Merge remote-tracking branch 'origin/main'

40 Fio 02 diagnostika 2.py

@@ -0,0 +1,24 @@
+import pymysql
+from pymysql.cursors import DictCursor
+
+conn = pymysql.connect(
+    host="192.168.1.76",
+    port=3307,
+    user="root",
+    password="Vlado9674+",
+    database="fio",
+    charset="utf8mb4",
+    cursorclass=DictCursor
+)
+
+with conn.cursor() as cur:
+    cur.execute("SHOW TABLES;")
+    print("📋 Tables:", [r[f"Tables_in_fio"] for r in cur.fetchall()])
+
+    cur.execute("SELECT COUNT(*) AS cnt FROM transactions;")
+    print("🧾 Rows in `transactions`:", cur.fetchone()["cnt"])
+
+    cur.execute("SHOW COLUMNS FROM transactions;")
+    print("\n📊 Columns:")
+    for r in cur.fetchall():
+        print(" -", r["Field"])

40 Fio 03 excel.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+"""
+Export Fio transactions (from MySQL → Excel)
+--------------------------------------------
+- Reads only cislo_uctu = '2800046620'
+- For OZP (protiucet=2070101041) includes only positive objem
+- Each sheet = insurance company (filtered by protiucet)
+- First sheet = summary with total amounts and transaction counts
+"""
+
+import pandas as pd
+import pymysql
+from pathlib import Path
+from datetime import datetime
+
+# ======== CONFIG ========
+MYSQL_CONFIG = {
+    "host": "192.168.1.76",
+    "port": 3307,
+    "user": "root",
+    "password": "Vlado9674+",
+    "database": "fio",
+    "charset": "utf8mb4",
+}
+
+REPORTOVAT = {
+    "VZP": "1114007221",
+    "VOZP": "2010009091",
+    "ČPZP": "2054108761",
+    "OZP": "2070101041",
+    "ZPŠ": "2090309181",
+    "ZPMV": "2112108031",
+}
+
+EXPORT_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230") / f"Fio_report_{datetime.now():%Y-%m-%d_%H-%M-%S}.xlsx"
+
+
+# ======== LOAD DATA ========
+def load_data():
+    print("🔄 Načítám data z MySQL (účet 2800046620, pro OZP jen kladné objemy)...")
+    conn = pymysql.connect(**MYSQL_CONFIG)
+
+    sql = """
+        SELECT *
+        FROM transactions
+        WHERE cislo_uctu = '2800046620'
+          AND (
+              protiucet <> '2070101041'
+              OR (protiucet = '2070101041' AND objem > 0)
+          );
+    """
+    df = pd.read_sql(sql, conn)
+    conn.close()
+
+    df.columns = df.columns.str.strip()
+    print(f"✅ Načteno {len(df)} řádků, {len(df.columns)} sloupců.")
+    return df
+
+
+# ======== EXPORT TO EXCEL ========
+def export_to_excel(df):
+    summary_rows = []  # to collect summary per insurer
+
+    with pd.ExcelWriter(EXPORT_PATH, engine="openpyxl") as writer:
+        # --- INDIVIDUAL SHEETS ---
+        for name, acc in REPORTOVAT.items():
+            filtered = df[df["protiucet"].astype(str) == acc]
+            if filtered.empty:
+                print(f"⚠️ {name}: žádné transakce (účet {acc})")
+                summary_rows.append({
+                    "Pojišťovna": name,
+                    "Číslo účtu": acc,
+                    "Počet transakcí": 0,
+                    "Součet objemu": 0.0
+                })
+                continue
+
+            # safe numeric conversion
+            filtered = filtered.copy()
+            filtered["objem_num"] = (
+                filtered["objem"]
+                .astype(str)
+                .str.replace("\u00A0", "", regex=False)
+                .str.replace(",", ".", regex=False)
+                .astype(float)
+            )
+
+            # --- summary data ---
+            total_sum = filtered["objem_num"].sum()
+            total_count = len(filtered)
+
+            summary_rows.append({
+                "Pojišťovna": name,
+                "Číslo účtu": acc,
+                "Počet transakcí": total_count,
+                "Součet objemu": round(total_sum, 2)
+            })
+
+            # --- write detailed sheet ---
+            filtered.to_excel(writer, index=False, sheet_name=name)
+            print(f"✅ {name}: {len(filtered)} řádků exportováno, součet {total_sum:,.2f} Kč")
+
+        # --- SUMMARY SHEET ---
+        summary_df = pd.DataFrame(summary_rows)
+        summary_df["Součet objemu"] = summary_df["Součet objemu"].map("{:,.2f} Kč".format)
+        summary_df.to_excel(writer, index=False, sheet_name="Přehled")
+        print("🧾 Přidán přehledový list s celkovými součty.")
+
+    print(f"\n📊 Hotovo! Soubor uložen jako:\n{EXPORT_PATH}")
+
+
+# ======== MAIN ========
+if __name__ == "__main__":
+    df = load_data()
+    export_to_excel(df)

