{ "cells": [ { "cell_type": "markdown", "id": "86a791a4", "metadata": {}, "source": [ "## Importing Data" ] }, { "cell_type": "code", "execution_count": 1, "id": "a5c7d964", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Row IDOrder IDOrder DateShip DateShip ModeCustomer IDCustomer NameSegmentCountry/RegionCity...Postal CodeRegionProduct IDCategorySub-CategoryProduct NameSalesQuantityDiscountProfit
01CA-2018-1521562018-11-082018-11-11Second ClassCG-12520Claire GuteConsumerUnited StatesHenderson...42420.0SouthFUR-BO-10001798FurnitureBookcasesBush Somerset Collection Bookcase261.960020.0041.9136
12CA-2018-1521562018-11-082018-11-11Second ClassCG-12520Claire GuteConsumerUnited StatesHenderson...42420.0SouthFUR-CH-10000454FurnitureChairsHon Deluxe Fabric Upholstered Stacking Chairs,...731.940030.00219.5820
23CA-2018-1386882018-06-122018-06-16Second ClassDV-13045Darrin Van HuffCorporateUnited StatesLos Angeles...90036.0WestOFF-LA-10000240Office SuppliesLabelsSelf-Adhesive Address Labels for Typewriters b...14.620020.006.8714
34US-2017-1089662017-10-112017-10-18Standard ClassSO-20335Sean O'DonnellConsumerUnited StatesFort Lauderdale...33311.0SouthFUR-TA-10000577FurnitureTablesBretford CR4500 Series Slim Rectangular Table957.577550.45-383.0310
45US-2017-1089662017-10-112017-10-18Standard ClassSO-20335Sean O'DonnellConsumerUnited StatesFort Lauderdale...33311.0SouthOFF-ST-10000760Office SuppliesStorageEldon Fold 'N Roll Cart System22.368020.202.5164
..................................................................
99899990CA-2016-1104222016-01-212016-01-23Second ClassTB-21400Tom BoeckenhauerConsumerUnited StatesMiami...33180.0SouthFUR-FU-10001889FurnitureFurnishingsUltra Door Pull Handle25.248030.204.1028
99909991CA-2019-1212582019-02-262019-03-03Standard ClassDB-13060Dave BrooksConsumerUnited StatesCosta Mesa...92627.0WestFUR-FU-10000747FurnitureFurnishingsTenex B1-RE Series Chair Mats for Low Pile Car...91.960020.0015.6332
99919992CA-2019-1212582019-02-262019-03-03Standard ClassDB-13060Dave BrooksConsumerUnited StatesCosta Mesa...92627.0WestTEC-PH-10003645TechnologyPhonesAastra 57i VoIP phone258.576020.2019.3932
99929993CA-2019-1212582019-02-262019-03-03Standard ClassDB-13060Dave BrooksConsumerUnited StatesCosta Mesa...92627.0WestOFF-PA-10004041Office SuppliesPaperIt's Hot Message Books with Stickers, 2 3/4\" x 5\"29.600040.0013.3200
99939994CA-2019-1199142019-05-042019-05-09Second ClassCC-12220Chris CortesConsumerUnited StatesWestminster...92683.0WestOFF-AP-10002684Office SuppliesAppliancesAcco 7-Outlet Masterpiece Power Center, Wihtou...243.160020.0072.9480
\n", "

9994 rows × 21 columns

\n", "
" ], "text/plain": [ " Row ID Order ID Order Date Ship Date Ship Mode \\\n", "0 1 CA-2018-152156 2018-11-08 2018-11-11 Second Class \n", "1 2 CA-2018-152156 2018-11-08 2018-11-11 Second Class \n", "2 3 CA-2018-138688 2018-06-12 2018-06-16 Second Class \n", "3 4 US-2017-108966 2017-10-11 2017-10-18 Standard Class \n", "4 5 US-2017-108966 2017-10-11 2017-10-18 Standard Class \n", "... ... ... ... ... ... \n", "9989 9990 CA-2016-110422 2016-01-21 2016-01-23 Second Class \n", "9990 9991 CA-2019-121258 2019-02-26 2019-03-03 Standard Class \n", "9991 9992 CA-2019-121258 2019-02-26 2019-03-03 Standard Class \n", "9992 9993 CA-2019-121258 2019-02-26 2019-03-03 Standard Class \n", "9993 9994 CA-2019-119914 2019-05-04 2019-05-09 Second Class \n", "\n", " Customer ID Customer Name Segment Country/Region City \\\n", "0 CG-12520 Claire Gute Consumer United States Henderson \n", "1 CG-12520 Claire Gute Consumer United States Henderson \n", "2 DV-13045 Darrin Van Huff Corporate United States Los Angeles \n", "3 SO-20335 Sean O'Donnell Consumer United States Fort Lauderdale \n", "4 SO-20335 Sean O'Donnell Consumer United States Fort Lauderdale \n", "... ... ... ... ... ... \n", "9989 TB-21400 Tom Boeckenhauer Consumer United States Miami \n", "9990 DB-13060 Dave Brooks Consumer United States Costa Mesa \n", "9991 DB-13060 Dave Brooks Consumer United States Costa Mesa \n", "9992 DB-13060 Dave Brooks Consumer United States Costa Mesa \n", "9993 CC-12220 Chris Cortes Consumer United States Westminster \n", "\n", " ... Postal Code Region Product ID Category Sub-Category \\\n", "0 ... 42420.0 South FUR-BO-10001798 Furniture Bookcases \n", "1 ... 42420.0 South FUR-CH-10000454 Furniture Chairs \n", "2 ... 90036.0 West OFF-LA-10000240 Office Supplies Labels \n", "3 ... 33311.0 South FUR-TA-10000577 Furniture Tables \n", "4 ... 33311.0 South OFF-ST-10000760 Office Supplies Storage \n", "... ... ... ... ... ... ... \n", "9989 ... 33180.0 South FUR-FU-10001889 Furniture Furnishings \n", "9990 ... 92627.0 West FUR-FU-10000747 Furniture Furnishings \n", "9991 ... 92627.0 West TEC-PH-10003645 Technology Phones \n", "9992 ... 92627.0 West OFF-PA-10004041 Office Supplies Paper \n", "9993 ... 92683.0 West OFF-AP-10002684 Office Supplies Appliances \n", "\n", " Product Name Sales Quantity \\\n", "0 Bush Somerset Collection Bookcase 261.9600 2 \n", "1 Hon Deluxe Fabric Upholstered Stacking Chairs,... 731.9400 3 \n", "2 Self-Adhesive Address Labels for Typewriters b... 14.6200 2 \n", "3 Bretford CR4500 Series Slim Rectangular Table 957.5775 5 \n", "4 Eldon Fold 'N Roll Cart System 22.3680 2 \n", "... ... ... ... \n", "9989 Ultra Door Pull Handle 25.2480 3 \n", "9990 Tenex B1-RE Series Chair Mats for Low Pile Car... 91.9600 2 \n", "9991 Aastra 57i VoIP phone 258.5760 2 \n", "9992 It's Hot Message Books with Stickers, 2 3/4\" x 5\" 29.6000 4 \n", "9993 Acco 7-Outlet Masterpiece Power Center, Wihtou... 243.1600 2 \n", "\n", " Discount Profit \n", "0 0.00 41.9136 \n", "1 0.00 219.5820 \n", "2 0.00 6.8714 \n", "3 0.45 -383.0310 \n", "4 0.20 2.5164 \n", "... ... ... \n", "9989 0.20 4.1028 \n", "9990 0.00 15.6332 \n", "9991 0.20 19.3932 \n", "9992 0.00 13.3200 \n", "9993 0.00 72.9480 \n", "\n", "[9994 rows x 21 columns]" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "superstore = pd.read_excel(r\"data/Superstore.xls\")\n", "superstore" ] }, { "cell_type": "markdown", "id": "c84c0c48", "metadata": {}, "source": [ "## Initial Data Inspection" ] }, { "cell_type": "code", "execution_count": 2, "id": "bdc3c57f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Row IDOrder IDOrder DateShip DateShip ModeCustomer IDCustomer NameSegmentCountry/RegionCity...Postal CodeRegionProduct IDCategorySub-CategoryProduct NameSalesQuantityDiscountProfit
01CA-2018-1521562018-11-082018-11-11Second ClassCG-12520Claire GuteConsumerUnited StatesHenderson...42420.0SouthFUR-BO-10001798FurnitureBookcasesBush Somerset Collection Bookcase261.960020.0041.9136
12CA-2018-1521562018-11-082018-11-11Second ClassCG-12520Claire GuteConsumerUnited StatesHenderson...42420.0SouthFUR-CH-10000454FurnitureChairsHon Deluxe Fabric Upholstered Stacking Chairs,...731.940030.00219.5820
23CA-2018-1386882018-06-122018-06-16Second ClassDV-13045Darrin Van HuffCorporateUnited StatesLos Angeles...90036.0WestOFF-LA-10000240Office SuppliesLabelsSelf-Adhesive Address Labels for Typewriters b...14.620020.006.8714
34US-2017-1089662017-10-112017-10-18Standard ClassSO-20335Sean O'DonnellConsumerUnited StatesFort Lauderdale...33311.0SouthFUR-TA-10000577FurnitureTablesBretford CR4500 Series Slim Rectangular Table957.577550.45-383.0310
45US-2017-1089662017-10-112017-10-18Standard ClassSO-20335Sean O'DonnellConsumerUnited StatesFort Lauderdale...33311.0SouthOFF-ST-10000760Office SuppliesStorageEldon Fold 'N Roll Cart System22.368020.202.5164
\n", "

5 rows × 21 columns

\n", "
