Hey guys.
Im running the lastest Streamlit version.
I have a Pandas Dataframe with datetime column
When I use pd.groupby, the table is always showing the year both in the Year and Month Index
Before (streamlit == 0.81.1) it was fine
Hi Joaocassis,
Did that code work for you? I used it and tried many other options (like : df_H45.columns=[‘culture_principale’,‘culture_precedente’,‘median_0_45’]) but i got an error:
ValueError: Length of names must match number of levels in MultiIndex.
ValueError: Length mismatch: Expected axis has 1 elements, new values have 3 elements
the dataframe result of group by is fine in python and i can download it correctly
It is only in streamlit that it hide the name of headers even when i download it from my streamlit app the result is one only column wich is the calculated result of my group by
Thanks for stopping by! We use cookies to help us understand how you interact with our website.
By clicking “Accept all”, you consent to our use of cookies. For more information, please see our privacy policy.
Cookie settings
Strictly necessary cookies
These cookies are necessary for the website to function and cannot be switched off. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms.
Performance cookies
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us understand how visitors move around the site and which pages are most frequently visited.
Functional cookies
These cookies are used to record your choices and settings, maintain your preferences over time and recognize you when you return to our website. These cookies help us to personalize our content for you and remember your preferences.
Targeting cookies
These cookies may be deployed to our site by our advertising partners to build a profile of your interest and provide you with content that is relevant to you, including showing you relevant ads on other websites.