40 fio 01.py

@@ -2,11 +2,11 @@
 # -*- coding: utf-8 -*-
 
 """
-Import Fio banka CSV export (UTF-8, ; separated, quoted)
+Fio CSV import → MySQL (dev version)
-into MySQL database `fio.transactions`.
+------------------------------------
-
+- Always drops & recreates `transactions` table
-Unique key = (Číslo účtu, ID operace, ID pokynu)
+- Uses real CSV headers as seen in "Vyhledane pohyby (3).csv"
-Duplicates are skipped silently.
+- Unique key = (Číslo účtu, ID operace, ID pokynu)
 """
 
 import csv
@@ -14,6 +14,7 @@ from pathlib import Path
 from datetime import datetime
 import pymysql
 from pymysql.cursors import DictCursor
+import re
 
 # ======== CONFIG ========
 CSV_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230\Vyhledane pohyby (3).csv")
@@ -33,14 +34,12 @@ MYSQL_CONFIG = {
 
 # ======== HELPERS ========
 def clean(s: str):
-    """Trim and normalize text values."""
     if not s:
         return None
     return s.strip() or None
 
 
 def parse_date(raw: str):
-    """Convert dd.mm.yyyy → date"""
     raw = (raw or "").strip()
     if not raw:
         return None
@@ -51,10 +50,15 @@ def parse_date(raw: str):
 
 
 def parse_float(raw: str):
-    """Convert comma/space separated numbers to float"""
+    if raw is None:
-    raw = (raw or "").replace(" ", "").replace(",", ".")
+        return None
+    s = str(raw).strip()
+    for ch in (" ", "\u00A0", "\u202F", "\u2007"):
+        s = s.replace(ch, "")
+    s = s.replace(",", ".")
+    s = re.sub(r"[^0-9.+-]", "", s)
     try:
-        return float(raw)
+        return float(s)
     except ValueError:
         return None
 
@@ -64,38 +68,43 @@ def get_mysql_connection():
     return pymysql.connect(**MYSQL_CONFIG)
 
 
-def ensure_table_exists(conn):
+def recreate_table(conn):
-    """Create table if it doesn’t exist, with unique key on (cislo_uctu, id_operace, id_pokynu)."""
+    """Drop and recreate table with schema matching CSV structure."""
     sql = f"""
-    CREATE TABLE IF NOT EXISTS `{TABLE_NAME}` (
+    DROP TABLE IF EXISTS `{TABLE_NAME}`;
+    CREATE TABLE `{TABLE_NAME}` (
         id INT AUTO_INCREMENT PRIMARY KEY,
         datum DATE,
-        castka DECIMAL(14,2),
+        objem DECIMAL(14,2),
-        akce VARCHAR(100),
+        mena CHAR(3),
         cislo_uctu VARCHAR(40),
-        id_operace VARCHAR(50),
-        id_pokynu VARCHAR(50),
         protiucet VARCHAR(40),
-        nazev_protiuctu VARCHAR(200),
         kod_banky VARCHAR(20),
         ks VARCHAR(20),
         vs VARCHAR(20),
         ss VARCHAR(20),
         zprava_pro_prijemce VARCHAR(500),
         poznamka VARCHAR(500),
-        reference_platce VARCHAR(200),
+        id_operace VARCHAR(50),
-        typ VARCHAR(100),
+        id_pokynu VARCHAR(50),
-        upresneni VARCHAR(500),
+        ks_1 VARCHAR(20),
-        zadal VARCHAR(200),
-        zdrojovy_ucet VARCHAR(50),
         nazev_banky VARCHAR(100),
+        nazev_protiuctu VARCHAR(200),
+        ss_1 VARCHAR(20),
+        typ VARCHAR(100),
+        upresneni_objem VARCHAR(100),
+        upresneni_mena VARCHAR(20),
+        vs_1 VARCHAR(20),
+        zadal VARCHAR(200),
         imported_at DATETIME DEFAULT CURRENT_TIMESTAMP,
         UNIQUE KEY uniq_tx (cislo_uctu, id_operace, id_pokynu)
     ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
     """
     with conn.cursor() as cur:
-        cur.execute(sql)
+        for stmt in sql.strip().split(";"):
-    print(f"✅ Tabulka `{TABLE_NAME}` zkontrolována nebo vytvořena.")
+            if stmt.strip():
+                cur.execute(stmt)
+    print(f"✅ Tabulka `{TABLE_NAME}` znovu vytvořena podle CSV struktury.")
 
