Upload CSV_HANDLING_GUIDE.ipynb

pages/CSV_HANDLING_GUIDE.ipynb

@@ -0,0 +1,222 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "0r5hCx60Yv0u"
+      },
+      "outputs": [],
+      "source": [
+        "import pandas as pd\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#2. Reading a CSV File"
+      ],
+      "metadata": {
+        "id": "dytrA9JLZJaO"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import pandas as pd\n",
+        "\n",
+        "try:\n",
+        "    # Read the CSV file into a DataFrame\n",
+        "    df = pd.read_csv(r\"/content/sample_data (1).csv\")\n",
+        "    print(df)\n",
+        "except FileNotFoundError:\n",
+        "    print(\"Error: The file was not found.\")\n",
+        "except pd.errors.ParserError:\n",
+        "    print(\"Error: There was a problem parsing the CSV file.\")\n",
+        "except Exception as e:\n",
+        "    print(f\"An unexpected error occurred: {e}\")\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "33v8Kr5LeNYP",
+        "outputId": "2d8e6eef-a25e-4c31-deab-80d4d6da35b8"
+      },
+      "execution_count": 18,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "   ID     Name  Age  Gender           City  Salary\n",
+            "0   1    Alice   25  Female       New York   70000\n",
+            "1   2      Bob   30    Male    Los Angeles   80000\n",
+            "2   3  Charlie   35    Male        Chicago   90000\n",
+            "3   4    Diana   28  Female        Houston   75000\n",
+            "4   5   Edward   40    Male  San Francisco  100000\n",
+            "5   6    Faith   32  Female          Miami   82000\n",
+            "6   7   George   45    Male        Seattle  110000\n",
+            "7   8   Hannah   29  Female         Boston   72000\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import csv\n",
+        "\n",
+        "# Path to your CSV file\n",
+        "csv_file_path = 'employee_data.csv'\n",
+        "\n",
+        "# Function to read CSV using csv module\n",
+        "def read_csv_using_csv_module():\n",
+        "    try:\n",
+        "        with open(r\"/content/sample_data (1).csv\") as file:\n",
+        "            csv_reader = csv.DictReader(file)  # Use DictReader to access columns by name\n",
+        "            print(\"Reading using csv module:\")\n",
+        "            for row in csv_reader:\n",
+        "                try:\n",
+        "                    # Ensuring data types are correct (Age should be an integer, Salary should be numeric)\n",
+        "                    row['Age'] = int(row['Age'])  # Convert Age to integer\n",
+        "                    row['Salary'] = float(row['Salary'])  # Convert Salary to float\n",
+        "                    print(row)\n",
+        "                except ValueError as ve:\n",
+        "                    print(f\"Error: Invalid data type in row {row}. Error: {ve}\")\n",
+        "    except FileNotFoundError:\n",
+        "        print(\"Error: The file was not found.\")\n",
+        "    except csv.Error as e:\n",
+        "        print(f\"Error reading the CSV file with csv module: {e}\")\n",
+        "    except Exception as e:\n",
+        "        print(f\"An unexpected error occurred with csv module: {e}\")\n",
+        "\n",
+        "# Call the function to read using csv module\n",
+        "read_csv_using_csv_module()\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "xvRO2NmZkCPJ",
+        "outputId": "abdb3575-5522-42d2-96d2-69231b60b6a7"
+      },
+      "execution_count": 20,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Reading using csv module:\n",
+            "{'ID': '1', 'Name': 'Alice', 'Age': 25, 'Gender': 'Female', 'City': 'New York', 'Salary': 70000.0}\n",
+            "{'ID': '2', 'Name': 'Bob', 'Age': 30, 'Gender': 'Male', 'City': 'Los Angeles', 'Salary': 80000.0}\n",
+            "{'ID': '3', 'Name': 'Charlie', 'Age': 35, 'Gender': 'Male', 'City': 'Chicago', 'Salary': 90000.0}\n",
+            "{'ID': '4', 'Name': 'Diana', 'Age': 28, 'Gender': 'Female', 'City': 'Houston', 'Salary': 75000.0}\n",
+            "{'ID': '5', 'Name': 'Edward', 'Age': 40, 'Gender': 'Male', 'City': 'San Francisco', 'Salary': 100000.0}\n",
+            "{'ID': '6', 'Name': 'Faith', 'Age': 32, 'Gender': 'Female', 'City': 'Miami', 'Salary': 82000.0}\n",
+            "{'ID': '7', 'Name': 'George', 'Age': 45, 'Gender': 'Male', 'City': 'Seattle', 'Salary': 110000.0}\n",
+            "{'ID': '8', 'Name': 'Hannah', 'Age': 29, 'Gender': 'Female', 'City': 'Boston', 'Salary': 72000.0}\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Using pandas for Reading and Handling Errors"
+      ],
+      "metadata": {
+        "id": "oXkmSf5lkjiP"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import pandas as pd\n",
+        "\n",
+        "# Path to your CSV file\n",
+        "csv_file_path = r\"/content/sample_data (1).csv\"\n",
+        "\n",
+        "# Function to read CSV using pandas\n",
+        "def read_csv_using_pandas():\n",
+        "    try:\n",
+        "        # Read the CSV file into a pandas DataFrame\n",
+        "        df = pd.read_csv(r\"/content/sample_data (1).csv\")\n",
+        "        print(\"\\nReading using pandas:\")\n",
+        "\n",
+        "        # Ensure that the 'Age' and 'Salary' columns are correctly typed\n",
+        "        df['Age'] = pd.to_numeric(df['Age'], errors='raise')  # Ensures Age is numeric\n",
+        "        df['Salary'] = pd.to_numeric(df['Salary'], errors='raise')  # Ensures Salary is numeric\n",
+        "\n",
+        "        # Display the DataFrame\n",
+        "        print(df)\n",
+        "\n",
+        "    except FileNotFoundError:\n",
+        "        print(\"Error: The file was not found.\")\n",
+        "    except pd.errors.ParserError:\n",
+        "        print(\"Error: There was a problem parsing the CSV file with pandas.\")\n",
+        "    except ValueError as ve:\n",
+        "        print(f\"Error: Invalid data type in the CSV file. {ve}\")\n",
+        "    except Exception as e:\n",
+        "        print(f\"An unexpected error occurred with pandas: {e}\")\n",
+        "\n",
+        "# Call the function to read using pandas\n",
+        "read_csv_using_pandas()\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "SItXSSqbkpKr",
+        "outputId": "9e6c4168-bc01-49d8-eabd-18dacab7e3c9"
+      },
+      "execution_count": 21,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "Reading using pandas:\n",
+            "   ID     Name  Age  Gender           City  Salary\n",
+            "0   1    Alice   25  Female       New York   70000\n",
+            "1   2      Bob   30    Male    Los Angeles   80000\n",
+            "2   3  Charlie   35    Male        Chicago   90000\n",
+            "3   4    Diana   28  Female        Houston   75000\n",
+            "4   5   Edward   40    Male  San Francisco  100000\n",
+            "5   6    Faith   32  Female          Miami   82000\n",
+            "6   7   George   45    Male        Seattle  110000\n",
+            "7   8   Hannah   29  Female         Boston   72000\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "L0TGXiLsk0yi"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}