min_indi.py

#!/usr/bin/env python
# coding: utf-8

import os
import json
import urllib.parse
from datetime import datetime
from io import BytesIO
import threading

import pandas as pd
import httpx
import requests
import panel as pn
import hvplot.pandas
import holoviews as hv

pn.extension('tabulator', inline=True, sizing_mode="stretch_both")

# -------------------------------
# SETTINGS
# -------------------------------
n_start = "2024-01-01"
n_end = "2025-11-13"
n_start_datetime = datetime.strptime(n_start, "%Y-%m-%d")
n_end_datetime = datetime.strptime(n_end, "%Y-%m-%d")

parquet_path = f"{n_start}_{n_end}.parquet"

# -------------------------------
# PANEL FUNCTIONS
# -------------------------------
def tablazat(text_input, multi_select, select, table_size, orvos_input):
    
    filtered = min_indi.groupby(multi_select).agg({
        f'Esetszam {n_start[:4]}': 'sum',
        f'Esetszam {n_end[:4]}': 'sum',
        f'Minoseg indikator arany {n_start[:4]}(%)': 'mean',
        f'Minoseg indikator arany {n_end[:4]}(%)': 'mean',
        'Minoseg indikator arany kulonbseg(%)': 'mean',
        'Minoseg indikator egyeb arany kulonbseg(%)': 'mean',
    }).reset_index()

    
    # Sort entire table first by selected column (descending)
    sorted_df = filtered.sort_values(by=select, ascending=False).reset_index(drop=True)

    # Step 3 — Determine mask based on input
    if text_input:
        mask = sorted_df['Bekuldo Intezet'].str.contains(text_input, case=False, na=False)
    elif orvos_input:
        mask = sorted_df['Bekuldo Orvos'].str.contains(orvos_input, case=False, na=False)
    else:
        mask = pd.Series(False, index=sorted_df.index)
    
    # Step 4 — Get integer index positions (→ now mask becomes index list)
    match_indices = sorted_df.index[mask].to_list()[:2]
    
    # Step 5 — Collect ±3 neighbors around each match
    neighbor_indices = set()
    for idx in match_indices:
        start = max(idx - 3, 0)
        end = min(idx + 3, len(sorted_df) - 1)
        neighbor_indices.update(range(start, end + 1))
    
    # Step 6 — Build neighbor-filtered dataframe
    if not neighbor_indices:
        neighbor_filtered = sorted_df.head(table_size)
    else:
        neighbor_filtered = sorted_df.loc[sorted(neighbor_indices)]

    return neighbor_filtered



# Plot
accept_color = '#5B91D1'
non_accept_color = '#CF6044'

def plot(text_input,multi_select,select,table_size,orvos_input):
    filtered_min_indi= tablazat(text_input,multi_select,select,table_size,orvos_input)
    # Define a function to determine the color based on the value
    
    def get_color(value):
        if value > 10:
            return non_accept_color
        else:
            return accept_color

    # Add a new column for color based on the values in column_1
    filtered_min_indi['color'] = filtered_min_indi[select].apply(get_color)
    bar = filtered_min_indi.hvplot.bar(
        x=multi_select[0],
        y=select,
        color ='color', 
        responsive=True,
        rot = 45,
        ylim= [(filtered_min_indi[select].min()-1),(filtered_min_indi[select].max()+1)]
    )
    if filtered_min_indi[select].min() < 0:
        acceptrange= hv.HSpan((filtered_min_indi[select].min()-1),10).opts(color= accept_color,alpha=0.1)
    else:
        acceptrange= hv.HSpan(0,10).opts(color='blue',alpha=0.2)
    non_acceptrange = hv.HSpan(10,(filtered_min_indi[select].max()+1)).opts(color= non_accept_color,alpha=0.1)
    return bar * acceptrange * non_acceptrange


min_indi = pd.read_parquet(parquet_path)
# -------------------------------
# WIDGETS
# -------------------------------
#esetszam_input = pn.widgets.IntInput(name='Minimum esetszám', value=5, step=1, start=0, end=500)
table_size = pn.widgets.IntSlider(name='Tábla méret', start=5, end=50, step=1, value=10)
index_options = ['Bekuldo Intezet','Bekuldo Orvos','Eloszuro','Orvos']

select = pn.widgets.Select(name='Sort by:', value = 'Minoseg indikator arany kulonbseg(%)',
                           options=list(min_indi.columns[4:]))
multi_select = pn.widgets.MultiSelect(name='Select Indexes', value=[index_options[2]], options=index_options, size=8)
text_input = pn.widgets.TextInput(name='Beküldő Intézet kereső', placeholder='Tartalmazza ezt...', visible=False)
orvos_input = pn.widgets.TextInput(name='Beküldő Orvos kereső', placeholder='Tartalmazza ezt...',visible=False)

def update_search_visibility(multi_select_value):
    text_input.visible = index_options[0] in multi_select_value
    orvos_input.visible = index_options[1] in multi_select_value

multi_select.param.watch(lambda event: update_search_visibility(event.new), 'value')



inter_ind = pn.bind(tablazat,text_input,multi_select,select,table_size,orvos_input)
inter_plot = pn.bind(plot,text_input,multi_select,select,table_size,orvos_input)

# -------------------------------
# PANEL TEMPLATE
# -------------------------------
template = pn.template.FastListTemplate(
    title='Minőség Indikátorok',
    sidebar=pn.Column(
        text_input,
        orvos_input,
        multi_select,
        select,
        table_size,
    ),
    main=[pn.Tabs(('DF',pn.widgets.DataFrame(inter_ind, disabled=False)),('Plot',inter_plot))],
    header_background=accept_color
)

template.servable()