 
 # ======== IMPORT ========
@@ -104,35 +113,37 @@ def import_fio_csv():
         reader = csv.DictReader(f, delimiter=";", quotechar='"')
         rows = list(reader)
 
-    total_rows = len(rows)
+    total = len(rows)
-    print(f"📄 Načteno {total_rows} řádků ze souboru {CSV_PATH.name}")
+    print(f"📄 Načteno {total} řádků ze souboru {CSV_PATH.name}")
 
     with get_mysql_connection() as conn:
-        ensure_table_exists(conn)
+        recreate_table(conn)
         inserted, skipped = 0, 0
 
         for i, row in enumerate(rows, start=1):
             data = {
                 "datum": parse_date(row.get("Datum")),
-                "castka": parse_float(row.get("Částka")),
+                "objem": parse_float(row.get("Objem")),
-                "akce": clean(row.get("Akce")),
+                "mena": clean(row.get("Měna")),
                 "cislo_uctu": clean(row.get("Číslo účtu")),
-                "id_operace": clean(row.get("ID operace")),
-                "id_pokynu": clean(row.get("ID pokynu")),
                 "protiucet": clean(row.get("Protiúčet")),
-                "nazev_protiuctu": clean(row.get("Název protiúčtu")),
                 "kod_banky": clean(row.get("Kód banky")),
                 "ks": clean(row.get("KS")),
                 "vs": clean(row.get("VS")),
                 "ss": clean(row.get("SS")),
                 "zprava_pro_prijemce": clean(row.get("Zpráva pro příjemce")),
                 "poznamka": clean(row.get("Poznámka")),
-                "reference_platce": clean(row.get("Reference plátce")),
+                "id_operace": clean(row.get("ID operace")),
-                "typ": clean(row.get("Typ")),
+                "id_pokynu": clean(row.get("ID pokynu")),
-                "upresneni": clean(row.get("Upřesnění")),
+                "ks_1": clean(row.get("KS.1")),
-                "zadal": clean(row.get("Zadal")),
-                "zdrojovy_ucet": clean(row.get("Zdrojový účet")),
                 "nazev_banky": clean(row.get("Název banky")),
+                "nazev_protiuctu": clean(row.get("Název protiúčtu")),
+                "ss_1": clean(row.get("SS.1")),
+                "typ": clean(row.get("Typ")),
+                "upresneni_objem": clean(row.get("Upřesnění - objem")),
+                "upresneni_mena": clean(row.get("Upřesnění - měna")),
+                "vs_1": clean(row.get("VS.1")),
+                "zadal": clean(row.get("Zadal")),
             }
 
             cols = ", ".join(data.keys())
@@ -146,21 +157,12 @@ def import_fio_csv():
                 else:
                     skipped += 1
 
-            # --- progress output ---
+            if i % 500 == 0 or i == total:
-            if i % 500 == 0 or i == total_rows:
+                print(f"  {i}/{total} zpracováno... ({inserted} vloženo, {skipped} duplicit)")
-                print(f"  {i}/{total_rows} zpracováno... ({inserted} vloženo, {skipped} duplicit)")
-
-        # summary
-        with conn.cursor() as cur:
-            cur.execute(f"SELECT COUNT(*) AS cnt FROM `{TABLE_NAME}`")
-            total_db = cur.fetchone()["cnt"]
 
         print(f"\n✅ Import dokončen: {inserted} nových, {skipped} duplicit přeskočeno.")
-        print(f"📊 Celkem v databázi: {total_db} záznamů.")
 
