app.py

# How can I add row to an iterable dataset
#🤗Datasets
#This is the first time xbilek25 has posted — let’s welcome them to our community!


#xbilek25

#2
#9h
#I need any working option to add row to a dataset, where streaming=True. While working with normal dataset I define new item and use code like this:
#tmp_dataset = tmp_dataset.add_item(new_item), but i can’t figure out how to do this while my dataset is streaming=True.
#Can anyone help me to find solution, please?

import streamlit as st

st.set_page_config(page_icon="📝", page_title="📝AI-EIO-Editor📊", layout="wide")

if st.checkbox('Show Anatomy Table'):
    st.markdown("""
    ## Anatomy Head to Toe Table with Body Organs Costly Conditions, Spending, CPT Codes and Frequency
    
    | Table Num | Body Part        | Organ/Part           | Description                   | 📈 Costly Condition          | 💰 Spending (billions) | CPT Range Start | CPT Range Finish | Frequency      |
    |-----------|------------------|----------------------|-------------------------------|------------------------------|------------------------|-----------------|------------------|----------------|
    | 1         | 🧠 Head          | 🧠 Brain             | Controls mental processes     | 😨 Anxiety & Depression      | 210                    | 90791           | 90899            | 1 in 5         |
    | 2         | 👀 Eyes          | 👁️ Optic Nerve      | Vision                        | 👓 Cataracts                 | 10.7                   | 92002           | 92499            | 1 in 6 (over 40 years) |
    | 3         | 👂 Ears          | 🐚 Cochlea           | Hearing                       | 📢 Hearing Loss              | 7.1                    | 92502           | 92700            | 1 in 8 (over 12 years) |
    | 4         | 👃 Nose          | 👃 Olfactory Bulb    | Smell                         | 🤧 Allergies                 | 25                     | 31231           | 31294            | 1 in 3         |
    | 5         | 👄 Mouth         | 👅 Tongue            | Taste                         | 🦷 Dental Issues             | 130                    | 00100           | 00192            | 1 in 2         |
    | 6         | 🫁 Neck          | 🦋 Thyroid           | Metabolism                    | 🦠 Hypothyroidism            | 3.1                    | 60210           | 60271            | 1 in 20        |
    | 7         | 💪 Upper Body    | ❤️ Heart             | Circulation                   | 💔 Heart Disease             | 230                    | 92920           | 93799            | 1 in 4 (over 65 years) |
    | 8         | 💪 Upper Body    | 🫁 Lungs             | Respiration                   | 😷 Chronic Obstructive Pulmonary Disease | 70   | 94002           | 94799            | 1 in 20 (over 45 years) |
    | 9         | 💪 Upper Body    | 🍷 Liver             | Detoxification                | 🍺 Liver Disease             | 40                     | 47000           | 47999            | 1 in 10        |
    | 10        | 💪 Upper Body    | 🍹 Kidneys           | Filtration                    | 🌊 Chronic Kidney Disease    | 110                    | 50010           | 50999            | 1 in 7         |
    | 11        | 💪 Upper Body    | 💉 Pancreas          | Insulin secretion             | 🍬 Diabetes                  | 327                    | 48100           | 48999            | 1 in 10        |
    | 12        | 💪 Upper Body    | 🍽️ Stomach          | Digestion                     | 🔥 Gastroesophageal Reflux Disease | 17          | 43200           | 43289            | 1 in 5         |
    | 13        | 💪 Upper Body    | 🛡️ Spleen            | Immune functions              | 🩸 Anemia                    | 5.6                    | 38100           | 38199            | 1 in 6         |
    | 14        | 💪 Upper Body    | 🫀 Blood Vessels     | Circulation of blood          | 🚑 Hypertension              | 55                     | 40110           | 40599            | 1 in 3         |
    | 15        | 🦵 Lower Body    | 🍝 Colon             | Absorption of water, minerals | 🌟 Colorectal Cancer         | 14                     | 45378           | 45378            | 1 in 23        |
    | 16        | 🦵 Lower Body    | 🚽 Bladder           | Urine excretion               | 💧 Urinary Incontinence      | 8                      | 51700           | 51798            | 1 in 4 (over 65 years) |
    | 17        | 🦵 Lower Body    | 💞 Reproductive Organs | Sex hormone secretion        | 🎗️ Endometriosis            | 22                     | 56405           | 58999            | 1 in 10 (women) |
    | 18        | 🦶 Feet          | 🎯 Nerve endings      | Balance and movement          | 🤕 Peripheral Neuropathy     | 19                     | 95900           | 96004            | 1 in 30        |
    | 19        | 🦶 Feet          | 🌡️ Skin              | Temperature regulation        | 🌞 Skin Cancer               | 8.1                    | 96910           | 96999            | 1 in 5         |
    | 20        | 🦶 Feet          | 💪 Muscles           | Movement and strength         | 🏋️‍♂️ Musculoskeletal Disorders | 176              | 97110           | 97799            | 1 in 2         |
    
