Hey there! Adding filter checkboxes to your Streamlit sales report is totally doable—let me walk you through how to integrate them with your existing code. I'll cover two common scenarios: multi-option category filters (using a checkbox-style selector) and single yes/no filters.

Multi-Option Filter (Checkbox Selector) #

This is perfect if you want users to filter your data by categories like product type, region, or sales quarter. Here's how to modify your code:

import pandas as pd
import streamlit as st
import plotly.express as px
from PIL import Image

st.set_page_config(page_title='Sales Report')
st.header('Sales Report')
st.subheader('Results')

# Read your data (note: make sure your file path includes the .csv suffix if it's a CSV file)
df = pd.read_csv('data.csv')

# 1. Define which column you want to filter by (replace with your actual column name)
filter_column = "Product Category"
# 2. Get all unique values from that column to use as filter options
filter_options = df[filter_column].unique()

# 3. Create a multi-select checkbox widget (users can pick multiple options)
selected_filters = st.multiselect(
    f"Filter by {filter_column}",
    filter_options,
    default=filter_options  # Default to showing all options initially
)

# 4. Filter the dataframe to only include rows matching selected options
filtered_df = df[df[filter_column].isin(selected_filters)]

# 5. Display the filtered table
st.dataframe(filtered_df)

Key Notes: #

• Replace Product Category with the actual column name from your dataset (e.g., Region, Sales Year, Product Line).
• The st.multiselect widget acts like a group of checkboxes—users can select multiple values at once.
• Setting default=filter_options ensures all data is shown when the app first loads, matching your current behavior.

Single Checkbox Filter (Yes/No Condition) #

If you have a binary condition (like "show only high-value sales" or "display in-stock items"), use a single checkbox:

import pandas as pd
import streamlit as st
import plotly.express as px
from PIL import Image

st.set_page_config(page_title='Sales Report')
st.header('Sales Report')
st.subheader('Results')

df = pd.read_csv('data.csv')

# Create a single checkbox for a binary filter
show_high_value_only = st.checkbox("Show only sales over $1000")

# Filter based on the checkbox state
if show_high_value_only:
    filtered_df = df[df["Sales Amount"] > 1000]
else:
    filtered_df = df

st.dataframe(filtered_df)

Just replace Sales Amount and the condition (> 1000) with your actual column and filter logic.

内容的提问来源于stack exchange，提问作者Manas Jadhav