Ag-Grid component with input support

Custom Components streamlit-aggrid
167

@rchamila a possible solution to your case is given by the below snippet (consider that I am no expert in neither AG Grid nor streamlit-aggrid components, so maybe some implementations can be improved)

It works for both single and multiple rows selection.

Snippet 
import string

import numpy as np
import pandas as pd
import streamlit as st
from st_aggrid import AgGrid, GridOptionsBuilder, GridUpdateMode

st.set_page_config(layout='wide')


def display_table(df: pd.DataFrame, selection: str) -> AgGrid:
    # Configure AgGrid options
    gb = GridOptionsBuilder.from_dataframe(df)
    gb.configure_selection(selection)
    st.write(f"Dataframe shape: {df.shape}")
    return AgGrid(
        df,
        gridOptions=gb.build(),
        # this override the default VALUE_CHANGED
        update_mode=GridUpdateMode.MODEL_CHANGED
    )


# Define dummy data
rng = np.random.default_rng(2021)
N_SAMPLES = 100
N_FEATURES = 10
df = pd.DataFrame(rng.integers(0, N_SAMPLES, size=(
    N_SAMPLES, N_FEATURES)), columns=list(string.ascii_uppercase[:N_FEATURES]))

cols = st.beta_columns(2)

with cols[0]:

    st.markdown('# 🠔 Before')

    # Display AgGrid from data and write response
    st.markdown("### 1️⃣ Let's display dummy data through AgGrid")
    selection = st.radio('Selection mode', ['single', 'multiple'])
    response = display_table(df, selection=selection)

    st.markdown(
        "### 2️⃣ AgGrid response contains `data` (original df) and `selected_rows`")
    for k, v in response.items():
        st.write(k, v)

with cols[1]:

    st.markdown('# 🠖 After')

    # Retrieve selected rows indices
    st.markdown(
        "### 3️⃣ From selected rows we can obtain dataframe indices to drop")
    data = response['data'].to_dict(orient='records')
    indices = [data.index(row) for row in response['selected_rows']]
    st.write(f"Selected rows are located at indices: {indices}")

    # Use retrieved indices to remove corresponding rows from dataframe
    st.markdown(
        "### 4️⃣ Display the updated dataframe where rows have been removed")
    _df = df.drop(indices, axis=0)
    st.write(f"Dataframe shape: {_df.shape}")
    AgGrid(_df)
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