodStart']).dt.strftime('%d/%m/%Y')
df = df = df.sort_values(by='new', ascending=True)
df
As the API can only run in one month periods, I am trying to loop-through it to be able to change the "fromdate" param to every month. I can then change the "corridor" param and I would be able to repeat the above for-loop. Thank you!
Get all data:
import pandas as pd
import requests
Base_URL = "https://api.jao.eu/OWSMP/getauctions?"
headers = {
"AUTH_API_KEY": "api_key"
}
final_df=pd.DataFrame() #all data will store here.
#create dates like 2022-01-01, 2022-08-01...
year=['2021','2022']
month=list(range(1,13))
dates=[]
errors=[]
for i in year:
for j in month:
if i =='2022' and j in [11,12]:
pass
else:
dates.append(i+ '-' + f'{j:02}' + '-01')
#dates are ready. let's request for each date and append data to final df.
for i in dates:
params = {
"horizon":"Daily",
"corridor":"IF1-FR-GB",
"fromdate":i
}
data = "results"
r = requests.get(Base_URL, headers=headers, params=params, json=data)
j = r.json()
try:
df = pd.DataFrame.from_dict(j)
final_df=final_df.append(df)
except:
errors.append(j)
#now, let's do same process for final data.
final_df=final_df.explode('results')
final_df=final_df.join(pd.json_normalize(final_df.pop('results')).add_suffix('_new'))
final_df.drop(['ftroption','identification','horizonName','periodToBeSecuredStart','periodToBeSecuredStop','bidGateOpening','bidGateClosure','isBidGateOpen','atcGateOpening','atcGateClosure','marketPeriodStop','disputeSubmissionGateOpening','disputeSubmissionGateClosure','disputeProcessGateOpening','disputeProcessGateClosure','ltResaleGateOpening','ltResaleGateClosure','maintenances','xnRule','winningParties','operationalMessage','products','lastDataUpdate','cancelled','comment_new','corridorCode_new','productIdentification_new','additionalMessage_new'], axis=1, inplace=True)
After you get all the data, if you want to get it automatically every month, you should set it to run on the first day of every month (if you want a different day, you should change the day value in timedelta).
import pandas as pd
import requests
Base_URL = "https://api.jao.eu/OWSMP/getauctions?"
headers = {
"AUTH_API_KEY": "api_key"
}
from datetime import datetime,timedelta
now=(datetime.today() - timedelta(days=2)).strftime('%Y-%m-01')
params = {
"horizon":"Daily",
"corridor":"IF1-FR-GB",
"fromdate":now
}
data = "results"
r = requests.get(Base_URL, headers=headers, params=params, json=data)
j = r.json()
df = pd.DataFrame.from_dict(j)
df=df.append(df)
df=df.explode('results')
df=df.join(pd.json_normalize(df.pop('results')).add_suffix('_new'))
df.drop(['ftroption','identification','horizonName','periodToBeSecuredStart','periodToBeSecuredStop','bidGateOpening','bidGateClosure','isBidGateOpen','atcGateOpening','atcGateClosure','marketPeriodStop','disputeSubmissionGateOpening','disputeSubmissionGateClosure','disputeProcessGateOpening','disputeProcessGateClosure','ltResaleGateOpening','ltResaleGateClosure','maintenances','xnRule','winningParties','operationalMessage','products','lastDataUpdate','cancelled','comment_new','corridorCode_new','productIdentification_new','additionalMessage_new'], axis=1, inplace=True)
Probably this is a simple question, but my experience in for loop is very limited.
I was trying to adapt the solution in this page https://www.mediawiki.org/wiki/API:Geosearch with some simple examples that i have, but the result is not what i expected.