 
 # ======== MAIN ========
 if __name__ == "__main__":
-    if not CSV_PATH.exists():
-        raise SystemExit(f"❌ Soubor {CSV_PATH} nenalezen.")
     import_fio_csv()

40 fio 02 diagnostika.py

@@ -2,46 +2,46 @@
 # -*- coding: utf-8 -*-
 
 """
-Diagnostický test: načti Fio CSV a ověř parsování datumu.
+Quick, verified dump of all Fio transactions from MySQL → Excel.
-Nenačítá se do MySQL – pouze vypíše výsledek.
+Column names are exactly as in DB.
 """
 
-import csv
+import pandas as pd
-from datetime import datetime
+import pymysql
+from pymysql.cursors import DictCursor
 from pathlib import Path
+from datetime import datetime
 
-# ✅ Tvoje cesta k souboru
+# ======== CONFIG ========
-CSV_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230\Vyhledane pohyby (1).csv")
+MYSQL_CONFIG = {
+    "host": "192.168.1.76",
+    "port": 3307,
+    "user": "root",
+    "password": "Vlado9674+",
+    "database": "fio",
+    "charset": "utf8mb4",
 
+}
 
-def parse_czech_date(s: str):
+EXPORT_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230") / f"Fio_ALL_{datetime.now():%Y-%m-%d_%H-%M-%S}.xlsx"
-    """Očistí řetězec a zkusí dd.mm.yyyy."""
-    if not s:
-        return None
-    s = s.strip().replace("\u00A0", "").replace("\ufeff", "")
-    try:
-        return datetime.strptime(s, "%d.%m.%Y").date()
-    except Exception:
-        return None
 
+# ======== MAIN ========
+def dump_all_transactions():
+    with pymysql.connect(**MYSQL_CONFIG) as conn:
+        sql = """
+            SELECT
+                *
+            FROM transactions
+            ORDER BY datum DESC;
+        """
+        df = pd.read_sql(sql, conn)
 
-def main():
+    print(f"✅ Načteno {len(df)} transakcí z MySQL.")
-    with open(CSV_PATH, "r", encoding="utf-8-sig", newline="") as f:
-        reader = csv.DictReader(f, delimiter=";", quotechar='"')
-        rows = list(reader)
 
-    print(f"Načteno {len(rows)} řádků.\n")
+    # Save to Excel
-    print("Ukázka prvních 10 řádků s hodnotou Datum:\n")
+    df.to_excel(EXPORT_PATH, index=False)
-
+    print(f"📊 Excel export hotov:\n{EXPORT_PATH}")
-    for i, row in enumerate(rows[:10], start=1):
-        raw = row.get("Datum")
-        parsed = parse_czech_date(raw)
-        print(f"{i:02d}. raw={repr(raw)}  ->  parsed={parsed}")
-
-    input("\n🔸 Stiskni Enter pro pokračování nebo ukončení... ")
 
 
 if __name__ == "__main__":
-    if not CSV_PATH.exists():
+    dump_all_transactions()
-        raise SystemExit(f"❌ Soubor {CSV_PATH} nenalezen.")
-    main()

50 Dekurs.py

@@ -20,26 +20,20 @@ from pathlib import Path
 from striprtf.striprtf import rtf_to_text
 from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
 from openpyxl.utils import get_column_letter
+from Functions import get_medicus_connection
 
 # ================== CONFIGURATION ==================
 FDB_PATH = r"z:\Medicus 3\data\MEDICUS.FDB"
 EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
 
-# calculate last 2 months dynamically
+# calculate last 2 months dynamically (now set to 10 days for testing)
-DATE_FROM = (datetime.now() - timedelta(days=365)).strftime("%Y-%m-%d")
+DATE_FROM = (datetime.now() - timedelta(days=10)).strftime("%Y-%m-%d")
 
 timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
 xlsx_path = EXPORT_DIR / f"{timestamp}_Dekurz (poslední rok).xlsx"
 
 # ================== FIREBIRD CONNECTION ==================
-conn = fb.connect(
+conn = get_medicus_connection()
-    host="192.168.1.4",
-    port=3050,
-    database=FDB_PATH,
-    user="SYSDBA",
-    password="masterkey",
-    charset="WIN1250",
-)
 
 def query_df(sql, params=None):
     cur = conn.cursor()
@@ -85,21 +79,29 @@ def safe_rtf_to_text(x):
 
 df["DEKURS"] = df["DEKURS"].apply(safe_rtf_to_text)
 
