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ProductPriceQuantitySale_DateCustomerCityPayment_Method
0Headphones2163392025-01-01Customer_1MeccaCredit Card
1Printer2280292025-01-02Customer_2MedinaApple Pay
2Keyboard2973422025-01-03Customer_3DammamMada
3Monitor2868442025-01-04Customer_4DammamMada
4Monitor539122025-01-05Customer_5MeccaApple Pay
5Phone2293272025-01-06Customer_6MedinaCash
6Monitor629382025-01-07Customer_7DammamApple Pay
7Mouse107502025-01-08Customer_8MeccaApple Pay
8Phone121372025-01-09Customer_9RiyadhMada
9Keyboard2431212025-01-10Customer_10JeddahMada
10Headphones113212025-01-11Customer_11MeccaMada
11Printer1974132025-01-12Customer_12DammamMada
12Mouse1954452025-01-13Customer_13JeddahCash
13Speaker2340222025-01-14Customer_14MeccaApple Pay
14Headphones1168352025-01-15Customer_15KhobarCash
15Tablet464342025-01-16Customer_16MedinaCredit Card
16Tablet1985182025-01-17Customer_17RiyadhCredit Card
17Phone2954162025-01-18Customer_18DammamApple Pay
18Speaker1483412025-01-19Customer_19MedinaCredit Card
19Printer127442025-01-20Customer_20MedinaApple Pay
\n", "
" ], "text/plain": [ " Product Price Quantity Sale_Date Customer City \\\n", "0 Headphones 2163 39 2025-01-01 Customer_1 Mecca \n", "1 Printer 2280 29 2025-01-02 Customer_2 Medina \n", "2 Keyboard 2973 42 2025-01-03 Customer_3 Dammam \n", "3 Monitor 2868 44 2025-01-04 Customer_4 Dammam \n", "4 Monitor 539 12 2025-01-05 Customer_5 Mecca \n", "5 Phone 2293 27 2025-01-06 Customer_6 Medina \n", "6 Monitor 629 38 2025-01-07 Customer_7 Dammam \n", "7 Mouse 107 50 2025-01-08 Customer_8 Mecca \n", "8 Phone 1213 7 2025-01-09 Customer_9 Riyadh \n", "9 Keyboard 2431 21 2025-01-10 Customer_10 Jeddah \n", "10 Headphones 1132 1 2025-01-11 Customer_11 Mecca \n", "11 Printer 1974 13 2025-01-12 Customer_12 Dammam \n", "12 Mouse 1954 45 2025-01-13 Customer_13 Jeddah \n", "13 Speaker 2340 22 2025-01-14 Customer_14 Mecca \n", "14 Headphones 1168 35 2025-01-15 Customer_15 Khobar \n", "15 Tablet 464 34 2025-01-16 Customer_16 Medina \n", "16 Tablet 1985 18 2025-01-17 Customer_17 Riyadh \n", "17 Phone 2954 16 2025-01-18 Customer_18 Dammam \n", "18 Speaker 1483 41 2025-01-19 Customer_19 Medina \n", "19 Printer 127 44 2025-01-20 Customer_20 Medina \n", "\n", " Payment_Method \n", "0 Credit Card \n", "1 Apple Pay \n", "2 Mada \n", "3 Mada \n", "4 Apple Pay \n", "5 Cash \n", "6 Apple Pay \n", "7 Apple Pay \n", "8 Mada \n", "9 Mada \n", "10 Mada \n", "11 Mada \n", "12 Cash \n", "13 Apple Pay \n", "14 Cash \n", "15 Credit Card \n", "16 Credit Card \n", "17 Apple Pay \n", "18 Credit Card \n", "19 Apple Pay " ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "data = pd.read_csv('big_sales_data.csv')\n", "data.head(20)" ] }, { "cell_type": "code", "execution_count": 2, "id": "f10f1b22-562c-4d73-a28c-625c3770f2bd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Product object\n", "Price int64\n", "Quantity int64\n", "Sale_Date object\n", "Customer object\n", "City object\n", "Payment_Method object\n", "dtype: object" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.dtypes" ] }, { "cell_type": "code", "execution_count": 3, "id": "4cd74000-bd5f-46c4-a59c-20df6456f783", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.duplicated().sum()" ] }, { "cell_type": "code", "execution_count": 13, "id": "35cb2616-90a1-483f-b210-1c075f6f9373", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(100, 7)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = data.drop_duplicates()\n", "data.shape" ] }, { "cell_type": "code", "execution_count": 12, "id": "d7cf34ac-87aa-4605-b2d5-1d98665b06bb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ProductPriceQuantitySale_DateCustomerCityPayment_Method