For example:
I have this simple data frame:
df= pd.DataFrame({'City':['Sesimbra','Ciudad Juárez','31100 Treviso','Ramada Portugal','Olhão'],
'Country':['Portugal','México','Itália','Portugal','Portugal']})
I created a list based on cities:
lista_cidades = list(df['City'])
and i would like to iterate over this list to get the coordinates (decimal, preferably)
So far i tried this approach:
import requests
lng_dict = {}
lat_dict = {}
S = requests.Session()
URL = "https://en.wikipedia.org/w/api.php"
PARAMS = {
"action": "query",
"format": "json",
"titles": [lista_cidades],
"prop": "coordinates"
}
R = S.get(url=URL, params=PARAMS)
DATA = R.json()
PAGES = DATA['query']['pages']
for i in range(len(lista_cidades)):
for k, v in PAGES.items():
try:
lat_dict[lista_cidades[i]] = str(v['coordinates'][0]['lat'])
lng_dict[lista_cidades[i]] = str(v['coordinates'][0]['lon'])
except:
pass
but it looks like the code doesn't iterate over the list and always returns the same coordinate
For example, when i call the dictionary with latitude coordinates, this is what i get
lng_dict
{'Sesimbra': '-7.84166667',
'Ciudad Juárez': '-7.84166667',
'31100 Treviso': '-7.84166667',
'Ramada Portugal': '-7.84166667',
'Olhão': '-7.84166667'}
What should i do to solve this?
Thanks in advance
I think the query returns only one result, it will take only the last city from you list (in your cas the "Olhão" coordinates).
You can check it by logging the DATA content.
I do not know about wikipedia API, but either your call lack a parameter (documentation should give you the information) or you have to call the API for each city like :
import pandas as pd
import requests
df = pd.DataFrame({'City': ['Sesimbra', 'Ciudad Juárez', '31100 Treviso', 'Ramada Portugal', 'Olhão'],
'Country': ['Portugal', 'México', 'Itália', 'Portugal', 'Portugal']})
lista_cidades = list(df['City'])
lng_dict = {}
lat_dict = {}
S = requests.Session()
URL = "https://en.wikipedia.org/w/api.php"
for city in lista_cidades:
PARAMS = {
"action": "query",
"format": "json",
"titles": city,
"prop": "coordinates"
}
R = S.get(url=URL, params=PARAMS)
DATA = R.json()
PAGES = DATA['query']['pages']
for k, v in PAGES.items():
try:
lat_dict[city] = str(v['coordinates'][0]['lat'])
lng_dict[city] = str(v['coordinates'][0]['lon'])
except:
pass
I am trying to extract the "mobility index" values for each state and county from this webpage:
https://www.cuebiq.com/visitation-insights-mobility-index/
The preferred output would be a panel data of place (state/county) by date for all available places and dates.
There is another thread (How can I scrape tooltips value from a Tableau graph embedded in a webpage) with a similar question. I tried to follow the solution there but it doesn't seem to work for my case.
Thanks a lot in advance.
(A way that I have tried is to download PDF files generated from Tableau, which would contain all counties' value on a specific date. However, I still need to find a way to make request for each date in the data. Anyway, let me know if you have a better idea than this route).
This tableau data url doesn't return any data. In fact, it only render images of the values (canvas probably) and I'm guessing it detects click based on coordinate. Probably, it's made this way to cache the value and render quickly.
But when you click on a state, it actually returns data but it seems it doesn't always returns the result for the state (but works the individual county).
