Sorting in st.dataframe

Using Streamlit
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So, I have a dataframe similar to the image attached. Is it possible to exclude the ‘Total’ row from sorting, I have look at the documentation of st.dataframe but there it is not specified how to exclude certain row while sorting

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Hi @Ameen

This can be done by using data slicing.

To exclude the last row of your DataFrame df, you can use:

df[:-1]

Hope this helps!

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Hi @dataprofessor, thank you for your response. However, my intention isn’t to remove the row from being displayed rather, I’m looking to exclude it from the sorting process… while using st.dataframe , it offers built-in sorting for each column, but I want to prevent the row labeled ‘Total’ from being affected by this sorting. Is there a way to achieve that?

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image

When I use the built-in sorting feature of st.dataframe , it correctly sorts the values. However, I would like to exclude the ‘Total’ row from sorting; I need it to stay at the bottom when sorting is applied. Is there a way to achieve this?

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Hey @Ameen . Then first subset the data except the last row and sort the remaining dataframe at last add the last two the sorted dataframe.

Hope it works well !!!

Happy Streamlit-ing :balloon:

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Thanks for the reply, could you please provide a code example? I didn’t fully understand your explanation.

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Hey @Ameen . Here is an demo:-

import pandas as pd
data = {
    'a': [54, 24, 78],
    'b': [104, 78, 182],
    'c': [324, 56, 380]
}
df = pd.DataFrame(data,index=['q1','q2','total'])
print('Before:\n',df)
df1=df.copy()
df=df1.iloc[:-1,:].sort_values(by=['a','b','c'],ignore_index=True)
df.loc[len(df.index)]=df1.loc['total']
df.rename(index={0:'q1',1:'q2',2:'total'},inplace=True)
print('-'*10)
print('After:\n',df)


Output:-
Before:
         a    b    c
q1     54  104  324
q2     24   78   56
total  78  182  380
----------
After:
         a    b    c
q1     24   78   56
q2     54  104  324
total  78  182  380

Hope you understood now !

Happy Streamlit-ing :balloon:

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Hi @Guna_Sekhar_Venkata, thank you for your reply. I was hoping to find a solution using st.dataframe, but it seems that’s not possible. I will have to use the workaround you shared. Thanks again…

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if anyone is struggling with similar issue use streamlit-aggrid, it provide way more table configuration that st.dataframe

from st_aggrid import AgGrid, ColumnsAutoSizeMode, GridUpdateMode, JsCode
from st_aggrid.grid_options_builder import GridOptionsBuilder

# pass your dataframe inside gridoptionbuilder
gob = GridOptionsBuilder.from_dataframe(df)

pinned_row_data = [df[df["Quarter"] == "Total"].to_dict(orient="records")[0]]
df = df.drop(df[df["Quarter"] == "Total"].index)
height = 180
gob.configure_grid_options(pinnedBottomRowData=pinned_row_data)
gridOptions = gob.build()

AgGrid(df, height=height, gridOptions=gridOptions, fit_columns_on_grid_load=True,update_mode=GridUpdateMode.VALUE_CHANGED)

Using this sample code, you can pin a row to ensure it remains excluded during sorting and filtering operations.

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