CSV Reader error: The row containing the table headers (row number 0) was not part of the table

NYGiants · October 9, 2024, 10:46pm

Hello all,

I am having trouble reading a CSV file from a URL. Hoping someone can help.

File looks simple (see below sample rows)

Date, employees_present
2024-09-01, 56
2024-09-02, 51

I have a URL that has the location of this CSV file
I am feeding this URL to a flow variable
I convert the flow variable type to “Path” from the default type which was string
I then use this flow variable in the CSV reader node with the following configuration
–Read from: Custom/KNIME URL
–URL is populated with the flow variable that was earlier configured
–This configuration looks perfect and I can see Knime is pulling in the correct URL to the csv in the URL field

However when running it gives me an error that says: The row containing the table headers (row number 0) was not part of the table

I tried the below to rule out issues with the file structure:

Downloaded the same file by entering the same URL in Chrome. File was downloaded to downloads folder
Used CSV reader node to read the same file from downloads folder using “Local File System” as Read From option
In this method where it is reading from local system, it works perfectly

Not sure what is wrong and why the same exact file will work from local folder but not from URL.

Kindly help

MartinDDDD · October 10, 2024, 6:19am

Hey there and welcome to the forum!

Is it possible to share some more information? I know you have described it fairly thoroughly, but I did some quick experiments using two .csv files i found on google:
This one works like a charm:
https://www.stats.govt.nz/assets/Uploads/Annual-enterprise-survey/Annual-enterprise-survey-2023-financial-year-provisional/Download-data/annual-enterprise-survey-2023-financial-year-provisional.csv

This one doesn’t work because it looks like despite the fact that the URL suggests a direct path to a .csv file, the content that gets pulled seems to be HTML:

github.com

codeforamerica/ohana-api/blob/master/data/sample-csv/addresses.csv

id,location_id,address_1,address_2,city,state_province,postal_code,country
1,1,2600 Middlefield Road,,Redwood City,CA,94063,US
2,2,24 Second Avenue,,San Mateo,CA,94401,US
3,3,24 Second Avenue,,San Mateo,CA,94403,US
4,4,24 Second Avenue,,San Mateo,CA,94401,US
5,5,24 Second Avenue,,San Mateo,CA,94401,US
6,6,800 Middle Avenue,,Menlo Park,CA,94025-9881,US
7,7,500 Arbor Road,,Menlo Park,CA,94025,US
8,8,800 Middle Avenue,,Menlo Park,CA,94025-9881,US
9,9,2510 Middlefield Road,,Redwood City,CA,94063,US
10,10,1044 Middlefield Road,,Redwood City,CA,94063,US
11,11,2140 Euclid Avenue.,,Redwood City,CA,94061,US
12,12,1044 Middlefield Road,2nd Floor,Redwood City,CA,94063,US
13,13,399 Marine Parkway.,,Redwood City,CA,94065,US
14,14,660 Veterans Blvd.,,Redwood City,CA,94063,US
15,15,1500 Valencia Street,,San Francisco,CA,94110,US
16,16,1161 South Bernardo,,Sunnyvale,CA,94087,US
17,17,409 South Spruce Avenue,,South San Francisco,CA,94080,US
18,18,114 Fifth Avenue,,Redwood City,CA,94063,US
19,19,19 West 39th Avenue,,San Mateo,CA,94403,US

This file has been truncated. show original

So one theory is that something similar happens in your case…