Best Of
Re: Discrepancy in Filter Responsiveness Across Charts in DOMO Dashboard
If this is a page filter, you'll need to edit the dashboard, click the wrench on the card that isn't responding and make sure "allow filtering" is selected in Filter Exceptions.
If this is a filter card, you'll need to edit the dashboard, click the wrench icon on the filter card and make sure that all 7 cards on the page are selected in the "change interaction" section.
If neither of those remedy the problem, check to see if the 2 cards use the same dataset as the other cards since column names can vary across datasets.
jessdoe
Re: Tab Autocomplete Messed Up
Hi @nmizzell,
What an interesting question. I think this isn't a Domo issue, but a configuration issue based on your browser. Because the Tab button is really just a command that says to go to the next thing rather than autocomplete something written.
Don't know if this helps, but this is an article on turning off autocomplete, but I think it's more for like addresses and CC info: https://support.mindbodyonline.com/s/article/203260523-How-to-disable-the-form-autofill-feature-in-your-browser?language=en_US
Re: Pydomo: Error with 'ds_get'
the ds_get function doesn't allow for any encoding other than the default utf8. Two options here:
- Override the Domo class and write your own ds_get function to handle the latin1 encoding you have
- Bypass using the ds_get and just call the dataset.data_export function to return the data, then call pandas read_csv on your csv string and pass in the encoding='latin1' as a parameter.
Here's a modified ds_get function:
def ds_get(self, dataset_id, encoding='utf-8'):
"""
Export data to pandas Dataframe
>>> df = domo.ds_get('80268aef-e6a1-44f6-a84c-f849d9db05fb')
>>> print(df.head())
:Parameters:
- `dataset_id`: id of a dataset (str)
:Returns:
pandas dataframe
"""
csv_download = self.datasets.data_export(dataset_id, include_csv_header=True)
content = StringIO(csv_download)
df = read_csv(content, encoding=encoding)
# Convert to dates or datetimes if possible
for col in df.columns:
if df[col].dtype == 'object':
try:
df[col] = to_datetime(df[col])
except ValueError:
pass
except TypeError:
pass
return df