The solution I've found is to use the tooltip to get the data for the state. When you click the state, it generates a request like this :
POST https://public.tableau.com/{path}/{session_id}/commands/tabsrv/render-tooltip-server
with the following form param :
worksheet: US Map - State - CMI
dashboard: CMI
tupleIds: [18]
vizRegionRect: {"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":null}
allowHoverActions: false
allowPromptText: true
allowWork: false
useInlineImages: true
where tupleIds: [18] refers to the index of the state in a list of states in reverse alphabetical order like this :
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
It gives a json with the html of the tooltip which has the CMI and YoY values you want to extract :
{
"vqlCmdResponse": {
"cmdResultList": [{
"commandName": "tabsrv:render-tooltip-server",
"commandReturn": {
"tooltipText": "{\"htmlTooltip\": \"<HTML HERE WITH THE VALUES>\"}]},\"overlayAnchors\":[]}"
}
}]
}
}
The only caveat is that you'll hava to make one request per state :
import requests
from bs4 import BeautifulSoup
import json
import time
data_host = "https://public.tableau.com"
r = requests.get(
f"{data_host}/views/CMI-2_0/CMI",
params= {
":showVizHome":"no",
}
)
soup = BeautifulSoup(r.text, "html.parser")
tableauData = json.loads(soup.find("textarea",{"id": "tsConfigContainer"}).text)
dataUrl = f'{data_host}{tableauData["vizql_root"]}/bootstrapSession/sessions/{tableauData["sessionid"]}'
r = requests.post(dataUrl, data= {
"sheet_id": tableauData["sheetId"],
})
data = []
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
for stateIndex, state in enumerate(stateNames):
time.sleep(0.5) #for throttling
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabsrv/render-tooltip-server',
data = {
"worksheet": "US Map - State - CMI",
"dashboard": "CMI",
"tupleIds": f"[{stateIndex+1}]",
"vizRegionRect": json.dumps({"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":None}),
"allowHoverActions": "false",
"allowPromptText": "true",
"allowWork": "false",
"useInlineImages": "true"
})
tooltip = json.loads(r.json()["vqlCmdResponse"]["cmdResultList"][0]["commandReturn"]["tooltipText"])["htmlTooltip"]
soup = BeautifulSoup(tooltip, "html.parser")
rows = [
t.find("tr").find_all("td")
for t in soup.find_all("table")
]
entry = { "state": state }
for row in rows:
if (row[0].text == "Mobility Index:"):
entry["CMI"] = "".join([t.text.strip() for t in row[1:]])
if row[0].text == "YoY (%):":
entry["YoY"] = "".join([t.text.strip() for t in row[1:]])
print(entry)
data.append(entry)
print(data)
Try this on repl.it
To get the county information it's the same as this post using the select endpoint which gives you the data with the same format as the post you've linked in your question
The following will extract data for all county and state :
import requests
from bs4 import BeautifulSoup
import json
import time
data_host = "https://public.tableau.com"
worksheet = "US Map - State - CMI"
dashboard = "CMI"
r = requests.get(
f"{data_host}/views/CMI-2_0/CMI",
params= {
":showVizHome":"no",
}
)
soup = BeautifulSoup(r.text, "html.parser")
tableauData = json.loads(soup.find("textarea",{"id": "tsConfigContainer"}).text)
dataUrl = f'{data_host}{tableauData["vizql_root"]}/bootstrapSession/sessions/{tableauData["sessionid"]}'
r = requests.post(dataUrl, data= {
"sheet_id": tableauData["sheetId"],
})
data = []
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
for stateIndex, state in enumerate(stateNames):
time.sleep(0.5) #for throttling
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabsrv/render-tooltip-server',
data = {
"worksheet": worksheet,
"dashboard": dashboard,
"tupleIds": f"[{stateIndex+1}]",
"vizRegionRect": json.dumps({"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":None}),
"allowHoverActions": "false",
"allowPromptText": "true",
"allowWork": "false",
"useInlineImages": "true"
})
tooltip = json.loads(r.json()["vqlCmdResponse"]["cmdResultList"][0]["commandReturn"]["tooltipText"])["htmlTooltip"]
soup = BeautifulSoup(tooltip, "html.parser")
rows = [
t.find("tr").find_all("td")
for t in soup.find_all("table")
]
entry = { "state": state }
for row in rows:
if (row[0].text == "Mobility Index:"):
entry["CMI"] = "".join([t.text.strip() for t in row[1:]])