-df.replace({r'(\r\n|\r|\n)': r'\r\n'}, regex=True, inplace=True)
+# --- Normalize and clean newlines ---
-df.replace({r'[\ud800-\udfff\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]+': ''},
+df["DEKURS"] = (
-           regex=True, inplace=True)
+    df["DEKURS"]
-df.replace({r'(\r\n){2,}': r'\r\n', r'(\r\n)+$': ''},
+    .replace(r"(\r\n|\r|\n)+", "\n", regex=True)  # unify newlines
-           regex=True, inplace=True)
+    .replace(r"\n{2,}", "\n", regex=True)         # collapse multiple blank lines
+    .str.strip()                                  # trim leading/trailing blanks
+)
 
+# --- Remove invalid control characters ---
+df.replace({r"[\ud800-\udfff\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]+": ""}, regex=True, inplace=True)
+
+# --- Merge patient name ---
 df["PACIENT"] = df["PRIJMENI"].fillna("") + ", " + df["JMENO"].fillna("")
 df.drop(columns=["PRIJMENI", "JMENO"], inplace=True)
 
+# --- Rename and format columns ---
 df.rename(columns={"ZKRATKA": "LEKAR", "VYKONY_DNE": "VYKONY DNE"}, inplace=True)
 df["DATUM"] = pd.to_datetime(df["DATUM"], errors="coerce").dt.date
 df.drop(columns=[c for c in df.columns if "ASCII" in c.upper()], inplace=True, errors="ignore")
 
 desired_order = ["DATUM", "RODCIS", "PACIENT", "LEKAR", "VYKONY DNE", "DEKURS"]
 df = df[[c for c in desired_order if c in df.columns]]
+
 # ================== CLEANUP OLD FILES ==================
 for old_file in EXPORT_DIR.glob("*Dekurz (poslední rok)*.xlsx"):
     try:
@@ -107,11 +109,12 @@ for old_file in EXPORT_DIR.glob("*Dekurz (poslední rok)*.xlsx"):
         print(f"🧹 Deleted old file: {old_file.name}")
     except Exception as e:
         print(f"⚠️ Could not delete {old_file.name}: {e}")
+
 # ================== EXPORT TO EXCEL ==================
 with pd.ExcelWriter(xlsx_path, engine="openpyxl") as writer:
     df.to_excel(writer, index=False, sheet_name="Dekurz")
     ws = writer.sheets["Dekurz"]
-
+    ws.freeze_panes = "F2" #zamčení prvního řádku a sloupců A:F
     # ----- Bright yellow header -----
     header_fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
     for cell in ws[1]:

55 Dekurz show decoded.py

@@ -7,14 +7,10 @@ Show decoded physician notes (RTF → plain text) directly in console.
 
 import fdb
 from striprtf.striprtf import rtf_to_text
+from Functions import get_medicus_connection
 
 # ===== connection =====
-con = fdb.connect(
+con = get_medicus_connection()
-    dsn='localhost:z:\\Medicus 3\\data\\medicus.fdb',
-    user='sysdba',
-    password='masterkey',
-    charset='WIN1250'
-)
 cur = con.cursor()
 
 # ===== pick a few recent records =====

70 PDF read ZPMVCR.py

@@ -0,0 +1,31 @@
+
+import pdfplumber
+import pandas as pd
+from pathlib import Path
+
+pdf_path = Path(r"u:\Dropbox\!!!Days\Downloads Z230\prehled 09_2025 zpmvcr.pdf")
+xlsx_path = pdf_path.with_suffix(".xlsx")
+
+all_tables = []
+
+with pdfplumber.open(pdf_path) as pdf:
+    for i, page in enumerate(pdf.pages, start=1):
+        tables = page.extract_tables()
+        if not tables:
+            continue
+        table = tables[0]
+        # Convert to DataFrame, first row = header
+        df = pd.DataFrame(table[1:], columns=table[0])
+        df["page"] = i
+        all_tables.append(df)
+
+if not all_tables:
+    print("❌ No tables found.")
+else:
+    df_all = pd.concat(all_tables, ignore_index=True)
+    print("✅ Combined shape:", df_all.shape)
+    print(df_all.head())
+
+    # Save to Excel
+    df_all.to_excel(xlsx_path, index=False)
+    print(f"💾 Saved to: {xlsx_path}")

