Hi,
I tried to drop, but df.drop seems to work only on the “regular” columns. Also tried df.style.hide_index(), but no effect.
Want to hide that incrementing number first column when you do st.write(). How to do that?
Thanks!
Hi,
I tried to drop, but df.drop seems to work only on the “regular” columns. Also tried df.style.hide_index(), but no effect.
Want to hide that incrementing number first column when you do st.write(). How to do that?
Thanks!
Hi! I think this documentation covers your question: Hide row indices when displaying a dataframe - Streamlit Docs
Hope it helps!
Hello,
Oh I see. So it’s not as straight forward as I thought.
The example worked, it hid the values. But not the column itself. So there’s a blank column with no values, like this:
------------------------
| | col1 |col2 |
------------------------
| | aa |bb |
| | cc |dd |
Thanks!
That’s weird, for me it looks exactly as in the documentation.
Maybe update the streamlit version?
Can you share the dataframe (first 5 rows) and code you’re using?
here goes:
records = [{'tt': 'abc', 'xx': 'xyz'}, {'tt': '111', 'xx': '222'}]
df = pd.DataFrame(records)
# CSS to inject contained in a string
hide_dataframe_row_index = """
<style>
.row_heading.level0 {display:none}
.blank {display:none}
</style>
"""
st.markdown(hide_dataframe_row_index, unsafe_allow_html=True)
st.dataframe(df)
thx.

hello ,
i looked at the example again and so it seems, st.dataframe will show that blank column.
st.table will remove it.
it is what it is. 
thank you!
What if I want to use st.dataframe and not show the blank column? @sebastiandres @jeisma
+1. Traced exactly the steps above in the thread and wound up at the same (unsatisfactory) place.
df = pd.read_csv('notes_and_reports/31_Days/available_days.csv', header='infer', index_col=None)
# show df without index
df = df.fillna('')
# CSS to inject contained in a string
hide_dataframe_row_index = """
<style>
.row_heading.level0 {display:none}
.blank {display:none}
</style>
"""
# Inject CSS with Markdown
st.markdown(hide_dataframe_row_index, unsafe_allow_html=True)
st.dataframe(df)
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