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Error: No Columns to parse from file #88
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Hey @hershey024 I'm able to reproduce your results if I create a In my screenshot I'm doing this by setting an actual field to be filtered by a value which does not exist, which results in 0 results. Also in my screenshot is an example of a successful attempt, where the filters were performed on valid field/values and the result set returned actual data. This suggests to me that your combination of filters may have at least one incorrect value. When a My first guess would be that the area code might be incorrect. Is it possible you have aliased your area codes in Tableau? For example, I typically would see area codes like Here is a screenshot of my Hope that helps! |
Hi @divinorum-webb, thanks for your help. I checked and changed the area code value and the filter is working fine, but the date filter is still throwing EmptyDataError. I entered the date in yyyy-mm-dd format. Also checked the underlying query to verify the original column name(changing to it) but with no luck. .twb file also displays the format in the same way above. Any further suggestions? |
from tableau_api_lib import TableauServerConnection
from tableau_api_lib.utils import querying, flatten_dict_column
import pandas as pd
from sqlalchemy import create_engine
import urllib
import io
Login through U/P, not using token
tableau_server_config = {
'tableau_dev' : {
'server': '',
'api_version': '3.14',
'username':'',
'password':'',
'site_name': '',
'site_url': ''
}
}
Date_filter = urllib.parse.quote('Ext Date')
Month_filter = urllib.parse.quote('Relevant Month')
Code = urllib.parse.quote('Area Code')
conn = TableauServerConnection(config_json = tableau_server_config, env = 'tableau_dev', ssl_verify = False)
response = conn.sign_in()
response
Ext_Date = urllib.parse.quote("2022-07-04")
Relevant_Month = urllib.parse.quote("2022-06-01")
Area_Code = urllib.parse.quote("IND")
param_dict = { "Ext Date": f"vf_{Date_filter}={Ext_Date}",
"Relevant Month": f"vf_{Month_filter}={Relevant_Month}"},
"Area Code": f"vf_{Code}={Area_Code}" }
views_df = querying.get_views_dataframe(conn)
view_df = flatten_dict_column(views_df, keys = ["name", "id"], col_name="workbook")
views_df.head(10)
views_df = views_df[views_df["workbook_name"] == "Month Results"]
views_df_new = views_df[views_df["viewUrlName"] == "Results"]
views_df.head(10)
VIEW_ID = "6v2q12-baa4-3436-v2ws-aswdtgfcqagh"
views_name_df = querying.get_view_data_dataframe(conn, view_id=VIEW_ID, parameter_dict=param_dict)
views_name_df.head(10)
db_connect = create_engine('mqsql+mysqlconnector://----')
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