if row[0].text == "YoY (%):":
entry["YoY"] = "".join([t.text.strip() for t in row[1:]])
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabdoc/select',
data = {
"worksheet": worksheet,
"dashboard": dashboard,
"selection": json.dumps({
"objectIds":[stateIndex+1],
"selectionType":"tuples"
}),
"selectOptions": "select-options-simple"
})
entry["county_data"] = r.json()["vqlCmdResponse"]["layoutStatus"]["applicationPresModel"]["dataDictionary"]["dataSegments"]
print(entry)
data.append(entry)
print(data)
When I query the AdWords API to get search volume data and trends through their TargetingIdeaSelector using the Python client library the returned data looks like this:
(TargetingIdeaPage){
totalNumEntries = 1
entries[] =
(TargetingIdea){
data[] =
(Type_AttributeMapEntry){
key = "KEYWORD_TEXT"
value =
(StringAttribute){
Attribute.Type = "StringAttribute"
value = "keyword phrase"
}
},
(Type_AttributeMapEntry){
key = "TARGETED_MONTHLY_SEARCHES"
value =
(MonthlySearchVolumeAttribute){
Attribute.Type = "MonthlySearchVolumeAttribute"
value[] =
(MonthlySearchVolume){
year = 2016
month = 2
count = 2900
},
...
(MonthlySearchVolume){
year = 2015
month = 3
count = 2900
},
}
},
},
}
This isn't JSON and appears to just be a messy Python list. What's the easiest way to flatten the monthly data into a Pandas dataframe with a structure like this?
Keyword | Year | Month | Count
keyword phrase 2016 2 10
The output is a sudsobject. I found that this code does the trick:
import suds.sudsobject as sudsobject
import pandas as pd
a = [sudsobject.asdict(x) for x in output]
df = pd.DataFrame(a)
Addendum: This was once correct but new versions of the API (I tested
201802) now return a zeep.objects. However, zeep.helpers.serialize_object should do the same trick.
link
Here's the complete code that I used to query the TargetingIdeaSelector, with requestType STATS, and the method I used to parse the data to a useable dataframe; note the section starting "Parse results to pandas dataframe" as this takes the output given in the question above and converts it to a dataframe. Probably not the fastest or best, but it works! Tested with Python 2.7.
"""This code pulls trends for a set of keywords, and parses into a dataframe.
The LoadFromStorage method is pulling credentials and properties from a
"googleads.yaml" file. By default, it looks for this file in your home
directory. For more information, see the "Caching authentication information"
section of our README.
"""
from googleads import adwords
import pandas as pd
adwords_client = adwords.AdWordsClient.LoadFromStorage()
PAGE_SIZE = 10
# Initialize appropriate service.
targeting_idea_service = adwords_client.GetService(
'TargetingIdeaService', version='v201601')
# Construct selector object and retrieve related keywords.
offset = 0
stats_selector = {
'searchParameters': [
{
'xsi_type': 'RelatedToQuerySearchParameter',
'queries': ['donald trump', 'bernie sanders']
},
{
# Language setting (optional).
# The ID can be found in the documentation:
# https://developers.google.com/adwords/api/docs/appendix/languagecodes
'xsi_type': 'LanguageSearchParameter',
'languages': [{'id': '1000'}],
},
{
# Location setting
'xsi_type': 'LocationSearchParameter',
'locations': [{'id': '1027363'}] # Burlington,Vermont
}
],
'ideaType': 'KEYWORD',
'requestType': 'STATS',
'requestedAttributeTypes': ['KEYWORD_TEXT', 'TARGETED_MONTHLY_SEARCHES'],
'paging': {
'startIndex': str(offset),
'numberResults': str(PAGE_SIZE)
}
}
stats_page = targeting_idea_service.get(stats_selector)
##########################################################################
# Parse results to pandas dataframe
stats_pd = pd.DataFrame()
if 'entries' in stats_page:
for stats_result in stats_page['entries']:
stats_attributes = {}
for stats_attribute in stats_result['data']:
#print (stats_attribute)
if stats_attribute['key'] == 'KEYWORD_TEXT':
kt = stats_attribute['value']['value']
else:
for i, val in enumerate(stats_attribute['value'][1]):
data = {'keyword': kt,
'year': val['year'],
'month': val['month'],
'count': val['count']}
data = pd.DataFrame(data, index = [i])
stats_pd = stats_pd.append(data, ignore_index=True)
print(stats_pd)
I have below data in JSON format, I have started with code below which throws a KEY ERROR.