0Headphones2163392025-01-01Customer_1MeccaCredit Card
1Printer2280292025-01-02Customer_2MedinaApple Pay
2Keyboard2973422025-01-03Customer_3DammamMada
3Monitor2868442025-01-04Customer_4DammamMada
4Monitor539122025-01-05Customer_5MeccaApple Pay
5Phone2293272025-01-06Customer_6MedinaCash
6Monitor629382025-01-07Customer_7DammamApple Pay
7Mouse107502025-01-08Customer_8MeccaApple Pay
8Phone121372025-01-09Customer_9RiyadhMada
9Keyboard2431212025-01-10Customer_10JeddahMada
10Headphones113212025-01-11Customer_11MeccaMada
11Printer1974132025-01-12Customer_12DammamMada
12Mouse1954452025-01-13Customer_13JeddahCash
13Speaker2340222025-01-14Customer_14MeccaApple Pay
14Headphones1168352025-01-15Customer_15KhobarCash
15Tablet464342025-01-16Customer_16MedinaCredit Card
16Tablet1985182025-01-17Customer_17RiyadhCredit Card
17Phone2954162025-01-18Customer_18DammamApple Pay
18Speaker1483412025-01-19Customer_19MedinaCredit Card
19Printer127442025-01-20Customer_20MedinaApple Pay
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" ], "text/plain": [ " Product Price Quantity Sale_Date Customer City \\\n", "0 Headphones 2163 39 2025-01-01 Customer_1 Mecca \n", "1 Printer 2280 29 2025-01-02 Customer_2 Medina \n", "2 Keyboard 2973 42 2025-01-03 Customer_3 Dammam \n", "3 Monitor 2868 44 2025-01-04 Customer_4 Dammam \n", "4 Monitor 539 12 2025-01-05 Customer_5 Mecca \n", "5 Phone 2293 27 2025-01-06 Customer_6 Medina \n", "6 Monitor 629 38 2025-01-07 Customer_7 Dammam \n", "7 Mouse 107 50 2025-01-08 Customer_8 Mecca \n", "8 Phone 1213 7 2025-01-09 Customer_9 Riyadh \n", "9 Keyboard 2431 21 2025-01-10 Customer_10 Jeddah \n", "10 Headphones 1132 1 2025-01-11 Customer_11 Mecca \n", "11 Printer 1974 13 2025-01-12 Customer_12 Dammam \n", "12 Mouse 1954 45 2025-01-13 Customer_13 Jeddah \n", "13 Speaker 2340 22 2025-01-14 Customer_14 Mecca \n", "14 Headphones 1168 35 2025-01-15 Customer_15 Khobar \n", "15 Tablet 464 34 2025-01-16 Customer_16 Medina \n", "16 Tablet 1985 18 2025-01-17 Customer_17 Riyadh \n", "17 Phone 2954 16 2025-01-18 Customer_18 Dammam \n", "18 Speaker 1483 41 2025-01-19 Customer_19 Medina \n", "19 Printer 127 44 2025-01-20 Customer_20 Medina \n", "\n", " Payment_Method \n", "0 Credit Card \n", "1 Apple Pay \n", "2 Mada \n", "3 Mada \n", "4 Apple Pay \n", "5 Cash \n", "6 Apple Pay \n", "7 Apple Pay \n", "8 Mada \n", "9 Mada \n", "10 Mada \n", "11 Mada \n", "12 Cash \n", "13 Apple Pay \n", "14 Cash \n", "15 Credit Card \n", "16 Credit Card \n", "17 Apple Pay \n", "18 Credit Card \n", "19 Apple Pay " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.head(20)" ] }, { "cell_type": "code", "execution_count": 15, "id": "fb294048-2b25-40f0-a9b5-4a23bd8814ac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Columns dropped: []\n", "Remaining columns: Index(['Product', 'Price', 'Quantity', 'Sale_Date', 'Customer', 'City',\n", " 'Payment_Method'],\n", " dtype='object')\n" ] } ], "source": [ "missing_percentage = data.isnull().mean() * 100\n", "threshold = 30\n", "columns_to_drop = missing_percentage[missing_percentage > threshold].index\n", "data = data.drop(columns=columns_to_drop)\n", "print(f\"Columns dropped: {list(columns_to_drop)}\")\n", "print(f\"Remaining columns: {data.columns}\")" ] }, { "cell_type": "code", "execution_count": 16, "id": "ba0c20c4-8ea2-46dd-b9a9-667b1336cc18", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ProductPriceQuantitySale_DateCustomerCityPayment_Method