    """)


import streamlit as st
import pandas as pd
import traceback
import sys

from st_aggrid import AgGrid
from st_aggrid.grid_options_builder import GridOptionsBuilder
from st_aggrid.shared import JsCode
from st_aggrid import GridUpdateMode, DataReturnMode

def parse(file, condition, data=[], ind_append=False):
    for line in file:
        st.write(line)
        data.append(line)
    return data

def read_csv_any_file(file):
    dropBlanks=True
    logResult=True
    logResultStartSymbol = "["
    
    
    if file is not None:
        data = []
        df = pd.DataFrame()
        for line in file:
            if line == b' \r\n':
                if dropBlanks == False:
                    st.write(line.decode('UTF-8'))
            else:   
                if logResult: 
                    st.write(line.decode('UTF-8'))
                    data.append(line.decode('UTF-8'))
        
        df = pd.DataFrame(data, columns=['InputLines'])
    return df

# Style
def _max_width_():
    max_width_str = f"max-width: 1800px;"
    st.markdown(
        f"""
    <style>
    .reportview-container .main .block-container{{
        {max_width_str}
    }}
    </style>    
    """,
        unsafe_allow_html=True,
    )
    
# Title Bar with Images and Icons
col1, col2, col3 = st.columns([1,6,1])
with col1:
    st.image("https://cdnb.artstation.com/p/assets/images/images/054/910/875/large/aaron-wacker-cyberpunk-computer-brain-design.jpg?1665656558",width=64,)
with col2:
    st.title("📝Double Line AI Editor📊")
with col3:
    st.image("https://cdna.artstation.com/p/assets/images/images/054/910/878/large/aaron-wacker-cyberpunk-computer-devices-iot.jpg?1665656564",width=64,)
    
# Upload
c29, c30, c31 = st.columns([1, 6, 1])
with c30:
    uploaded_file = st.file_uploader("", key="1", help="To activate 'wide mode', go to the menu > Settings > turn on 'wide mode'",)
    if uploaded_file is not None:
        file_container = st.expander("Check your uploaded .csv")
        #try:
        shows = read_csv_any_file(uploaded_file)
        #shows = pd.read_csv(uploaded_file)
        #except:
        #    print(sys.exc_info()[2])
            
        uploaded_file.seek(0)
        file_container.write(shows)
    else:
        st.info(f"""⬆️Upload a 📝.CSV file.  Examples: [Chatbot](https://huggingface.co/datasets/awacke1/Carddata.csv)  [Mindfulness](https://huggingface.co/datasets/awacke1/MindfulStory.csv)  [Wikipedia](https://huggingface.co/datasets/awacke1/WikipediaSearch)""")
        st.stop()

# DisplayGrid
#gb = GridOptionsBuilder.from_dataframe(shows)

#z = [[" ".join(i.split()[:2]),str(i.split()[2])] for i in shows]
#df = pd.DataFrame(z,columns=['Str','Str2'])

gb = GridOptionsBuilder.from_dataframe(shows)

gb.configure_default_column(enablePivot=True, enableValue=True, enableRowGroup=True)
gb.configure_selection(selection_mode="multiple", use_checkbox=True)
gb.configure_side_bar()
gridOptions = gb.build()
st.success(f"""💡 Tip! Hold shift key when selecting rows to select multiple rows at once.""")
response = AgGrid(
    shows,
    gridOptions=gridOptions,
    enable_enterprise_modules=True,
    update_mode=GridUpdateMode.MODEL_CHANGED,
    data_return_mode=DataReturnMode.FILTERED_AND_SORTED,
    fit_columns_on_grid_load=False,
)

# Filters
df = pd.DataFrame(response["selected_rows"])
st.subheader("Filtered data will appear below 📊 ")
st.text("")
st.table(df)
st.text("")

import base64
import pandas as pd

# Example DataFrame
data = {'Column1': [1, 2], 'Column2': [3, 4]}
df = pd.DataFrame(data)

# Function to convert DataFrame to CSV and then encode to base64
def to_base64_csv(df):
    csv = df.to_csv(index=False)
    b64 = base64.b64encode(csv.encode()).decode()
    return f"data:text/csv;base64,{b64}"

# Function to convert DataFrame to TXT and then encode to base64
def to_base64_txt(df):
    txt = df.to_csv(index=False, sep='\t')
    b64 = base64.b64encode(txt.encode()).decode()
    return f"data:text/plain;base64,{b64}"

# Generate base64 encoded links
csv_link = to_base64_csv(df)
txt_link = to_base64_txt(df)

# Markdown format for hyperlinks in bold font with emojis
markdown_csv_link = f"**[📥 Download Dataset as CSV]({csv_link})**"
markdown_txt_link = f"**[📥 Download Dataset as TXT]({txt_link})**"

# Display as markdown (hypothetical, depends on how you render markdown in your application)
print(markdown_csv_link)
print(markdown_txt_link)

st.markdown(markdown_csv_link, unsafe_allow_html=True)
st.markdown(markdown_txt_link, unsafe_allow_html=True)
#-----------------------------------------------------------------------
    
import streamlit as st
import pandas as pd

# Load dataset
def load_data():
    return pd.read_csv('anatomy_dataset.csv')

# Save dataset
def save_data(df):
    df.to_csv('anatomy_dataset.csv', index=False)

# CRUD Operations
def add_data(df):
    # Add a row to the dataframe (Example)
    # You can modify this function to take input from the user
    new_row = {'Table Num': 21, 'Body Part': 'New Part', 'Organ/Part': 'New Organ', 'Description': 'New Description',
               'Costly Condition': 'New Condition', 'Spending (billions)': 0, 'CPT Range Start': 0, 'CPT Range Finish': 0,
               'Frequency': 'New Frequency'}
    df = df.append(new_row, ignore_index=True)
    return df

def update_data(df):
    # Update a row in the dataframe (Example)
    # Implement the update logic based on your requirements
    if not df.empty:
        df.at[0, 'Description'] = 'Updated Description'
    return df

def delete_data(df):
    # Delete a row from the dataframe (Example)
    # Implement the delete logic based on your requirements
    if not df.empty:
        df = df.drop(df.index[0])
    return df

# Streamlit UI
st.title("Anatomy Head to Toe CRUD Operations")

# Display the table if checkbox is checked
if st.checkbox('Show Anatomy Table as Dataframe'):
    df = load_data()
    st.markdown("## Anatomy Head to Toe Table with Body Organs Costly Conditions, Spending, CPT Codes and Frequency")
    st.dataframe(df)

# CRUD operation buttons
col1, col2, col3, col4 = st.columns(4)
if col1.button('➕ Add'):
    df = load_data()
    df = add_data(df)
    save_data(df)

if col2.button('🔄 Update'):
    df = load_data()
    df = update_data(df)
    save_data(df)

if col3.button('❌ Delete'):
    df = load_data()
    df = delete_data(df)
    save_data(df)

if col4.button('💾 Save'):
    df = load_data()
    save_data(df)
    st.success("Data saved to CSV!")