Configure a selectbox column in st.dataframe or st.data_editor.
This is the default column type for Pandas categorical values. This command needs to be used in the column_config parameter of st.dataframe or st.data_editor. When used with st.data_editor, editing will be enabled with a selectbox widget.
| Function signature[source] | |
|---|---|
st.column_config.SelectboxColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, options=None) | |
| Parameters | |
label (str or None) | The label shown at the top of the column. If None (default), the column name is used. |
width ("small", "medium", "large", or None) | The display width of the column. Can be one of "small", "medium", or "large". If None (default), the column will be sized to fit the cell contents. |
help (str or None) | An optional tooltip that gets displayed when hovering over the column label. |
disabled (bool or None) | Whether editing should be disabled for this column. Defaults to False. |
required (bool or None) | Whether edited cells in the column need to have a value. If True, an edited cell can only be submitted if it has a value other than None. Defaults to False. |
default (str, int, float, bool, or None) | Specifies the default value in this column when a new row is added by the user. |
options (Iterable of str or None) | The options that can be selected during editing. If None (default), this will be inferred from the underlying dataframe column if its dtype is "category" (see Pandas docs on categorical data). |
Examples
import pandas as pd
import streamlit as st
data_df = pd.DataFrame(
{
"category": [
"📊 Data Exploration",
"📈 Data Visualization",
"🤖 LLM",
"📊 Data Exploration",
],
}
)
st.data_editor(
data_df,
column_config={
"category": st.column_config.SelectboxColumn(
"App Category",
help="The category of the app",
width="medium",
options=[
"📊 Data Exploration",
"📈 Data Visualization",
"🤖 LLM",
],
required=True,
)
},
hide_index=True,
)
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