" ], "text/plain": [ " Row ID Order ID Order Date Ship Date Ship Mode Customer ID \\\n", "0 1 CA-2018-152156 2018-11-08 2018-11-11 Second Class CG-12520 \n", "1 2 CA-2018-152156 2018-11-08 2018-11-11 Second Class CG-12520 \n", "2 3 CA-2018-138688 2018-06-12 2018-06-16 Second Class DV-13045 \n", "3 4 US-2017-108966 2017-10-11 2017-10-18 Standard Class SO-20335 \n", "4 5 US-2017-108966 2017-10-11 2017-10-18 Standard Class SO-20335 \n", "\n", " Customer Name Segment Country/Region City ... \\\n", "0 Claire Gute Consumer United States Henderson ... \n", "1 Claire Gute Consumer United States Henderson ... \n", "2 Darrin Van Huff Corporate United States Los Angeles ... \n", "3 Sean O'Donnell Consumer United States Fort Lauderdale ... \n", "4 Sean O'Donnell Consumer United States Fort Lauderdale ... \n", "\n", " Postal Code Region Product ID Category Sub-Category \\\n", "0 42420.0 South FUR-BO-10001798 Furniture Bookcases \n", "1 42420.0 South FUR-CH-10000454 Furniture Chairs \n", "2 90036.0 West OFF-LA-10000240 Office Supplies Labels \n", "3 33311.0 South FUR-TA-10000577 Furniture Tables \n", "4 33311.0 South OFF-ST-10000760 Office Supplies Storage \n", "\n", " Product Name Sales Quantity \\\n", "0 Bush Somerset Collection Bookcase 261.9600 2 \n", "1 Hon Deluxe Fabric Upholstered Stacking Chairs,... 731.9400 3 \n", "2 Self-Adhesive Address Labels for Typewriters b... 14.6200 2 \n", "3 Bretford CR4500 Series Slim Rectangular Table 957.5775 5 \n", "4 Eldon Fold 'N Roll Cart System 22.3680 2 \n", "\n", " Discount Profit \n", "0 0.00 41.9136 \n", "1 0.00 219.5820 \n", "2 0.00 6.8714 \n", "3 0.45 -383.0310 \n", "4 0.20 2.5164 \n", "\n", "[5 rows x 21 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore.head()" ] }, { "cell_type": "code", "execution_count": 3, "id": "ab3ae174", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(9994, 21)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# checking to see all the orders took place in U.S or not\n", "superstore[superstore[\"Country/Region\"] == \"United States\"].shape" ] }, { "cell_type": "code", "execution_count": 4, "id": "29bbbf26", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(9994, 21)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore.shape" ] }, { "cell_type": "code", "execution_count": 5, "id": "b93ee93b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Row ID 0\n", "Order ID 0\n", "Order Date 0\n", "Ship Date 0\n", "Ship Mode 0\n", "Customer ID 0\n", "Customer Name 0\n", "Segment 0\n", "Country/Region 0\n", "City 0\n", "State 0\n", "Postal Code 11\n", "Region 0\n", "Product ID 0\n", "Category 0\n", "Sub-Category 0\n", "Product Name 0\n", "Sales 0\n", "Quantity 0\n", "Discount 0\n", "Profit 0\n", "dtype: int64" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 6, "id": "8f555d7e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Row IDOrder IDOrder DateShip DateShip ModeCustomer IDCustomer NameSegmentCountry/RegionCity...Postal CodeRegionProduct IDCategorySub-CategoryProduct NameSalesQuantityDiscountProfit
22342235CA-2019-1040662019-12-052019-12-10Standard ClassQJ-19255Quincy JonesCorporateUnited StatesBurlington...NaNEastTEC-AC-10001013TechnologyAccessoriesLogitech ClearChat Comfort/USB Headset H390205.0370.067.6599
52745275CA-2017-1628872017-11-072017-11-09Second ClassSV-20785Stewart VisinskyConsumerUnited StatesBurlington...NaNEastFUR-CH-10000595FurnitureChairsSafco Contoured Stacking Chairs715.2030.0178.8000
87988799US-2018-1501402018-04-062018-04-10Standard ClassVM-21685Valerie MitchumHome OfficeUnited StatesBurlington...NaNEastTEC-PH-10002555TechnologyPhonesNortel Meridian M5316 Digital phone1294.7550.0336.6350
91469147US-2018-1655052018-01-232018-01-27Standard ClassCB-12535Claudia BergmannCorporateUnited StatesBurlington...NaNEastTEC-AC-10002926TechnologyAccessoriesLogitech Wireless Marathon Mouse M70599.9820.042.9914
91479148US-2018-1655052018-01-232018-01-27Standard ClassCB-12535Claudia BergmannCorporateUnited StatesBurlington...NaNEastOFF-AR-10003477Office SuppliesArt4009 Highlighters8.0460.02.7336
91489149US-2018-1655052018-01-232018-01-27Standard ClassCB-12535Claudia BergmannCorporateUnited StatesBurlington...NaNEastOFF-ST-10001526Office SuppliesStorageIceberg Mobile Mega Data/Printer Cart1564.29130.0406.7154
93869387US-2019-1272922019-01-192019-01-23Standard ClassRM-19375Raymond MesseConsumerUnited StatesBurlington...NaNEastOFF-PA-10000157Office SuppliesPaperXerox 19179.9240.037.5624
93879388US-2019-1272922019-01-192019-01-23Standard ClassRM-19375Raymond MesseConsumerUnited StatesBurlington...NaNEastOFF-PA-10001970Office SuppliesPaperXerox 188112.2810.05.7716
93889389US-2019-1272922019-01-192019-01-23Standard ClassRM-19375Raymond MesseConsumerUnited StatesBurlington...NaNEastOFF-AP-10000828Office SuppliesAppliancesAvanti 4.4 Cu. Ft. Refrigerator542.9430.0152.0232
93899390US-2019-1272922019-01-192019-01-23Standard ClassRM-19375Raymond MesseConsumerUnited StatesBurlington...NaNEastOFF-EN-10001509Office SuppliesEnvelopesPoly String Tie Envelopes2.0410.00.9588
97419742CA-2017-1170862017-11-082017-11-12Standard ClassQJ-19255Quincy JonesCorporateUnited StatesBurlington...NaNEastFUR-BO-10004834FurnitureBookcasesRiverside Palais Royal Lawyers Bookcase, Royal...4404.9050.01013.1270
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11 rows × 21 columns

\n", "
" ], "text/plain": [ " Row ID Order ID Order Date Ship Date Ship Mode \\\n", "2234 2235 CA-2019-104066 2019-12-05 2019-12-10 Standard Class \n", "5274 5275 CA-2017-162887 2017-11-07 2017-11-09 Second Class \n", "8798 8799 US-2018-150140 2018-04-06 2018-04-10 Standard Class \n", "9146 9147 US-2018-165505 2018-01-23 2018-01-27 Standard Class \n", "9147 9148 US-2018-165505 2018-01-23 2018-01-27 Standard Class \n", "9148 9149 US-2018-165505 2018-01-23 2018-01-27 Standard Class \n", "9386 9387 US-2019-127292 2019-01-19 2019-01-23 Standard Class \n", "9387 9388 US-2019-127292 2019-01-19 2019-01-23 Standard Class \n", "9388 9389 US-2019-127292 2019-01-19 2019-01-23 Standard Class \n", "9389 9390 US-2019-127292 2019-01-19 2019-01-23 Standard Class \n", "9741 9742 CA-2017-117086 2017-11-08 2017-11-12 Standard Class \n", "\n", " Customer ID Customer Name Segment Country/Region City \\\n", "2234 QJ-19255 Quincy Jones Corporate United States Burlington \n", "5274 SV-20785 Stewart Visinsky Consumer United States Burlington \n", "8798 VM-21685 Valerie Mitchum Home Office United States Burlington \n", "9146 CB-12535 Claudia Bergmann Corporate United States Burlington \n", "9147 CB-12535 Claudia Bergmann Corporate United States Burlington \n", "9148 CB-12535 Claudia Bergmann Corporate United States Burlington \n", "9386 RM-19375 Raymond Messe Consumer United States Burlington \n", "9387 RM-19375 Raymond Messe Consumer United States Burlington \n", "9388 RM-19375 Raymond Messe Consumer United States Burlington \n", "9389 RM-19375 Raymond Messe Consumer United States Burlington \n", "9741 QJ-19255 Quincy Jones Corporate United States Burlington \n", "\n", " ... Postal Code Region Product ID Category Sub-Category \\\n", "2234 ... NaN East TEC-AC-10001013 Technology Accessories \n", "5274 ... NaN East FUR-CH-10000595 Furniture Chairs \n", "8798 ... NaN East TEC-PH-10002555 Technology Phones \n", "9146 ... NaN East TEC-AC-10002926 Technology Accessories \n", "9147 ... NaN East OFF-AR-10003477 Office Supplies Art \n", "9148 ... NaN East OFF-ST-10001526 Office Supplies Storage \n", "9386 ... NaN East OFF-PA-10000157 Office Supplies Paper \n", "9387 ... NaN East OFF-PA-10001970 Office Supplies Paper \n", "9388 ... NaN East OFF-AP-10000828 Office Supplies Appliances \n", "9389 ... NaN East OFF-EN-10001509 Office Supplies Envelopes \n", "9741 ... NaN East FUR-BO-10004834 Furniture Bookcases \n", "\n", " Product Name Sales Quantity \\\n", "2234 Logitech ClearChat Comfort/USB Headset H390 205.03 7 \n", "5274 Safco Contoured Stacking Chairs 715.20 3 \n", "8798 Nortel Meridian M5316 Digital phone 1294.75 5 \n", "9146 Logitech Wireless Marathon Mouse M705 99.98 2 \n", "9147 4009 Highlighters 8.04 6 \n", "9148 Iceberg Mobile Mega Data/Printer Cart 1564.29 13 \n", "9386 Xerox 191 79.92 4 \n", "9387 Xerox 1881 12.28 1 \n", "9388 Avanti 4.4 Cu. Ft. Refrigerator 542.94 3 \n", "9389 Poly String Tie Envelopes 2.04 1 \n", "9741 Riverside Palais Royal Lawyers Bookcase, Royal... 4404.90 5 \n", "\n", " Discount Profit \n", "2234 0.0 67.6599 \n", "5274 0.0 178.8000 \n", "8798 0.0 336.6350 \n", "9146 0.0 42.9914 \n", "9147 0.0 2.7336 \n", "9148 0.0 406.7154 \n", "9386 0.0 37.5624 \n", "9387 0.0 5.7716 \n", "9388 0.0 152.0232 \n", "9389 0.0 0.9588 \n", "9741 0.0 1013.1270 \n", "\n", "[11 rows x 21 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[superstore[\"Postal Code\"].isnull()]" ] }, { "cell_type": "code", "execution_count": 7, "id": "86699971", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Row ID 0\n", "Order ID 0\n", "Order Date 0\n", "Ship Date 0\n", "Ship Mode 0\n", "Customer ID 0\n", "Customer Name 0\n", "Segment 0\n", "Country/Region 0\n", "City 0\n", "State 0\n", "Postal Code 0\n", "Region 0\n", "Product ID 0\n", "Category 0\n", "Sub-Category 0\n", "Product Name 0\n", "Sales 0\n", "Quantity 0\n", "Discount 0\n", "Profit 0\n", "dtype: int64" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[\"Postal Code\"] = superstore[\"Postal Code\"].fillna(0)\n", "superstore.