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" ], "text/plain": [ " Product Price Quantity Sale_Date Customer City Payment_Method\n", "0 1 2163 39 0 0 3 2\n", "1 7 2280 29 1 12 4 0\n", "2 2 2973 42 2 23 0 3\n", "3 4 2868 44 3 34 0 3\n", "4 4 539 12 4 45 3 0" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.preprocessing import LabelEncoder\n", "\n", "label_encoder = LabelEncoder()\n", "\n", "for column in data.select_dtypes(include=['object']).columns:\n", " data[column] = label_encoder.fit_transform(data[column])\n", "\n", "data.head()" ] }, { "cell_type": "code", "execution_count": 17, "id": "635129c6-f6f3-4a1e-89f5-c9277bd2d81b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Product 0\n", "Price 0\n", "Quantity 0\n", "Sale_Date 0\n", "Customer 0\n", "City 0\n", "Payment_Method 0\n", "dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "for column in data.select_dtypes(include=['float64']).columns:\n", " mean_value = data[column].mean()\n", " data[column] = data[column].fillna(mean_value)\n", "\n", "for column in data.select_dtypes(include=['object']).columns:\n", " mode_value = data[column].mode()[0]\n", " data[column] = data[column].fillna(mode_value)\n", "\n", "data.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 18, "id": "cb45fb58-d6cd-482c-9b0b-3fb24a892356", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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100 rows × 7 columns

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" ], "text/plain": [ " Product Price Quantity Sale_Date Customer City Payment_Method\n", "0 1 2163 39 0 0 3 2\n", "1 7 2280 29 1 12 4 0\n", "2 2 2973 42 2 23 0 3\n", "3 4 2868 44 3 34 0 3\n", "4 4 539 12 4 45 3 0\n", ".. ... ... ... ... ... ... ...\n", "95 2 1659 32 95 96 1 0\n", "96 5 1556 42 96 97 5 0\n", "97 6 698 21 97 98 2 1\n", "98 5 2621 43 98 99 3 3\n", "99 2 1664 47 99 2 4 0\n", "\n", "[100 rows x 7 columns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 19, "id": "c187b5ba-3644-4186-8c7c-cd322ffe1c07", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sum of null values in each column\n", "Product 0\n", "Price 0\n", "Quantity 0\n", "Sale_Date 0\n", "Customer 0\n", "City 0\n", "Payment_Method 0\n", "dtype: int64\n" ] } ], "source": [ "def replace_outliers_with_nan(column):\n", " Q1 = column.quantile(0.25)\n", " Q3 = column.quantile(0.75)\n", " IQR = Q3 - Q1\n", " lower_bound = Q1 - 1.5 * IQR\n", " upper_bound = Q3 + 1.5 * IQR\n", " return column.where((column >= lower_bound) & (column <= upper_bound), np.nan)\n", "\n", "for col in data.select_dtypes(include=['float64', 'int64']).columns:\n", " data[col] = replace_outliers_with_nan(data[col])\n", "\n", "null_counts = data.isnull().sum()\n", "print(\"Sum of null values in each column\")\n", "print(null_counts)" ] }, { "cell_type": "code", "execution_count": 9, "id": "c7054312-24b4-4bb2-9484-a6022416e8b4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.countplot(x='Payment_Method', data=data)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 33, "id": "55874e99-4780-41c9-8e14-e9b0aeeae967", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.scatterplot(x='Price', y='Quantity', data=data)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 7, "id": "3cf0eda1-5d80-47a0-9184-8d442e8d0fdd", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(X_test, y_test, color='blue')\n", "plt.plot(X_test, y_pred, color='red')\n", "plt.xlabel('Price')\n", "plt.ylabel('Quantity')\n", "plt.title('Price vs Quantity Prediction')\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "anaconda-2024.02-py310", "language": "python", "name": "conda-env-anaconda-2024.02-py310-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.14" } }, "nbformat": 4, "nbformat_minor": 5 }