Not sure how to get all data listed in headers section.
I know I am not doing it right in json_obj['offers'][0]['pkg']['Info']: but not sure how to do it correctly.
how can I get to different nodes like info,PricingInfo,Flt_Info etc?
{
"offerInfo":{
"siteID":"1",
"language":"en_US",
"currency":"USD"
},
"offers":{
"pkg":[
{
"offerDateRange":{
"StartDate":[
2015,
11,
8
],
"EndDate":[
2015,
11,
14
]
},
"Info":{
"Id":"111"
},
"PricingInfo":{
"BaseRate":1932.6
},
"flt_Info":{
"Carrier":"AA"
}
}
]
}
}
import os
import json
import csv
f = open('api.csv','w')
writer = csv.writer(f,delimiter = '~')
headers = ['Id' , 'StartDate', 'EndDate', 'Id', 'BaseRate', 'Carrier']
default = ''
writer.writerow(headers)
string = open('data.json').read().decode('utf-8')
json_obj = json.loads(string)
for pkg in json_obj['offers'][0]['pkg']['Info']:
row = []
row.append(json_obj['id']) # just to test,but I need column values listed in header section
writer.writerow(row)
It looks like you're accessing the json incorrectly. After you have accessed json_obj['offers'], you accessed [0], but there is no array there. json_obj['offers'] gives you another dictionary.
For example, to get PricingInfo like you asked, access like this:
json_obj['offers']['pkg'][0]['PricingInfo']
or 11 from the StartDate like this:
json_obj['offers']['pkg'][0]['offerDateRange']['StartDate'][1]
And I believe you get the KEY ERROR because you access [0] in the dictionary, which since that isn't a key, you get the error.
try to substitute this piece of code:
for pkg in json_obj['offers'][0]['pkg']['Info']:
row = []
row.append(json_obj['id']) # just to test,but I need column values listed in header section
writer.writerow(row)
With this:
for pkg in json_obj['offers']['pkg']:
row.append(pkg['Info']['Id'])
year = pkg['offerDateRange']['StartDate'][0]
month = pkg['offerDateRange']['StartDate'][1]
day = pkg['offerDateRange']['StartDate'][2]
StartDate = "%d-%d-%d" % (year,month,day)
print StartDate
writer.writerow(row)
Try this
import os
import json
import csv
string = open('data.json').read().decode('utf-8')
json_obj = json.loads(string)
print json_obj["offers"]["pkg"][0]["Info"]["Id"]
print str(json_obj["offers"]["pkg"][0]["offerDateRange"]["StartDate"][0]) +'-'+ str(json_obj["offers"]["pkg"][0]["offerDateRange"]["StartDate"][1])+'-'+str(json_obj["offers"]["pkg"][0]
["offerDateRange"]["StartDate"][2])
print str(json_obj["offers"]["pkg"][0]["offerDateRange"]["EndDate"][0]) +'-'+ str(json_obj["offers"]["pkg"][0]["offerDateRange"]["EndDate"][1])+'-'+str(json_obj["offers"]["pkg"][0]
["offerDateRange"]["EndDate"][2])
print json_obj["offers"]["pkg"][0]["Info"]["Id"]
print json_obj["offers"]["pkg"][0]["PricingInfo"]["BaseRate"]
print json_obj["offers"]["pkg"][0]["flt_Info"]["Carrier"]