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 8, "id": "83c90d84", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.int64(0)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore.duplicated().sum()" ] }, { "cell_type": "code", "execution_count": 9, "id": "6cafb94e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 9994 entries, 0 to 9993\n", "Data columns (total 21 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Row ID 9994 non-null int64 \n", " 1 Order ID 9994 non-null str \n", " 2 Order Date 9994 non-null datetime64[us]\n", " 3 Ship Date 9994 non-null datetime64[us]\n", " 4 Ship Mode 9994 non-null str \n", " 5 Customer ID 9994 non-null str \n", " 6 Customer Name 9994 non-null str \n", " 7 Segment 9994 non-null str \n", " 8 Country/Region 9994 non-null str \n", " 9 City 9994 non-null str \n", " 10 State 9994 non-null str \n", " 11 Postal Code 9994 non-null float64 \n", " 12 Region 9994 non-null str \n", " 13 Product ID 9994 non-null str \n", " 14 Category 9994 non-null str \n", " 15 Sub-Category 9994 non-null str \n", " 16 Product Name 9994 non-null str \n", " 17 Sales 9994 non-null float64 \n", " 18 Quantity 9994 non-null int64 \n", " 19 Discount 9994 non-null float64 \n", " 20 Profit 9994 non-null float64 \n", "dtypes: datetime64[us](2), float64(4), int64(2), str(13)\n", "memory usage: 1.6 MB\n" ] } ], "source": [ "superstore.info()" ] }, { "cell_type": "markdown", "id": "4cdafcf0", "metadata": {}, "source": [ "## preprocessing pipelines:" ] }, { "cell_type": "code", "execution_count": 10, "id": "416c042b", "metadata": {}, "outputs": [], "source": [ "class DataCleaner:\n", "\n", " def __init__(self, df):\n", " self.df = df.copy()\n", "\n", " def convert_to_category(self, cat_columns):\n", " for col in cat_columns:\n", " try:\n", " self.df[col] = self.df[col].astype(\"category\")\n", " except KeyError:\n", " print(f\"Column '{col}' not found, skipped.\")\n", " return self.df\n", "\n", " def clean_text_columns(self, text_columns):\n", " for col in text_columns:\n", " try:\n", " self.df[col] = self.df[col].astype(str).str.strip()\n", " except KeyError:\n", " print(f\"Column '{col}' not found, skipped.\")\n", " return self.df\n", "\n", " def detect_outliers_iqr(self, numeric_columns):\n", " report = {}\n", " for col in numeric_columns:\n", " try:\n", " Q1, Q3 = self.df[col].quantile([0.25, 0.75])\n", " IQR = Q3 - Q1\n", " lower, upper = Q1 - 1.5 * IQR, Q3 + 1.5 * IQR\n", " mask = (self.df[col] < lower) | (self.df[col] > upper)\n", " report[col] = mask.sum()\n", " except Exception as e:\n", " print(f\"Error checking '{col}': {e}\")\n", " return report\n", "\n", " def get_cleaned_data(self):\n", " return self.df" ] }, { "cell_type": "code", "execution_count": 11, "id": "f889f0d2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " Outlier Report : \n" ] }, { "data": { "text/plain": [ "{'Sales': np.int64(1167),\n", " 'Profit': np.int64(1881),\n", " 'Discount': np.int64(856),\n", " 'Quantity': np.int64(170)}" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 9994 entries, 0 to 9993\n", "Data columns (total 21 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Row ID 9994 non-null int64 \n", " 1 Order ID 9994 non-null str \n", " 2 Order Date 9994 non-null datetime64[us]\n", " 3 Ship Date 9994 non-null datetime64[us]\n", " 4 Ship Mode 9994 non-null category \n", " 5 Customer ID 9994 non-null category \n", " 6 Customer Name 9994 non-null str \n", " 7 Segment 9994 non-null category \n", " 8 Country/Region 9994 non-null category \n", " 9 City 9994 non-null str \n", " 10 State 9994 non-null str \n", " 11 Postal Code 9994 non-null float64 \n", " 12 Region 9994 non-null category \n", " 13 Product ID 9994 non-null str \n", " 14 Category 9994 non-null category \n", " 15 Sub-Category 9994 non-null category \n", " 16 Product Name 9994 non-null str \n", " 17 Sales 9994 non-null float64 \n", " 18 Quantity 9994 non-null int64 \n", " 19 Discount 9994 non-null float64 \n", " 20 Profit 9994 non-null float64 \n", "dtypes: category(7), datetime64[us](2), float64(4), int64(2), str(6)\n", "memory usage: 1.2 MB\n", "Memory before: 8.27 MB\n", "Memory after: 4.48 MB\n", "Reduction: 45.9%\n" ] } ], "source": [ "before = superstore.memory_usage(deep=True).sum() / 1024**2 # memory\n", "\n", "cleaner = DataCleaner(superstore)\n", "\n", "cleaner.convert_to_category([\"Region\", \"Segment\", \"Ship Mode\", \"Category\", \"Sub-Category\", \"Customer ID\", \"Country/Region\"])\n", "cleaner.clean_text_columns([\"City\", \"State\", \"Customer Name\", \"Product Name\"])\n", "\n", "outlier_report = cleaner.detect_outliers_iqr([\"Sales\", \"Profit\", \"Discount\", \"Quantity\"])\n", "print( \"\\n Outlier Report : \")\n", "display(outlier_report)\n", "\n", "superstore = cleaner.get_cleaned_data()\n", "superstore.info()\n", "\n", "after = superstore.memory_usage(deep=True).sum() / 1024**2 #memory\n", "\n", "print(f\"Memory before: {before:.2f} MB\")\n", "print(f\"Memory after: {after:.2f} MB\")\n", "print(f\"Reduction: {(before-after)/before*100:.1f}%\")" ] }, { "cell_type": "markdown", "id": "71723b82", "metadata": {}, "source": [ "**Memory Optimization:**\n", "\n", "Converting text columns (Region, Segment, Category, Sub-Category, Customer ID, Country/Region) to `category` dtype reduced the dataset's memory usage from **8.27 MB to 4.48 MB — a 45.9% reduction** — without any loss of data or functionality." ] }, { "cell_type": "code", "execution_count": 12, "id": "d7d86506", "metadata": {}, "outputs": [], "source": [ "class FeatureEngineer:\n", "\n", " def __init__(self, df):\n", " self.df = df.copy()\n", "\n", " def add_profit_margin(self):\n", " try:\n", " self.df[\"Profit Margin\"] = self.df[\"Profit\"] / self.df[\"Sales\"]\n", " except Exception as e:\n", " print(f\"Error calculating Profit Margin: {e}\")\n", " return self.df\n", "\n", " def add_shipping_duration(self):\n", " try:\n", " self.df[\"Shipping Duration\"] = (self.df[\"Ship Date\"] - self.df[\"Order Date\"]).dt.days\n", " except Exception as e:\n", " print(f\"Error calculating Shipping Duration: {e}\")\n", " return self.df\n", "\n", " def add_sales_performance_category(self):\n", " try:\n", " q25 = self.df[\"Sales\"].quantile(0.25)\n", " q75 = self.df[\"Sales\"].quantile(0.75)\n", "\n", " def categorize(sales):\n", " if sales >= q75:\n", " return \"High\"\n", " elif sales >= q25:\n", " return \"Medium\"\n", " else:\n", " return \"Low\"\n", "\n", " self.df[\"Sales Performance Category\"] = self.df[\"Sales\"].apply(categorize)\n", " except Exception as e:\n", " print(f\"Error creating Sales Performance Category: {e}\")\n", " return self.df\n", "\n", " def get_data(self):\n", " return self.df" ] }, { "cell_type": "code", "execution_count": 13, "id": "d1e517e3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SalesProfitProfit MarginOrder DateShip DateShipping DurationSales Performance Category
0261.960041.913616.002018-11-082018-11-113High
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" ], "text/plain": [ " Sales Profit Profit Margin Order Date Ship Date Shipping Duration \\\n", "0 261.9600 41.9136 16.00 2018-11-08 2018-11-11 3 \n", "1 731.9400 219.5820 30.00 2018-11-08 2018-11-11 3 \n", "2 14.6200 6.8714 47.00 2018-06-12 2018-06-16 4 \n", "3 957.5775 -383.0310 -40.00 2017-10-11 2017-10-18 7 \n", "4 22.3680 2.5164 11.25 2017-10-11 2017-10-18 7 \n", "\n", " Sales Performance Category \n", "0 High \n", "1 High \n", "2 Low \n", "3 High \n", "4 Medium " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fe = FeatureEngineer(superstore)\n", "fe.add_profit_margin()\n", "superstore = fe.get_data() \n", "superstore[\"Profit Margin\"] = superstore[\"Profit Margin\"] * 100\n", "fe.add_shipping_duration()\n", "fe.add_sales_performance_category()\n", "\n", "superstore = fe.get_data()\n", "superstore[[\"Sales\", \"Profit\", \"Profit Margin\", \"Order Date\", \"Ship Date\", \"Shipping Duration\", \"Sales Performance Category\"]].head()" ] }, { "cell_type": "markdown", "id": "218a1367", "metadata": {}, "source": [ "## EDA:" ] }, { "cell_type": "markdown", "id": "fe9796f7", "metadata": {}, "source": [ "correlation analysis" ] }, { "cell_type": "code", "execution_count": 14, "id": "21ca54e9", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SalesQuantityDiscountProfitProfit MarginShipping Duration
