Session state logic

Using Streamlit
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1

Idea:
Say I have 4 checkboxes with keys A, B, C, D and I also have a dataframe with A, B, C, D as indexes and all of them having some default value, like this:

import pandas as pd
import streamlit as st

df = pd.DataFrame(index = [‘A’, ‘B’, ‘C’, ‘D’], columns = [‘Value’, ‘Active’], data = [[1, False], [2, False], [3, False], [4, False]])

df[‘Active’].loc[‘A’] = st.checkbox(‘A’)
df[‘Active’].loc[‘B’] = st.checkbox(‘B’)
df[‘Active’].loc[‘C’] = st.checkbox(‘C’)
df[‘Active’].loc[‘D’] = st.checkbox(‘D’)

My goal is to create a data editor filtering only the “active keys” (determined by the checkboxes), this is my previous attempt:

st.data_editor(df[df[‘Active’] == True][‘Value’])

So let’s say we click on the checkbox “C”, it should create a new row with in the data editor.

Problem:
The problem is that everytime we click on the checkbox the code gets run again so it resets all values that may have been changed to the default. Example: we activate “A” and change the value to 37, but then activate “B”, when “B” is activated the row “A” returns to the default value of 1, but I want it to keep 37.

I guess the solution may have something with session states but I just can’t figure it out! Thanks for the attention

2

Yes, you would need to implement session state as in code below.

import pandas as pd
import streamlit as st

# Step 1: Initialize the DataFrame in the session state
if 'df' not in st.session_state:
    st.session_state['df'] = pd.DataFrame(index=['A', 'B', 'C', 'D'], columns=['Value', 'Active'], data=[[1, False], [2, False], [3, False], [4, False]])

# Step 2: Activate rows based on checkbox selections
st.session_state['df']['Active'].loc['A'] = st.checkbox('A')
st.session_state['df']['Active'].loc['B'] = st.checkbox('B')
st.session_state['df']['Active'].loc['C'] = st.checkbox('C')
st.session_state['df']['Active'].loc['D'] = st.checkbox('D')

# Step 3 & 4: Edit values and reflect changes back in the session state
active_df = st.session_state['df'][st.session_state['df']['Active'] == True].copy()
edited_df = st.data_editor(active_df['Value'])

if edited_df is not None:
    st.session_state['df']['Value'].update(edited_df)

Screen Recording 2023-09-15 at 3_scaling-0.5_fps-20_speed-5.0_duration-0-11

1 Like
3

Thank you very very very very much! It worked :slight_smile:

1 Like
4

Great! Glad it worked. Happy Streamlit-ing!:balloon:

5

Tony, I don’t know why, I just changed a little bit of your code to be like this:

import pandas as pd
import streamlit as st

if 'df' not in st.session_state:
    st.session_state['df'] = pd.DataFrame(
      index=['A', 'B', 'C', 'D'], 
      columns=['Low', 'High', 'Active'], 
      data=[[.0, 50., False], [.0, 500., False], [.1, 1.5, False], [.0, 50., False]])

st.session_state['df']['Active'].loc['A'] = st.checkbox('A')
st.session_state['df']['Active'].loc['B'] = st.checkbox('B')
st.session_state['df']['Active'].loc['C'] = st.checkbox('C')
st.session_state['df']['Active'].loc['D'] = st.checkbox('D')

active_df = st.session_state['df'][st.session_state['df']['Active'] == True].copy()
edited_df = st.data_editor(active_df[['Low', 'High']])
 
if edited_df is not None:
st.session_state['df'][['Low', 'High']].update(edited_df)

I changed the column “Value” to be 2 columns “Low” & “High” and now is not working anymore

6

You can try updating each column separately as the original update code is trying to update multiple columns all at once causing an error. See the updated code below:

import pandas as pd
import streamlit as st

if 'df' not in st.session_state:
    st.session_state['df'] = pd.DataFrame(
      index=['A', 'B', 'C', 'D'], 
      columns=['Low', 'High', 'Active'], 
      data=[[.0, 50., False], [.0, 500., False], [.1, 1.5, False], [.0, 50., False]])

st.session_state['df']['Active'].loc['A'] = st.checkbox('A')
st.session_state['df']['Active'].loc['B'] = st.checkbox('B')
st.session_state['df']['Active'].loc['C'] = st.checkbox('C')
st.session_state['df']['Active'].loc['D'] = st.checkbox('D')

active_df = st.session_state['df'][st.session_state['df']['Active'] == True].copy()
edited_df = st.data_editor(active_df[['Low', 'High']])
 
if edited_df is not None:
    for idx, row in edited_df.iterrows():
        st.session_state['df'].loc[idx, ['Low', 'High']] = row['Low'], row['High']
7

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