merge_csv_file

merge_csv_file.py

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+# File: merge_csv_by_key.py
+# Task: Merge multiple CSV files by a common key (e.g., "id")
+# Author: VGLUG - Linus Torvalds - 2025
+
+import pandas as pd
+import glob
+import os
+
+def merge_csv_files_by_key(folder_path, key_column, output_file):
+    # Find all CSV files in the given folder
+    csv_files = glob.glob(os.path.join(folder_path, "*.csv"))
+
+    if not csv_files:
+        print("❌ No CSV files found in the folder!")
+        return
+
+    print(f"📂 Found {len(csv_files)} CSV files. Merging by key '{key_column}'...")
+
+    # Read the first CSV as base
+    merged_df = pd.read_csv(csv_files[0])
+    print(f"✅ Loaded: {os.path.basename(csv_files[0])}")
+
+    # Merge all remaining CSV files one by one
+    for file in csv_files[1:]:
+        df = pd.read_csv(file)
+        print(f"🔄 Merging: {os.path.basename(file)}")
+        merged_df = pd.merge(merged_df, df, on=key_column, how="outer")  # or "inner"
+
+    # Save the merged file
+    merged_df.to_csv(output_file, index=False)
+    print(f"\n✅ Successfully merged files saved as: {output_file}")
+
+# ------------------ RUN SECTION ------------------
+if __name__ == "__main__":
+    folder = input("Enter the folder path containing CSV files: ").strip()
+    key = input("Enter the key column name to merge on (e.g., id): ").strip()
+    output = input("Enter output CSV file name (e.g., merged_output.csv): ").strip()
+
+    merge_csv_files_by_key(folder, key, output)
+# File: merge_csv_by_key.py
+# Task: Merge multiple CSV files by a common key (e.g., "id")
+# Author: VGLUG - Linus Torvalds - 2025
+
+import pandas as pd
+import glob
+import os
+
+def merge_csv_files_by_key(folder_path, key_column, output_file):
+    # Find all CSV files in the given folder
+    csv_files = glob.glob(os.path.join(folder_path, "*.csv"))
+
+    if not csv_files:
+        print("❌ No CSV files found in the folder!")
+        return
+
+    print(f"📂 Found {len(csv_files)} CSV files. Merging by key '{key_column}'...")
+
+    # Read the first CSV as base
+    merged_df = pd.read_csv(csv_files[0])
+    print(f"✅ Loaded: {os.path.basename(csv_files[0])}")
+
+    # Merge all remaining CSV files one by one
+    for file in csv_files[1:]:
+        df = pd.read_csv(file)
+        print(f"🔄 Merging: {os.path.basename(file)}")
+        merged_df = pd.merge(merged_df, df, on=key_column, how="outer")  # or "inner"
+
+    # Save the merged file
+    merged_df.to_csv(output_file, index=False)
+    print(f"\n✅ Successfully merged files saved as: {output_file}")
+
+# ------------------ RUN SECTION ------------------
+if __name__ == "__main__":
+    folder = input("Enter the folder path containing CSV files: ").strip()
+    key = input("Enter the key column name to merge on (e.g., id): ").strip()
+    output = input("Enter output CSV file name (e.g., merged_output.csv): ").strip()
+
+    merge_csv_files_by_key(folder, key, output)

typeconversion.py

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+# Sno 3 : "Type Conversion and validation examples: Implement a Python program to type conversion and validation examples"
+
+#conversion of tuple to list
+tuple=(1,2,3,4,5)
+list1=list(tuple)
+print("conversion of tuple to list",list1)
+#conversion of int to float
+a=22
+print("conversion of int to float",float(a))
+#conversion of float to int
+b=33.0
+print("conversion of float to int",int(b))
+#int to string conversion
+c=7888
+print("int to string conversion",str(c))
+#string len to float
+s="swe"
+print("string to float",float(len(s)))