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Shipping Duration-0.0073500.0183150.000452-0.004658-0.0118001.000000
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" ], "text/plain": [ " Sales Quantity Discount Profit Profit Margin \\\n", "Sales 1.000000 0.200795 -0.028190 0.479064 0.003444 \n", "Quantity 0.200795 1.000000 0.008623 0.066253 -0.005280 \n", "Discount -0.028190 0.008623 1.000000 -0.219487 -0.864452 \n", "Profit 0.479064 0.066253 -0.219487 1.000000 0.223732 \n", "Profit Margin 0.003444 -0.005280 -0.864452 0.223732 1.000000 \n", "Shipping Duration -0.007350 0.018315 0.000452 -0.004658 -0.011800 \n", "\n", " Shipping Duration \n", "Sales -0.007350 \n", "Quantity 0.018315 \n", "Discount 0.000452 \n", "Profit -0.004658 \n", "Profit Margin -0.011800 \n", "Shipping Duration 1.000000 " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "numeric_cols = [\"Sales\", \"Quantity\", \"Discount\", \"Profit\", \"Profit Margin\", \"Shipping Duration\"]\n", "correlation_matrix = superstore[numeric_cols].corr()\n", "correlation_matrix" ] }, { "cell_type": "markdown", "id": "7e842d2f", "metadata": {}, "source": [ "- Discount & Profit Margin (-0.86): Strong inverse — discounting is the primary driver of margin erosion.\n", "- Sales & Profit (0.48): Moderate positive — sales volume contributes to profit, but isn't the sole driver.\n", "- Shipping Duration: No meaningful correlation with any variable — delivery time is not a performance factor here." ] }, { "cell_type": "markdown", "id": "409b76c5", "metadata": {}, "source": [ "-----" ] }, { "cell_type": "markdown", "id": "11cec2d9", "metadata": {}, "source": [ "Statistical Summary" ] }, { "cell_type": "code", "execution_count": 15, "id": "4dd29557", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SalesQuantityDiscountProfitProfit MarginShipping Duration
count9994.0000009994.0000009994.0000009994.0000009994.0000009994.000000
mean229.8580013.7895740.15620328.65689612.0313933.958075
std623.2451012.2251100.206452234.26010846.6754351.747937
min0.4440001.0000000.000000-6599.978000-275.0000000.000000
25%17.2800002.0000000.0000001.7287507.5000003.000000
50%54.4900003.0000000.2000008.66650027.0000004.000000
75%209.9400005.0000000.20000029.36400036.2500005.000000
max22638.48000014.0000000.8000008399.97600050.0000007.000000
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" ], "text/plain": [ " Sales Quantity Discount Profit Profit Margin \\\n", "count 9994.000000 9994.000000 9994.000000 9994.000000 9994.000000 \n", "mean 229.858001 3.789574 0.156203 28.656896 12.031393 \n", "std 623.245101 2.225110 0.206452 234.260108 46.675435 \n", "min 0.444000 1.000000 0.000000 -6599.978000 -275.000000 \n", "25% 17.280000 2.000000 0.000000 1.728750 7.500000 \n", "50% 54.490000 3.000000 0.200000 8.666500 27.000000 \n", "75% 209.940000 5.000000 0.200000 29.364000 36.250000 \n", "max 22638.480000 14.000000 0.800000 8399.976000 50.000000 \n", "\n", " Shipping Duration \n", "count 9994.000000 \n", "mean 3.958075 \n", "std 1.747937 \n", "min 0.000000 \n", "25% 3.000000 \n", "50% 4.000000 \n", "75% 5.000000 \n", "max 7.000000 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[numeric_cols].describe()" ] }, { "cell_type": "code", "execution_count": 16, "id": "c887b95a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Row IDOrder IDOrder DateShip DateShip ModeCustomer IDCustomer NameSegmentCountry/RegionCity...CategorySub-CategoryProduct NameSalesQuantityDiscountProfitProfit MarginShipping DurationSales Performance Category
261262US-2019-1552992019-06-082019-06-12Standard ClassDl-13600Dorris liebeCorporateUnited StatesPasadena...Office SuppliesAppliancesEureka Disposable Bags for Sanitaire Vibra Gro...1.62420.8-4.466-275.04Low
676677US-2019-1194382019-03-182019-03-23Standard ClassCD-11980Carol DarleyConsumerUnited StatesTyler...Office SuppliesAppliancesHoover Portapower Portable Vacuum2.68830.8-7.392-275.05Low
87668767CA-2017-1070832017-11-212017-11-27Standard ClassBB-11545Brenda BowmanCorporateUnited StatesFort Worth...Office SuppliesAppliancesKensington 6 Outlet SmartSocket Surge Protector24.58830.8-67.617-275.06Medium
91649165CA-2017-1640072017-06-082017-06-12Standard ClassMG-17695Maureen GnadeConsumerUnited StatesChicago...Office SuppliesAppliancesHoover Shoulder Vac Commercial Portable Vacuum143.12820.8-393.602-275.04Medium
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4 rows × 24 columns

\n", "
" ], "text/plain": [ " Row ID Order ID Order Date Ship Date Ship Mode \\\n", "261 262 US-2019-155299 2019-06-08 2019-06-12 Standard Class \n", "676 677 US-2019-119438 2019-03-18 2019-03-23 Standard Class \n", "8766 8767 CA-2017-107083 2017-11-21 2017-11-27 Standard Class \n", "9164 9165 CA-2017-164007 2017-06-08 2017-06-12 Standard Class \n", "\n", " Customer ID Customer Name Segment Country/Region City ... \\\n", "261 Dl-13600 Dorris liebe Corporate United States Pasadena ... \n", "676 CD-11980 Carol Darley Consumer United States Tyler ... \n", "8766 BB-11545 Brenda Bowman Corporate United States Fort Worth ... \n", "9164 MG-17695 Maureen Gnade Consumer United States Chicago ... \n", "\n", " Category Sub-Category \\\n", "261 Office Supplies Appliances \n", "676 Office Supplies Appliances \n", "8766 Office Supplies Appliances \n", "9164 Office Supplies Appliances \n", "\n", " Product Name Sales Quantity \\\n", "261 Eureka Disposable Bags for Sanitaire Vibra Gro... 1.624 2 \n", "676 Hoover Portapower Portable Vacuum 2.688 3 \n", "8766 Kensington 6 Outlet SmartSocket Surge Protector 24.588 3 \n", "9164 Hoover Shoulder Vac Commercial Portable Vacuum 143.128 2 \n", "\n", " Discount Profit Profit Margin Shipping Duration \\\n", "261 0.8 -4.466 -275.0 4 \n", "676 0.8 -7.392 -275.0 5 \n", "8766 0.8 -67.617 -275.0 6 \n", "9164 0.8 -393.602 -275.0 4 \n", "\n", " Sales Performance Category \n", "261 Low \n", "676 Low \n", "8766 Medium \n", "9164 Medium \n", "\n", "[4 rows x 24 columns]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[superstore[\"Profit Margin\"] == superstore[\"Profit Margin\"].min()]" ] }, { "cell_type": "code", "execution_count": 17, "id": "1c1438da", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sub-Category\n", "Binders 0.372292\n", "Machines 0.306087\n", "Tables 0.261285\n", "Bookcases 0.211140\n", "Chairs 0.170178\n", "Appliances 0.166524\n", "Copiers 0.161765\n", "Phones 0.154556\n", "Furnishings 0.138349\n", "Fasteners 0.082028\n", "Envelopes 0.080315\n", "Accessories 0.078452\n", "Supplies 0.076842\n", "Paper 0.074891\n", "Art 0.074874\n", "Storage 0.074704\n", "Labels 0.068681\n", "Name: Discount, dtype: float64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "discount_by_subcat = superstore.groupby(\"Sub-Category\")[\"Discount\"].mean().sort_values(ascending=False)\n", "discount_by_subcat" ] }, { "cell_type": "code", "execution_count": 18, "id": "8c5abedd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sub-Category\n", "Binders 613\n", "Appliances 67\n", "Machines 23\n", "Bookcases 15\n", "dtype: int64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "high_discount_by_subcat = superstore[superstore[\"Discount\"] >= 0.7].groupby(\"Sub-Category\").size().sort_values(ascending=False)\n", "high_discount_by_subcat" ] }, { "cell_type": "code", "execution_count": 19, "id": "fe857e60", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total Binders transactions: 1523\n", "High discount (≥70%) transactions: 613 (40.2%)\n", "Profit from normal-discount Binders: $68,732.26\n", "Profit/Loss from high-discount Binders: $-38,510.50\n" ] } ], "source": [ "total_binders = superstore[superstore[\"Sub-Category\"] == \"Binders\"].shape[0]\n", "high_discount_binders = superstore[(superstore[\"Sub-Category\"] == \"Binders\") & (superstore[\"Discount\"] >= 0.7)].shape[0]\n", "\n", "binders_normal_profit = superstore[(superstore[\"Sub-Category\"] == \"Binders\") & (superstore[\"Discount\"] < 0.7)][\"Profit\"].sum()\n", "binders_high_discount_profit = superstore[(superstore[\"Sub-Category\"] == \"Binders\") & (superstore[\"Discount\"] >= 0.7)][\"Profit\"].sum()\n", "\n", "print(f\"Total Binders transactions: {total_binders}\")\n", "print(f\"High discount (≥70%) transactions: {high_discount_binders} ({high_discount_binders/total_binders*100:.1f}%)\")\n", "print(f\"Profit from normal-discount Binders: ${binders_normal_profit:,.2f}\")\n", "print(f\"Profit/Loss from high-discount Binders: ${binders_high_discount_profit:,.2f}\")" ] }, { "cell_type": "code", "execution_count": 20, "id": "6bb0f028", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sub-Category\n", "Binders 1523\n", "Paper 1370\n", "Furnishings 957\n", "Phones 889\n", "Storage 846\n", "Art 796\n", "Accessories 775\n", "Chairs 617\n", "Appliances 466\n", "Labels 364\n", "Tables 319\n", "Envelopes 254\n", "Bookcases 228\n", "Fasteners 217\n", "Supplies 190\n", "Machines 115\n", "Copiers 68\n", "Name: count, dtype: int64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[\"Sub-Category\"].value_counts()" ] }, { "cell_type": "markdown", "id": "6ad8fe20", "metadata": {}, "source": [ "- Sales: Heavily right-skewed (mean $230 vs. median $54) — most orders are modest, with a few large ones pulling the average up.