80 CtiKapitaceZTabulkyFAK.py

@@ -0,0 +1,111 @@
+import re
+import pandas as pd
+import firebirdsql as fb
+from datetime import datetime, timedelta
+from pathlib import Path
+from striprtf.striprtf import rtf_to_text
+from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
+from openpyxl.utils import get_column_letter
+import textwrap
+
+# ================== CONFIGURATION ==================
+FDB_PATH = r"z:\Medicus 3\data\MEDICUS.FDB"
+EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
+
+# ================== FIREBIRD CONNECTION ==================
+conn = fb.connect(
+    host="192.168.1.4",
+    port=3050,
+    database=FDB_PATH,
+    user="SYSDBA",
+    password="masterkey",
+    charset="WIN1250",
+)
+
+def query_df(sql, params=None):
+    cur = conn.cursor()
+    cur.execute(sql, params or ())
+    rows = cur.fetchall()
+    cols = [d[0].strip().lower() for d in cur.description]  # 👈 normalize
+    return pd.DataFrame(rows, columns=cols)
+# ================== QUERY ==================
+sql = """
+SELECT id, cisfak, poj, datkapod, datkapdo, kapdetail
+FROM fak
+WHERE EXTRACT(YEAR FROM datkapod) = 2025
+  AND EXTRACT(MONTH FROM datkapod) = 9
+  AND poj = '211'
+"""
+df = query_df(sql)
+
+# print(df.columns.tolist())
+# print(df.head())
+
+# Display the first KAPDETAIL text, wrapped nicely
+kap_text = df.loc[0, 'kapdetail']
+# print("\n".join(textwrap.wrap(kap_text, width=100)))
+
+# ========== SOURCE STRING ==========
+text = kap_text
+
+# Extract triplets: patientid;age|price;
+pattern = r"(\d{4});(\d{1,3})\|([\d.]+);"
+matches = re.findall(pattern, text)
+
+# Create dataframe
+dfdavka = pd.DataFrame(matches, columns=["patientid", "age", "price"])
+
+# ✅ Fix small typo: use dfdavka (not df) for conversions
+dfdavka["patientid"] = dfdavka["patientid"].astype(int)
+dfdavka["age"] = dfdavka["age"].astype(int)
+dfdavka["price"] = dfdavka["price"].astype(float)
+
+# ========== LOAD KAR ==========
+sql = "SELECT idpac, rodcis FROM kar"
+dfkar = query_df(sql)
+
+# ========== MERGE ==========
+dfmerged = pd.merge(dfdavka, dfkar, left_on="patientid", right_on="idpac", how="left")
+
+# Optional: reorder columns
+dfmerged = dfmerged[["patientid", "rodcis", "age", "price"]]
+
+print(dfmerged.head())
+print(dfmerged.info())
+
+# ========== OPTIONAL EXPORT ==========
+# outfile = EXPORT_DIR / "kapdetail_merged.xlsx"
+# dfmerged.to_excel(outfile, index=False)
+# print(f"✅ Exported to {outfile}")
+
+
+
+# ========== 1️⃣ Load Excel and prepare dfpoj ==========
+xlsx_path = Path(r"u:\Dropbox\!!!Days\Downloads Z230\prehled 09_2025 zpmvcr.xlsx")
+df = pd.read_excel(xlsx_path)
+
+print("Columns in Excel:", df.columns.tolist())
+
+# Select 2nd column (index 1)
+dfpoj = df.iloc[:, [1]].copy()
+dfpoj.columns = ["rodcis"]  # give proper name
+dfpoj["rodcis"] = dfpoj["rodcis"].astype(str).str.strip()
+
+print(dfpoj.head())
+
+# ========== 2️⃣ Compare dfmerged vs dfpoj ==========
+dfmerged["rodcis"] = dfmerged["rodcis"].astype(str).str.strip()
+
+# Find those in dfmerged but not in dfpoj
+df_missing = dfmerged[~dfmerged["rodcis"].isin(dfpoj["rodcis"])].copy()
+
+print(f"❌ Počet pacientů v dfmerged, kteří NEJSOU v dfpoj: {len(df_missing)}")
+print(df_missing.head())
+
+# ========== 3️⃣ (Optional) Export differences ==========
+EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
+timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+xlsx_out = EXPORT_DIR / f"chybějící_pacienti_{timestamp}.xlsx"
+
+df_missing.to_excel(xlsx_out, index=False)
+print(f"✅ Výsledek uložen do {xlsx_out}")