\n", "- Profit: Wide range (-$6,600 to $8,400) — some transactions generate significant losses.\n", "- Discount: 25% of orders have no discount at all; median discount is 20% when applied.\n", "- Profit Margin: Averages ~12%, but drops as low as -275% — driven by 80% discounts on Appliances, which guarantee losses regardless of sale volume.\n", "- Shipping Duration: Consistent and predictable (0–7 days, low variance) — not a source of operational risk.\n", "\n", "**Note** : \n", "\n", "Binders have by far the most high-discount transactions (613), nearly 9x more than Appliances (67). This shifts the primary concern from Appliances to Binders — while Appliances was the first pattern identified, Binders show a far more frequent occurrence of extreme discounting." ] }, { "cell_type": "markdown", "id": "3e98ec31", "metadata": {}, "source": [ "------------" ] }, { "cell_type": "markdown", "id": "df6c0d7d", "metadata": {}, "source": [ "Trend Analysis" ] }, { "cell_type": "code", "execution_count": 21, "id": "fc3855cd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Order MonthSales
2019-11118,447.82
2018-1296,999.04
2019-0987,866.65
2019-1283,829.32
2016-0981,777.35
2018-1179,411.97
2016-1178,628.72
2019-1077,776.92
2017-1175,972.56
2017-1274,919.52
2018-0973,410.02
2016-1269,545.62
2017-0964,595.92
2019-0863,120.89
2018-1059,687.74
2019-0358,872.35
2018-0556,987.73
2016-0355,691.01
2019-0652,981.73
2018-0351,715.88
2019-0745,264.42
2019-0544,261.11
2019-0143,971.37
2018-0640,344.53
2018-0739,261.96
2018-0438,750.04
2017-0338,726.25
2017-0836,898.33
2019-0436,521.54
2016-0634,595.13
2017-0434,195.21
2016-0733,946.39
2016-1031,453.39
2017-1031,404.92
2018-0831,115.37
2017-0530,131.69
2017-0728,765.33
2016-0428,295.35
2016-0827,909.47
2017-0624,797.29
2016-0523,648.29
2018-0222,978.82
2019-0220,301.13
2018-0118,542.49
2017-0118,174.08
2016-0114,236.90
2017-0211,951.41
2016-024,519.89
\n" ], "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "superstore[\"Order Month\"] = superstore[\"Order Date\"].dt.to_period(\"M\")\n", "monthly_sales = superstore.groupby(\"Order Month\")[\"Sales\"].sum() \n", "monthly_sales_display = (\n", " monthly_sales\n", " .sort_values(ascending=False)\n", " .reset_index()\n", " .style.format({\"Sales\": \"{:,.2f}\"})\n", " .hide(axis=\"index\")\n", ")\n", "monthly_sales_display" ] }, { "cell_type": "markdown", "id": "9c0f2195", "metadata": {}, "source": [ "----------------" ] }, { "cell_type": "markdown", "id": "2222c6cc", "metadata": {}, "source": [ "### Visualizations:" ] }, { "cell_type": "code", "execution_count": 22, "id": "e6f7e38a", "metadata": {}, "outputs": [], "source": [ "# Libraries:\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import numpy as np\n", "import plotly.express as px" ] }, { "cell_type": "markdown", "id": "eaea6aab", "metadata": {}, "source": [ "1. Correlation Heatmap:" ] }, { "cell_type": "code", "execution_count": 23, "id": "9a2e6ff2", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,6))\n", "sns.heatmap(correlation_matrix, annot=True, cmap=\"coolwarm\", fmt=\".2f\")\n", "plt.title(\"Correlation Heatmap\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "2924fa79", "metadata": {}, "source": [ "The heatmap visualizes the correlations above — the dark blue cell (Discount vs. Profit Margin) stands out as the strongest relationship in the dataset." ] }, { "cell_type": "markdown", "id": "e205ba6f", "metadata": {}, "source": [ "2. Monthly Sales Trend:" ] }, { "cell_type": "code", "execution_count": 24, "id": "f5bfb8df", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12,5))\n", "monthly_sales.plot()\n", "plt.title(\"Monthly Sales Trend\")\n", "plt.ylabel(\"Sales\")\n", "plt.xlabel(\"Month\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "b804e22c", "metadata": {}, "source": [ "- Data covers Jan 2016 – Dec 2019.\n", "- Sales show a clear seasonal pattern, peaking every November/December (holiday season) across all four years, with a dip each January/February.\n", "- Overall sales trend upward year over year, with the highest peak in November 2019 (~$118K). " ] }, { "cell_type": "markdown", "id": "53b74aa4", "metadata": {}, "source": [ "3. Category Share of Profit, Quantity & Discount (%):" ] }, { "cell_type": "code", "execution_count": 25, "id": "ccf49b13", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "alignmentgroup": "True", "hovertemplate": "Metric=Total_Profit
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"standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "Category Share of Profit, Quantity & Discount (%)" }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "title": { "text": "Category" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "Share of Total (%)" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "summary = superstore.groupby(\"Category\").agg(\n", " Total_Profit=(\"Profit\", \"sum\"),\n", " Total_Quantity=(\"Quantity\", \"sum\"),\n", " Avg_Discount=(\"Discount\", \"mean\")\n", ")\n", "\n", "share = summary / summary.sum() * 100\n", "\n", "share_reset = share.reset_index().melt(id_vars=\"Category\", var_name=\"Metric\", value_name=\"Share\")\n", "\n", "fig = px.bar(share_reset, x=\"Category\", y=\"Share\", color=\"Metric\", barmode=\"group\",\n", " title=\"Category Share of Profit, Quantity & Discount (%)\",\n", " labels={\"Share\": \"Share of Total (%)\"})\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 26, "id": "ebf227ec", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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DiscountProfit Margin
Category
Furniture0.1739233.878353
Office Supplies0.15728513.803029
Technology0.13232315.613805
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" ], "text/plain": [ " Discount Profit Margin\n", "Category \n", "Furniture 0.173923 3.878353\n", "Office Supplies 0.157285 13.803029\n", "Technology 0.132323 15.613805" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "category_stats = superstore.groupby(\"Category\")[[\"Discount\", \"Profit Margin\"]].mean()\n", "category_stats" ] }, { "cell_type": "markdown", "id": "90d5fc6e", "metadata": {}, "source": [ "- Furniture holds the highest share of discounting (37%) but the lowest share of profit (6%) — a clear mismatch between discount investment and return. \n", "- Office Supplies drives the most volume (61%) with a moderate profit share (43%), showing efficiency at scale. \n", "- Technology takes the largest profit share (51%) from the smallest volume share (18%) and lowest discount share (28%) — the most profitable category per unit sold." ] }, { "cell_type": "markdown", "id": "415545b7", "metadata": {}, "source": [ "4. Sales Distribution (histogram):" ] }, { "cell_type": "code", "execution_count": 27, "id": "27d26cee", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,5))\n", "sns.histplot(superstore[\"Sales\"], bins=50, kde=True)\n", "plt.title(\"Sales Distribution\")\n", "plt.xlim(0, 2000) \n", "plt.show()" ] }, { "cell_type": "markdown", "id": "54d98721", "metadata": {}, "source": [ "- The vast majority of orders fall under $450, with a long tail of high-value orders extending beyond $2,000 (not shown here for readability, **max sales 22,638** ).\n", "- This right-skewed pattern confirms the earlier finding that mean sales ($230) exceed the median ($54)." ] }, { "cell_type": "markdown", "id": "df3f17d1", "metadata": {}, "source": [ "5. Discount vs Profit (scatter):" ] }, { "cell_type": "code", "execution_count": 28, "id": "ee645853", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,5))\n", "sns.scatterplot(data=superstore, x=\"Discount\", y=\"Profit\", alpha=0.4)\n", "plt.title(\"Discount vs Profit\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "508a45ad", "metadata": {}, "source": [ "- At 0% discount, profit ranges widely (up to $8,000+).\n", "- As discount increases beyond ~50%, the maximum achievable profit drops sharply, and losses become increasingly common and severe (down to -$6,600 at 70-80% discount).\n", "- Confirms the strong inverse correlation (-0.86) between Discount and Profit Margin at the individual transaction level." ] }, { "cell_type": "markdown", "id": "1952b9ee", "metadata": {}, "source": [ "6. Sales by Region:" ] }, { "cell_type": "code", "execution_count": 29, "id": "82234f8d", "metadata": {}, "outputs": [ { "data": { "image/png": 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ffvhB5cuX18yZMzV9+nRJsvlBILuvE69WrZp2796tr776SkuWLJFhGOrQoYNeeeUVm8+tRo0aSktLu6HfpUqVMn9zAsAxORn38lQMAAD3wcSJEzV48GBFRkaqa9eu9u7ODbp3764VK1bo7Nmz9u4KADtjzjQAwOFERkaqePHi6tixo137kZaWdsO3UJ4+fVqLFi3Sk08+aadeAXAkTPMAADiE9PR0rVixQuvWrdPGjRs1ZcqU2y65d7/Fx8erZcuW6t69ux555BEdO3ZM48aNU7FixTR69Gi79g2AY2CaBwDAISQkJOjZZ59VwYIF9fjjj9/x2tL325EjRzRz5kzt27dPTk5OatCggfr06aPChQvbu2sAHABhGgAAALCIOdMAAACARYRpAAAAwCIeQLSDrKwsnT59WoUKFbrtgv8AAADIfYZhKDExUSVLlrzlt7ASpu3g9OnTCgoKsnc3AAAAcBsxMTEKDAy86XbCtB0UKlRI0rW/HB8fHzv3BgAAAP+UkJCgoKAgM7fdDGHaDq5P7fDx8SFMAwAAOLDbTcnlAUQAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAi1zt3QEAAIDcUm/YLHt3Ablo60c97/s5GJkGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwyK7rTI8bN05paWk3tNeqVUuPP/64+T4pKUk//fSTzp07pxo1aqhVq1Y37ONoNQAAAHjw2XVkOj4+XpcvXzZfR44cUXh4uPbu3WvWnDp1SjVr1tTHH3+sPXv2qHv37urWrZsMw3DYGgAAAOQPdh2ZHj16tM37CRMmyM3NTT17/t+31QwfPlxFihTRxo0b5ebmpr1796pmzZp69tln1alTJ4esAQAAQP7gUHOmp0+fro4dO+qhhx6SJGVmZmrRokXq1auX3NzcJElVq1ZVSEiIFixY4JA1AAAAyD8cJkxv3rxZu3fvVt++fc22EydOKDk5WZUqVbKprVSpkvbt2+eQNdlJTU1VQkKCzQsAAAB5n8OE6enTp6tcuXI2D/MlJSVJknx9fW1qCxcubG5ztJrsREREyNfX13wFBQXdtBYAAAB5h0OE6StXrigyMlJ9+vSRk5OT2e7t7S1JN4zkxsfHm9scrSY74eHhio+PN18xMTE3rQUAAEDe4RBhev78+bpy5YpefPFFm/bSpUvLw8NDhw4dsmk/dOiQKlas6JA12XF3d5ePj4/NCwAAAHmfQ4Tp6dOnq127dipZsqRNu6urq9q3b685c+YoMzNTknTkyBGtXr3aXDnD0WoAAACQfzgZdl4g+a+//lKlSpX0888/q127djdsP3r0qJo0aaJKlSqpQYMGmj9/vqpWraqff/5Zzs7ODllzOwkJCfL19VV8fDyj1AAA5KJ6w2bZuwvIRVs/6nn7opu407xm9zC9bt06LV26VKNHj5aLi0u2NXFxcfruu+/Mbxzs1KnTDcHV0WpuhTANAIB9EKbzl3wRpvMjwjQAAPZBmM5fciNMO8ScaQAAACAvIkwDAAAAFhGmAQAAAIsI0wAAAIBFrvbuAAAAPBSWv9zLQ2GAo2FkGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWGT3MB0TE6OXXnpJZcuWVdWqVTVhwgRlZWXZ1Hz99deqVauWSpQooTZt2mj79u03HMfRagAAAPDgs2uYPn36tBo2bKikpCQtWbJES5Ys0alTp7R+/XqzZt68eerfv7+GDRum9evXq3z58mrZsqXOnDnjsDUAAADIH5wMwzDsdfLevXtr48aN2r17t1xdXbOtqVmzppo0aaKpU6dKkjIzM1WqVCm98sor+ve//+2QNbeTkJAgX19fxcfHy8fH564/NwB40NQbNsveXUAu2vpRT7udm3stf7mXe+1O85rdRqazsrK0aNEiPf/88zcN0pcvX9auXbvUqlUrs83FxUUtW7bUunXrHLIGAAAA+YfdwnRsbKzi4+NVpEgRtW/fXgEBAapXr54mTpxozpk+ffq0JKl48eI2+xYrVszc5mg12UlNTVVCQoLNCwAAAHmf3cJ0ZmamJOntt99Wz549tXXrVr3zzjsaMWKEPv74Y5taZ2fbbrq6uuqfs1McrebvIiIi5Ovra76CgoJuWgsAAIC8w25h2t/fXy4uLurWrZueffZZlSxZUk8//bReeuklzZkzR9K1EV9JunDhgs2+58+fN7c5Wk12wsPDFR8fb75iYmJuWgsAAIC8w25h2t3dXXXr1pW7u/sN7RkZGZKkokWL6uGHH9batWttatasWaOGDRs6ZM3NrtXHx8fmBQAAgLzPrkvjvfnmm/r222+1ZcsWSdL27dv1zTffqEuXLmbN4MGDNW3aNK1fv15paWmKiIjQ2bNn1a9fP4etAQAAQP6Q/TIauaRr1646f/682rdvr8uXL8vX11d9+vTRu+++a9YMGjRIFy5c0BNPPKHk5GSVLVtWixcv1iOPPOKwNQAAAMgf7LrO9N+lpKTIw8PjptsNw1BKSoo8PT3zTM3NsM40ANhi7d/8hXWmkVse6HWm/+lWQVqSnJycbhtcHa0GAAAADzaHCdMAAABAXkOYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIld7nnz9+vXat2+fTZufn586depk05aenq5Vq1bp3LlzqlGjhmrVqnXDsRytBgAAAA8+u45Mz549W2PHjtWmTZvMV3R0tE1NXFycgoOD1b9/f33//fdq3ry5Bg4c6NA1AAAAyB/sOjItSfXq1dO0adNuuj08PFzp6emKjo6Wt7e3tmzZooYNG6pdu3Z6/PHHHbIGAAAA+YPd50zHxsZq7ty5+uWXX3Tu3DmbbVlZWfruu+/00ksvydvbW5IUHBysRo0aad68eQ5ZAwAAgPzD7mH68OHDWrx4sd5//32VK1dOkydPNrfFxMQoISFBVatWtdmnWrVq2r17t0PWZCc1NVUJCQk2LwAAAOR9dp3m0atXL02aNEkFChSQJH311Vfq37+/GjVqpLp165qhs0iRIjb7+fn5mdscrSY7ERERGj169E23A46q3rBZ9u4CctHWj3rauwsAkOfYdWS6cePGZpCWpL59+8rPz0+///67JMnT01OSlJiYaLNfYmKiuc3RarITHh6u+Ph48xUTE3PTWgAAAOQddn8A8Z88PT118eJFSVLp0qVVoEABHTt2zKbm6NGjqlChgkPWZMfd3V3u7u63u3QAAADkMXYbmc7MzLxhhHbjxo2KiYlR48aNJUlubm5q27atIiMjZRiGJOnMmTOKiopShw4dHLIGAAAA+YeTcT0V5rKMjAzVrl1bTZo0UbVq1XTixAl9+eWXateunebOnStn52s5f+/evWrSpIlatmypRo0a6ZtvvlHhwoW1atUqc4qIo9XcTkJCgnx9fRUfHy8fH5+c/miBHMOc6fzFnnOmudfyF+415JZ7udfuNK/ZbWTa1dVVW7duVUhIiI4dOyZfX1/9+OOPioyMNIO0JFWtWlU7d+5U7dq1dfz4cQ0aNEgrV660Ca6OVgMAAID8wW4j0/kZI9PIKxjByV8YLURu4V5DbnmgR6YBAACAvI4wDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYlGNhOiMjI6cOBQAAAOQJlsL0oUOH9O6775rvR4wYIU9PT1WoUEF79+7Nsc4BAAAAjsxSmB46dKgaN24sSTp8+LAmTJigOXPmqHXr1ho2bFiOdhAAAABwVK5Wdlq7dq3mzZsnSfrtt9/05JNPqmvXrmrTpo0qVKiQox0EAAAAHJWlkekCBQrowoULkqSlS5eqZcuWkqSsrCy5uLjkXO8AAAAAB2YpTLdt21bdunXT66+/rpUrV6pDhw6SpFWrVpnB+m5NnTpVlStXVkRExA3bfvnlF7Vt21a1a9dWjx49dOTIEYevAQAAwIPPUpj+/PPP1bhxY508eVILFixQQECAJGnJkiV677337vp40dHRioiI0NWrV3Xu3Dmbbb/++qs6duyoNm3a6PPPP9fVq1fVrFkzXbp0yWFrAAAAkD84GYZh2LMDycnJql+/vj7++GO9/fbbCg0N1YQJE8ztDRo0UJUqVfTNN99IktLS0lSiRAkNGzZM4eHhDllzOwkJCfL19VV8fLx8fHzu5eMD7qt6w2bZuwvIRVs/6mm3c3Ov5S/ca8gt93Kv3Wles7zOdFZWlqKjo7Vo0SKzLTU19a6PM2DAALVs2VLt2rW7YVtSUpL+/PNPPfbYY2abm5ubWrduraioKIesAQAAQP5hKUyfOXNGjRs3Vt26ddWpUyezvVOnTvrtt9/u+DjffvutNm/erI8//jjb7SdPnpRhGOY0kutKlCihkydPOmRNdlJTU5WQkGDzAgAAQN5neZ3pihUrKj4+3qZ9+PDhev/99+/oGIcOHdLgwYP17bffytPTM9uazMxMSddGf//O3d3d/MZFR6vJTkREhHx9fc1XUFDQTWsBAACQd1haZ3rFihXas2ePChYsaNNeq1Ytbd68+Y6OsXTpUl25ckXPPfec2Xbs2DGdOHFCS5cu1Z49e+Tv7y9J5jJ81124cMHc5mg12QkPD9cbb7xhvk9ISCBQAwAAPAAsjUxfuXLFHJ11cnIy22NjY+Xh4XFHx3jhhRe0bds2LV682HyVK1dOHTp00OLFi+Xi4qISJUooMDBQmzZtstl348aNql+/viQ5XE123N3d5ePjY/MCAABA3mcpTIeEhGjGjBmS/i9Mp6WlacSIEQoNDb2jYxQuXFiVK1e2ebm7u6tIkSKqXLmyWdevXz9NmzZNBw8elCR9/fXXOnTokPr27euwNQAAAMgfLE3z+OijjxQaGqrffvtNhmGod+/eioqKUkJCgjZs2JCjHRw+fLhOnDih6tWry9fXVxkZGZo5c6Zq1qzpsDX3G8v65C/2XEIKAADcmuV1pmNiYvTZZ5/pzz//VFZWlurWravBgwerdOnSljtz7NgxeXl5qVixYjdsS0hIUFxcnAIDA1WgQIFs93e0mpu513WmCdP5C+uxIrdwryG3cK8ht+TGOtOWRqYlKSgoSB9++KHV3bNVtmzZm267k7nGjlYDAACAB9sdh+mUlJQ7PuidPoQIAAAA5GV3HKZvthZ0duz8DeUAAABArrjjML127dr72Q8AAAAgz7njMB0SEnI/+wEAAADkOZbWmQYAAABwD6t5/PTTT1qwYIFOnDihjIwMm23r1q27544BAAAAjs7SyPTkyZPVq1cv+fn5afXq1QoJCZGbm5vWr1+vSpUq5XQfAQAAAIdkKUxPnDhRCxYs0IQJEyRJH3zwgVauXKmxY8fq4sWLOdk/AAAAwGFZCtNHjhwxH0h0d3dXUlKSJKl///5auXJlzvUOAAAAcGCWwnR6errc3d0lSYGBgYqOjpYkxcbGysnJKed6BwAAADgwyw8gXte9e3d169ZN7dq107Jly9S+ffuc6BcAAADg8CyF6YMHD5p/HjVqlPz8/LRx40b16NFDw4YNy7HOAQAAAI7MUpiuUKGC+WdnZ2cNHjxYgwcPzrFOAQAAAHnBPU/zSEpK0owZM3Tp0iU98cQTql+/fk70CwAAAHB4d/UA4qZNm9S2bVvzfUZGhkJDQzV06FCNHz9eTZo0YTUPAAAA5Bt3FaY//PBDDRo0yHz/888/a9euXdq6dasuXbqkoUOH6oMPPsjxTgIAAACO6K7C9IYNG9SkSRPz/fLly9W6dWvVqlVLkjR48GDt3LkzZ3sIAAAAOKi7CtMpKSk260j/8ccfaty4sfm+cOHCSkxMzLneAQAAAA7srsJ0lSpVNHv2bEnSgQMHtG3bNrVq1crcfujQIVWsWDFnewgAAAA4qLsK0//617/0xhtvqGbNmmrQoIHq16+vRo0amdsXLlyoZ555Jsc7CQAAADiiu1oa7+mnn9ayZcv0448/ys/PTwMHDrSZ9uHs7KxXX301xzsJAAAAOKK7Xmc6LCxMYWFh2W5777337rU/AAAAQJ5xV9M8AAAAAPwfwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARa727kB6erp2796tpKQkVapUScWKFcu2bteuXTp37pyqVq2qkiVL5okaAAAAPNjsOjI9d+5cVa5cWa+++qqGDx+uMmXK6PXXX5dhGGZNUlKSWrVqpbCwMI0cOVLly5fXmDFjbI7jaDUAAADIH+w6Mm0YhjZv3ix/f39J0pYtW9SgQQM99thjeuKJJyRJI0eO1NGjR3XgwAH5+/tr2bJlevTRR9W8eXM1b97cIWsAAACQP9h1ZLp79+5mkJakGjVqyNXVVRcvXpR0LWzPnj1bffr0MevatGmjunXratasWQ5ZAwAAgPzD7nOmY2Nj9ccffyghIUEzZ85U8+bN1blzZ0nSqVOnFBcXp1q1atnsU7t2bUVHRztkTXZSU1OVmppqvk9ISLj1hwIAAIA8we5hOiYmRlOnTtWFCxd0+PBhvf322/L09JQkXb58WZLk5+dns4+/v7+5zdFqshMREaHRo0ffdDsAAADyJruH6bp16+rnn3+WJG3btk0hISEqXLiwXnzxRbm5uUmSrly5YrPPlStXzG2OVpOd8PBwvfHGG+b7hIQEBQUF3bQeAAAAeYNDrTNdt25dBQcHa+XKlZKk0qVLy8XFRSdPnrSpi4mJUbly5RyyJjvu7u7y8fGxeQEAACDvs1uYzszMVHx8vE3b1atXdejQIXPdZg8PD7Vo0UI//PCDWXP58mWtWLFCjz32mEPWAAAAIP+w2zSP9PR0NWrUSF27dlXVqlV1+fJlff3113J2dtagQYPMuoiICDVv3lz9+/dX48aNNXXqVJUtW1Yvv/yyw9YAAAAgf7DbyLSHh4c2bNggLy8vLVq0SJs3b1aPHj20f/9+lSpVyqxr0KCBNm/eLCcnJ/3vf//To48+qnXr1pkPKTpiDQAAAPIHJ+PvXzeIXJGQkCBfX1/Fx8dbmj9dbxhrWucnWz/qabdzc6/lL9xryC3ca8gt93Kv3Wlec6gHEAEAAIC8hDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIruG6UuXLunDDz/UU089pc6dO2v8+PFKSUm5oW7Dhg3q3r27WrduraFDh+rcuXMOXwMAAIAHn93CdGZmpurUqaPLly/r5Zdf1jPPPKMvv/xSbdu2VUZGhlm3Zs0ahYaGKigoSIMGDdLu3bvVtGlTJSUlOWwNAAAA8gcnwzAMe508MTFRhQoVMt/v2LFDderU0YYNG9S4cWNJUrNmzRQQEKD58+dLkpKTkxUQEKD33ntPb7zxhkPW3E5CQoJ8fX0VHx8vHx+fu/7c6g2bddf7IO/a+lFPu52bey1/4V5DbuFeQ265l3vtTvOaXad5/D1IS5Kvr68kmVM9rly5og0bNujJJ580a7y9vdW6dWstW7bMIWsAAACQfzjUA4gREREqXry4GjZsKEmKiYlRVlaWSpUqZVNXqlQpnThxwiFrspOamqqEhASbFwAAAPI+hwnTkydP1syZMzV79mx5eXlJktLT0yVJHh4eNrWenp5KS0tzyJrsREREyNfX13wFBQXdtBYAAAB5h0OE6enTp2vo0KGaN2+e2rRpY7b7+flJkuLi4mzq4+LizG2OVpOd8PBwxcfHm6+YmJib1gIAACDvsHuYnjFjhl577TXNmTNHnTt3ttlWsmRJFS9eXFu3brVp37x5s+rUqeOQNdlxd3eXj4+PzQsAAAB5n13D9KxZs/Tqq69qzpw5euaZZ7Kt6d27t6ZNm6YzZ85IkhYvXqzdu3erd+/eDlsDAACA/MHVXie+fPmyevfurcKFC+vTTz/Vp59+am4bPny42rdvL0kaNWqUDhw4oAoVKqhMmTI6duyYPv30U/MhRUesAQAAQP5gtzBdsGBBrV69OtttjzzyiPlnDw8P/fDDDzpx4oTOnTunihUrmkvoOWoNAAAA8ge7hWlXV1eFhITccX3p0qVVunTpPFUDAACAB5vdH0AEAAAA8irCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFjlEmD5//rw2bdqkhISEm9acPn1aO3bsUFJSUp6pAQAAwIPNrmF6+/bt6tatm6pVq6bGjRtr27ZtN9Skpqaqa9euKl++vJ555hkVL15cU6ZMcegaAAAA5A92D9NPPfWU/vjjj5vW/Oc//9G6det06NAhHTx4ULNmzdKAAQO0ZcsWh60BAABA/mDXMP3SSy/pueeek5ub201rpk+frj59+qhUqVKSpM6dO6tq1ar6+uuvHbYGAAAA+YNDzJm+mdOnT+vs2bMKDg62aW/YsKG2b9/ukDUAAADIP1zt3YFbuXjxoiTJz8/Ppt3f319xcXEOWZOd1NRUpaammu9v9aAlAAAA8g6HHpkuUKCAJNkEUUm6evWquc3RarITEREhX19f8xUUFHTTWgAAAOQdDh2mg4KC5OzsrNOnT9u0nz59WmXKlHHImuyEh4crPj7efMXExNzpRwAAAAAH5tBh2svLS40aNdJPP/1ktl25ckXLly9Xq1atHLImO+7u7vLx8bF5AQAAIO+z65zp2NhYHT58WLGxsZKkvXv3ysPDQ4GBgQoMDJQkjRkzRo8++qhGjhypxo0ba+LEifLz89Mrr7xiHsfRagAAAJA/2HVkevPmzRoyZIjGjh2rhg0batasWRoyZIiWLl1q1oSFhWnFihU6cOCAPvzwQ1WoUEHr16+3Gd11tBoAAADkD3YdmW7Xrp3atWt327rmzZurefPmeaoGAAAADz6HnjMNAAAAODLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAItc7d2BvGj//v366quvdO7cOdWoUUMDBgxQwYIF7d0tAAAA5DJGpu/Stm3bVK9ePV28eFHNmjXTwoUL1axZM6Wmptq7awAAAMhlhOm7FB4ertDQUM2YMUP9+vXT0qVLdeDAAc2YMcPeXQMAAEAuI0zfhdTUVK1cuVJdunQx2/z9/dWqVSv9+uuvduwZAAAA7IE503fhxIkTysjIUOnSpW3aS5curdWrV990v9TUVJtpIPHx8ZKkhIQES/3ITL1qaT/kTVbvk5zAvZa/cK8ht3CvIbfcy712fV/DMG5ZR5i+C9cDsZeXl017wYIFlZKSctP9IiIiNHr06Bvag4KCcraDeCD5TnrV3l1APsG9htzCvYbckhP3WmJionx9fW+6nTB9F65/kJcuXbJpj4uLU+HChW+6X3h4uN544w3zfVZWli5evCh/f385OTndl74+aBISEhQUFKSYmBj5+PjYuzt4gHGvIbdwryG3cK9ZYxiGEhMTVbJkyVvWEabvQmBgoIoUKaKdO3fqiSeeMNt37typmjVr3nQ/d3d3ubu727TdKnzj5nx8fPiHALmCew25hXsNuYV77e7dakT6Oh5AvAtOTk7q3r27pk+frsuXL0uSVq9erS1btuiFF16wb+cAAACQ6xiZvktjx47Vtm3bVKVKFVWpUkV//PGHRowYoZYtW9q7awAAAMhlhOm75OPjo3Xr1mnLli06d+6cqlevrnLlytm7Ww88d3d3jRo16obpMkBO415DbuFeQ27hXru/nIzbrfcBAAAAIFvMmQYAAAAsIkwDAAAAFhGm8cBKTU3VunXrbvmFOkBuO3LkiPbt22fvbgAAcghhGvddamqq9u/fr7179yo9Pf2+nCM9PV3r1q3TlStXzLYzZ86oWbNmOnny5H05J+wvLi5OW7du1aFDh5SRkXFfznH48GHt378/x443btw4hYeH59jx4BgiIyPVpUuXG169evXKsXN8+eWX+uSTT3LseMg7fv3112yX4O3du7feeustm7aEhAR16dJFmzdvvufzzp8/XyNHjrzn4zzoCNO4r6ZMmaKAgAC1b99ezz33nAICAjR8+HDzq9lzSlxcnJo1a6YjR47k6HHhmPbu3auWLVsqKChIffv2Vbt27VSsWDG99dZbOf6biI8++kjvvPNOjh4TD57du3dr/fr16tatm82rc+fOOXaObdu2aePGjTl2POQdfn5++vbbb7Vnzx6z7dChQ5o3b54mTpxoM5C0Zs0aff/99woMDLzn8+7du1dRUVH3fJwHHUvj4b7ZvHmzBgwYoAULFpj/oVy5ckWff/65EhMTbZboSU1N1Z49e+Tu7q4qVarI2fn/fs5LSkrSjh071LhxY7m4uEi69pXsGzZsUK1atVSoUCHzJ/Dt27fr8uXL8vX1VaFChcxjJCcn69ChQypZsqQeeuih3Lh83Cd//fWXmjRpoo4dO2rx4sXmt3lduXJFU6ZMUXx8vDw8PMz6Cxcu6NixYwoKClLx4sVtjnXw4EEZhqGKFSvq+PHjSkpKUqVKleTqeu2fxhMnTujs2bOKj4/XunXrJEk1atTQ+fPnZRiGKlSooP379+vq1auqV6+eYmJidPz4cUnXvjXrkUcesekLHmze3t7q0qXLTbd///33mjdvnqRr90fdunXVt29fubm5mTVJSUmaNm2aoqOj5e/vr65duyo4OFiRkZFatmyZUlNTzXOMGjVKNWrUuL8XBYdQv359FSpUSFFRUapWrZokKSoqSiEhITp9+rQ2bNig1q1bm+0VK1Y0vwL7woUL+vLLL7V3714FBASoa9euql+/vnns1NRUzZgxQ1u2bFGhQoXUsWNHhYaGaunSpZo/f77Onz9v3nODBw9Ws2bNcvnqHR9hGvfN5s2b5e7ubjMy4+XlpWHDhtnULViwQP369ZO/v7+SkpLk7e2thQsXqnbt2pKk/fv3q1mzZrp06ZL5NexXrlxRs2bNtHHjRgUHB2vs2LGSpPHjx8vLy0s1a9Y0f/X13//+Vz/99JOKFy+uffv26b333uPX7HlYeHi4/Pz89OWXX9qEEC8vL7355pvm+7S0NA0YMEDz589X+fLldfz4cTVt2lSzZ882vx527NixOnjwoFJSUpSamqq4uDj5+Pho+fLlCgoK0m+//aY//vhD6enpGj58uCRpwoQJ+uyzz3Tw4EElJycrIyND1atXV2RkpKKiovTll19Kki5evKiTJ09q0qRJOfqrfuRd1apVU7du3SRduz+mTZumBQsWaNWqVWbNk08+qdTUVL388stKSkrS0KFDFRERoRo1aqh8+fJKTEw0j/HPHw7x4HJ1dVWzZs0UFRWlgQMHSroWmkNDQ3Xq1ClFRUXZhOnrXyR37NgxNW3aVG3atFGbNm10/PhxtWnTRtOmTTP/b+7du7f27NmjAQMGKDMzU2PHjlVcXJxq166t6tWra9euXeY9V6ZMGTtcfR5gAPdJVFSUIcn4z3/+Y8TFxWVbc+rUKcPLy8v49NNPDcMwjIyMDOO5554zqlWrZmRkZBiGYRhbtmwxJBmXLl0y90tMTDQkGRs3bjQMwzDOnDljSDJ27dpl1hw9etSQZDz11FNGSkqKYRiG8cMPPxiurq7G6dOn78cl4z7LyMgwvLy8jOHDh9+29q233jIaN25sXLx40TAMw0hOTjZatmxp9O/f36zp1auX4erqaqxZs8YwDMNISUkxgoODjddee82s6devn9G5c2ebY/fq1ctwcnIyfv/991v2YenSpYanp6dx8uRJs23AgAHGU089ddv+I295++23DW9vb6Nz5842rzFjxtx0n4SEBMPb29tYv369YRiGcfXqVUOSsW3bNrMmMzPTvIezuxeRf3z00UeGv7+/kZWVZRiGYQQEBBhr16415s2bZzRu3NgwDMO4dOmS4ezsbHz33XeGYRjGM888Y7z88ss2x5k6dapRvnx5872vr6/x66+/2tRcuHDBMAzDGDVqlNG0adP7dk0PCkamcd+Ehobqk08+0ZgxY/Tuu++qYsWKCgsL02uvvWb+ajIyMlJ+fn7mT9ouLi6KiIhQ2bJltXnzZjVu3Pie+/HWW2+ZU0o6dOigrKws7du3TwEBAfd8bOSuuLg4Xbly5bbfOpqVlaUvvvhCw4YN04EDB2QYhgzDULNmzTRjxgyb2rCwMPPXlu7u7nrsscdsRgpvpkmTJmrTps0N7ZmZmTp27JjOnz8vb29vFSpUSH/88Yc6dep05xeKPKlQoULmCN51JUqUMP+clZWlRYsWadWqVTp//rwyMzPl5ORkTl3y8PBQlSpV9Pbbb2vYsGFq1KiRPD09VaRIkdy+FDigsLAwDRs2TLt27ZK7u7suX76sBg0aqHz58urZs6eSk5O1evVqGYahsLAwSdLSpUtVtWpVdevWzfx3MC4uTkeOHNGVK1fk5eWlunXr6v3335eTk5NCQkJUsGBB+fv72/lq8xbCNO6rN954Q4MHD9aff/6pTZs2afbs2apbt65WrlxpPjBYsWJFmznSZcqUkZeXlw4fPpwjYbpYsWLmn11dXVWgQAGbhzWQd3h6ekqS4uPjb1l37tw5xcfHa8GCBVqyZInNtn8G8b/fH9K16SJ3cn+ULl36hrZVq1bpxRdfVEpKioKCguTu7q7ExESdPXv2tsdD3ne7OdMDBw7Ur7/+qn79+qlRo0Zyd3fX+vXrlZSUZNZERUXpk08+0ZAhQ3To0CF16NBBkyZN4lkPqE6dOipcuLCioqLk7u6uJk2ayM3NTQEBASpbtqzWrVunqKgoVa9eXQ899JAyMzOVmJioJk2aqEmTJjbH6t+/v/lsyA8//KDx48dr5MiR2r17t1q3bq3PPvuMKR13gTCN+87FxUUNGzZUw4YN9dprr6ly5cqaNm2amjVrJh8fH5v/SKRry9ylpKSY81qdnJwkSYZhmDVpaWm5dwFwGIUKFdLDDz+s7du337LueugeNWqUnn766fvSl7//AHjdSy+9pF69eum9994z79sSJUooKyvrvvQBeUdWVpa++eYbLViwQE888YSka//W9ezZ06auePHi+u9//6v//ve/OnnypNq1a6dRo0Zp8uTJ5j2F/MnZ2VktWrQww3RoaKi5LTQ0VFFRUYqKijJHpV1cXFSyZEl5enre8oe8woULa/To0Ro9erRiY2P1zDPPaOjQofrhhx+45+4QS+PhvklISLihrUCBAvLy8lKBAgUkScHBwYqOjrYZufvtt9/k7OxsPoB4/dekMTExZs0/18+8Hp7u1zrWcByvvfaa5s+fr+jo6Bu2paamKi0tTYULF1atWrU0Z86cG2r++cPb7Xh6et7RfZWZmakTJ04oNDTU/A9o+/btOnfu3F2dDw8mZ2dnFShQQKdPnzbbIiIidPXqVfP9hQsXtHDhQvN9YGCgAgMDzd+UFC1aVLGxsbnXaTicsLAwrV69WqtWrbIJ0y1atNCiRYu0a9cu8+FDSXr55Zf1+eef2yypl5iYqG+//VbStf8zZ8yYYf7A/9BDD6l8+fLcc3eJkWncN//73/80fvx4vfDCC6pSpYrS09M1b948HTx4UNOmTZMkdezYUfXq1VO7du309ttvKz4+XsOHD9egQYMUFBQkSSpVqpQaNGigQYMGafjw4Tpz5ow++OADm3P5+voqKChIX331lbp166YiRYrYLI2HB8fQoUO1detWhYWFaejQoWrUqJGSk5O1e/duffPNN1qzZo0CAgI0adIktW3bVt27d1fXrl2VkpKiFStWKCMjQ9OnT7/j89WoUUNz587Vjz/+KD8/v5suRebi4qIWLVpoxIgRGjlypGJjYzVq1CibFUfwYDt79my2I4CzZs2Sl5eX/v3vf2vgwIGaP3++YmNjlZ6ebrMih6enp7777jv9v//3/1StWjWdPHlS8fHxWrp0qSTp6aef1rhx49SyZUv5+fmxNF4+FBYWpiFDhsjT01MNGjQw21u0aKG//vrLHL2+buTIkTp16pSCg4NVv359OTk56ciRI+bqRC4uLlq7dq3effddVa9eXXFxcTp+/Lh+/PFHSVK7du00YsQIhYSEqESJEiyNdxOEadw3PXr0UO3atTVr1iwtX75crq6uqlixonbs2KHKlStLujaFY+nSpRo3bpymTp0qd3d3/fvf/1bfvn1tjvXjjz9qzJgxmjBhgipUqKAffvhBr776qrnGsCQtXLhQn376qd59911VrVpV7777rpo2bWqOWl/XtGlT+fn53f8PAPeFs7Oz5s6dq6VLl+r777/X6tWr5evrqxo1amj16tXmg6XNmjXT9u3b9fnnn2vixIkqWrSo2rRpY7NMXcWKFZWZmWlz/KCgIPO3IpL0wgsv6NSpU5o6daoSEhI0YcKEbPeTrj1Q+/7772vcuHHy9/fXlClTNGfOHHO9V0kqX768zX2LB8Nzzz1nc9/83fXfxL3++utq37699u7dK39/fwUHB2vlypUqX768pGtzrhcsWKCYmBjt3r1bRYoUUf369c25rXXr1tXRo0e1Y8cOJSQksDRePlSjRg0tXLhQvr6+Nj+oBwYGavHixSpQoIC5hKx07d6bPn26Ro8erZ07d8rHx0e1a9dWwYIFJV379/Trr7/W2bNnFR0dLW9vbwUHB5sP7ZctW1bHjh3T1q1bFR8fzzzqm3Ay/j4RFQAAAMAdY840AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACLCNMAAACARYRpAECOO3LkiH766Sd7dwMA7ju+tAUA8om1a9fq1KlTkiQ3NzcFBQWpbt26cnFxyfFzTZs2TWPGjNGxY8dy/NgA4Ej4OnEAyCc+/PBDRUdHq2nTpkpLS9PmzZtVsGBBLVmyROXKlcvRc5UvX14dOnTI0WMCgCMiTANAPtKwYUNFRkZKkq5evapatWpp+PDh+u6772zqjh07pujoaBUtWlR169aVp6enzfasrCxt2LBBiYmJqlWrljIyMrR9+3Y99dRTkqQyZcro0UcfveH80dHROnz4sEqWLKkGDRrI2fn/Zhv+9ddfOnLkiFq3bq2dO3fqzJkzqlOnjkqWLJnTHwMA5BjCNADkU56engoNDdWaNWvMNsMwNGjQIM2bN0+NGjVSbGyszp07p0WLFqlu3bqSroXwtm3bav/+/apfv7527dqlKlWqaOfOnWaYXrlypcaMGWOOTqenp6tLly5au3atGjZsqJ07d6pUqVJasmSJ/P39JUm//vqrPvroIwUGBsrLy0tZWVnasmWLFixYoHbt2uXypwMAd4YwDQD52OHDh1WsWDHz/dSpU/X777/r4MGD8vPzkySNHj1aPXv21O7duyVJn332mQ4fPqzdu3erWLFiunDhgurXr3/L80yePFkbN27Uzp07FRgYqISEBDVp0kQjR47U5MmTzbrTp09r8uTJZigfOnSo3n33XcI0AIdFmAaAfOTkyZOKjIxUWlqaVq9erQ0bNtisujFjxgzVqlVLK1eulGEYMgxDPj4+2rNnj2JjY/XQQw9p4cKF6tmzpxnCixYtqt69e2vKlCk3PW9kZKR69OihwMBASZKPj48GDRqk8PBwmzAdEBBgBmlJCg0N1VdffZXTHwMA5BjCNADkI6dOndLixYt19epVrV69Ws8884xatmxpbj927JgMw9DChQtt9uvatatSU1MlSTExMSpbtqzN9n++/6fjx4/rhRdesGkrX768Ll26pMTERBUqVEiSzNHw69zd3ZWSknI3lwgAuYowDQD5yN8fQDx+/Ljq1aunsWPHauTIkZKujRi3adNG77///k2P4efnp8uXL9u0Xbp06ZbnLVq0qC5evGjTdvHiRXl4eKhgwYIWrgQAHANf2gIA+VSZMmU0duxYvf/++4qJiZEkPfbYY5ozZ46Sk5Ntaq+vTy1JTZs21Y8//miz/Z/v/ykkJESLFi3S37/aYMGCBWrSpImcnJzu9VIAwG4YmQaAfOzll1/W+PHj9e6772rGjBkaPXq0oqKiFBwcrD59+sjDw0ObNm1STEyMoqKiJEnh4eGqXbu2OnXqpMcff1zLli3Trl275Op68/9SRo4cqTp16qhdu3bq2LGj1q9fr19++UVr167NrUsFgPuCkWkAyCeaN2+ukJAQmzZXV1dNmjRJaWlpSkhIkL+/v7Zs2aIhQ4Zoz5492rdvn9q2bavly5eb+5QtW1ZbtmxRuXLl9Oeff6p169YaOXKkOe9ZuvFLWwICArRjxw41bNhQ69atU4kSJbR9+3bVq1fPrKlUqZIef/xxm/4FBASoa9euOf1RAECO4evEAQB37eLFizYPC7Zv316FChXSvHnz7NgrAMh9TPMAANy1Vq1aqVOnTipRooSWLFmitWvXatWqVfbuFgDkOqZ5AADu2vW1qTdt2qS6detqz549qlOnjp17BQC5j2keAAAAgEWMTAMAAAAWEaYBAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFv1/POXqxzvc1PgAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "region_order = superstore.groupby(\"Region\")[\"Sales\"].sum().sort_values(ascending=True).index\n", "\n", "plt.figure(figsize=(8,5))\n", "sns.barplot(data=superstore, x=\"Region\", y=\"Sales\", estimator=sum, errorbar=None, order=region_order)\n", "plt.title(\"Total Sales by Region\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "cdab90fe", "metadata": {}, "source": [ "- West and East together account for the majority of sales, while South lags significantly behind (~$390K vs. West's ~$725K) — nearly half. Worth investigating whether this reflects fewer customers, lower demand, or an under-served market in the South region." ] }, { "cell_type": "markdown", "id": "3e86a28e", "metadata": {}, "source": [ "7. Top 10 Sub-Categories by Sales:" ] }, { "cell_type": "code", "execution_count": 30, "id": "4eafa3f5", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "top_subcat = superstore.groupby(\"Sub-Category\")[\"Sales\"].sum().sort_values(ascending=False).head(10)\n", "plt.figure(figsize=(10,5))\n", "top_subcat.plot(kind=\"barh\")\n", "plt.title(\"Top 10 Sub-Categories by Sales\")\n", "plt.gca().invert_yaxis()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "66c88675", "metadata": {}, "source": [ "- *Phones* and *Chairs* lead sales (~$330K each), followed by Storage, Tables, and Binders in the mid-range." ] }, { "cell_type": "markdown", "id": "a84ba774", "metadata": {}, "source": [ "8. Sales Performance Category count:" ] }, { "cell_type": "code", "execution_count": 31, "id": "3759a431", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(6,5))\n", "sns.countplot(data=superstore, x=\"Sales Performance Category\", order=[\"Low\",\"Medium\",\"High\"])\n", "plt.title(\"Sales Performance Category Distribution\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "017f345e", "metadata": {}, "source": [ "- The Medium category contains the largest share of transactions (~5,000), while Low and High each contain roughly half that amount (~2,500 each), resulting in a balanced, symmetric distribution across the three categories." ] }, { "cell_type": "markdown", "id": "54258d79", "metadata": {}, "source": [ "------------------" ] }, { "cell_type": "markdown", "id": "1a62768b", "metadata": {}, "source": [ "## KPI Report:" ] }, { "cell_type": "code", "execution_count": 32, "id": "e52f9a2e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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KPIValue
0Total Sales2,297,200.86
1Total Profit286,397.02
2Average Discount0.156
3Average Profit Margin12.031
4Best Category (Profit)Technology
5Best Region (Sales)West
6Avg Shipping Duration (days)4.0
7Total Orders5,009
\n", "
" ], "text/plain": [ " KPI Value\n", "0 Total Sales 2,297,200.86\n", "1 Total Profit 286,397.02\n", "2 Average Discount 0.156\n", "3 Average Profit Margin 12.031\n", "4 Best Category (Profit) Technology\n", "5 Best Region (Sales) West\n", "6 Avg Shipping Duration (days) 4.0\n", "7 Total Orders 5,009" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "class KPI_Report:\n", " def __init__(self, df):\n", " self.df = df\n", "\n", " def generate_summary(self):\n", " try:\n", " summary = {\n", " \"Total Sales\": round(self.df[\"Sales\"].sum(), 2),\n", " \"Total Profit\": round(self.df[\"Profit\"].sum(), 2),\n", " \"Average Discount\": round(self.df[\"Discount\"].mean(), 3),\n", " \"Average Profit Margin\": round(self.df[\"Profit Margin\"].mean(), 3),\n", " \"Best Category (Profit)\": self.df.groupby(\"Category\")[\"Profit\"].sum().idxmax(),\n", " \"Best Region (Sales)\": self.df.groupby(\"Region\")[\"Sales\"].sum().idxmax(),\n", " \"Avg Shipping Duration (days)\": round(self.df[\"Shipping Duration\"].mean(), 1),\n", " \"Total Orders\": self.df[\"Order ID\"].nunique()\n", " }\n", " return summary\n", " except Exception as e:\n", " print(f\"Error generating summary: {e}\")\n", " return {}\n", "\n", "report = KPI_Report(superstore)\n", "kpi_summary = report.generate_summary()\n", "\n", "def format_value(val):\n", " if isinstance(val, (int, float, np.integer, np.floating)) and abs(val) >= 1000:\n", " return f\"{val:,}\"\n", " return val\n", "\n", "kpi_df = pd.DataFrame(list(kpi_summary.items()), columns=[\"KPI\", \"Value\"])\n", "kpi_df[\"Value\"] = kpi_df[\"Value\"].apply(format_value)\n", "kpi_df" ] }, { "cell_type": "markdown", "id": "536fc78b", "metadata": {}, "source": [ "## Summary:" ] }, { "cell_type": "markdown", "id": "1f1053a7", "metadata": {}, "source": [ "This analysis of the Superstore dataset (2016–2019, 9,994 transactions) showed four key findings with direct business implications:\n", "\n", "1. **Discounting negatively affects profitability** : Discount and Profit Margin show a strong inverse correlation (-0.86) — the single strongest relationship in the dataset.\n", "\n", "2. **Furniture is the weakest category** : Despite reasonable sales volume, Furniture carries the highest average discount (17.4%) and the lowest profit margin (3.9%) of all categories — its discount strategy needs review.\n", "\n", "3. **Binders shows the most severe discount-driven losses** : 40.2% of Binders transactions (613 of 1,523) carry a 70%+ discount, resulting in a net loss of $38,510 — against $68,732 earned from normally-discounted items. Despite this, Binders still ranks among the top sub-categories by total Sales, since high volume masks the profitability issue. This is the most significant discount-related risk identified in the dataset.\n", "\n", "4. **The South region underperforms** : Sales in the South (~$390K) trail West (~$725K) by nearly half, warranting further investigation into demand or market coverage.\n", "\n", "5. **Sales peak consistently at year-end** : Every year (2016–2019) shows a clear seasonal spike in November/December, with the highest peak in November 2019 (~$118K) — a predictable, recurring pattern." ] }, { "cell_type": "markdown", "id": "7b943992", "metadata": {}, "source": [ "\n", "## Recommendations:\n", "- Review discounts on Furniture and Binders, or review their pricing strategies.\n", "- Cap discounts on Binders specifically — 40.2% of its transactions lose money at 70%+ discount, the single largest source of discount-driven loss in the dataset ($38,510).\n", "- Investigate the South region's lower performance.\n", "- Continue leveraging Technology's high-margin, low-discount model as a benchmark for other categories.\n", "- Plan inventory and staffing ahead of the November/December sales peak, which recurs predictably every year." ] }, { "cell_type": "markdown", "id": "f1352fc8", "metadata": {}, "source": [ "## Saving Changes:" ] }, { "cell_type": "code", "execution_count": 33, "id": "36736a80", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "File exported successfully.\n" ] } ], "source": [ "superstore.to_csv(\"superstore_cleaned.csv\", index=False)\n", "print(\"File exported successfully.\")" ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.14.6" } }, "nbformat": 4, "nbformat_minor": 5 }