diff --git a/your-code/pandas_1.ipynb b/your-code/pandas_1.ipynb index 4f428ac..6706bab 100644 --- a/your-code/pandas_1.ipynb +++ b/your-code/pandas_1.ipynb @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -44,10 +44,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 5.7\n", + "1 75.2\n", + "2 74.4\n", + "3 84.0\n", + "4 66.5\n", + "5 66.3\n", + "6 55.8\n", + "7 75.7\n", + "8 29.1\n", + "9 43.7\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "x = pd.Series(lst)\n", + "print(x)" + ] }, { "cell_type": "markdown", @@ -60,10 +81,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "74.4\n" + ] + } + ], + "source": [ + "print(x[2])" + ] }, { "cell_type": "markdown", @@ -74,7 +105,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -92,10 +123,145 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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DescriptionQuantityUnitPriceRevenue
0LUNCH BAG APPLE DESIGN11.651.65
1SET OF 60 VINTAGE LEAF CAKE CASES240.5513.20
2RIBBON REEL STRIPES DESIGN11.651.65
3WORLD WAR 2 GLIDERS ASSTD DESIGNS28800.18518.40
4PLAYING CARDS JUBILEE UNION JACK21.252.50
5POPCORN HOLDER70.855.95
6BOX OF VINTAGE ALPHABET BLOCKS111.9511.95
7PARTY BUNTING44.9519.80
8JAZZ HEARTS ADDRESS BOOK100.191.90
9SET OF 4 SANTA PLACE SETTINGS481.2560.00
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" + ], + "text/plain": [ + " Description Quantity UnitPrice Revenue\n", + "0 LUNCH BAG APPLE DESIGN 1 1.65 1.65\n", + "1 SET OF 60 VINTAGE LEAF CAKE CASES 24 0.55 13.20\n", + "2 RIBBON REEL STRIPES DESIGN 1 1.65 1.65\n", + "3 WORLD WAR 2 GLIDERS ASSTD DESIGNS 2880 0.18 518.40\n", + "4 PLAYING CARDS JUBILEE UNION JACK 2 1.25 2.50\n", + "5 POPCORN HOLDER 7 0.85 5.95\n", + "6 BOX OF VINTAGE ALPHABET BLOCKS 1 11.95 11.95\n", + "7 PARTY BUNTING 4 4.95 19.80\n", + "8 JAZZ HEARTS ADDRESS BOOK 10 0.19 1.90\n", + "9 SET OF 4 SANTA PLACE SETTINGS 48 1.25 60.00" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame.from_dict(orders)\n", + "df" + ] }, { "cell_type": "markdown", @@ -238,10 +603,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Revenue: 637.0\n", + "Quantity: 2978\n" + ] + } + ], + "source": [ + "print(\"Revenue: \", df.Revenue.sum())\n", + "print(\"Quantity: \", df.Quantity.sum())" + ] }, { "cell_type": "markdown", @@ -252,10 +629,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Description Quantity UnitPrice Revenue\n", + "6 BOX OF VINTAGE ALPHABET BLOCKS 1 11.95 11.95\n", + "7 PARTY BUNTING 4 4.95 19.80\n", + "0 LUNCH BAG APPLE DESIGN 1 1.65 1.65\n", + "2 RIBBON REEL STRIPES DESIGN 1 1.65 1.65\n", + "4 PLAYING CARDS JUBILEE UNION JACK 2 1.25 2.50\n", + "9 SET OF 4 SANTA PLACE SETTINGS 48 1.25 60.00\n", + "5 POPCORN HOLDER 7 0.85 5.95\n", + "1 SET OF 60 VINTAGE LEAF CAKE CASES 24 0.55 13.20\n", + "8 JAZZ HEARTS ADDRESS BOOK 10 0.19 1.90\n", + "3 WORLD WAR 2 GLIDERS ASSTD DESIGNS 2880 0.18 518.40\n", + "\n", + "Diferrence: 11.77 \n" + ] + } + ], + "source": [ + "print(df.sort_values(by=\"UnitPrice\", ascending=False))\n", + "\n", + "difference = df[\"UnitPrice\"].max() - df[\"UnitPrice\"].min()\n", + "print(f\"\\nDiferrence: {difference} \")" + ] }, { "cell_type": "markdown", @@ -266,7 +668,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 83, "metadata": {}, "outputs": [], "source": [ @@ -285,10 +687,237 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 57, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Serial No. GRE Score TOEFL Score University Rating SOP LOR CGPA \\\n", + "0 1 337 118 4 4.5 4.5 9.65 \n", + "1 2 316 104 3 3.0 3.5 8.00 \n", + "2 3 322 110 3 3.5 2.5 8.67 \n", + "3 4 314 103 2 2.0 3.0 8.21 \n", + "4 5 330 115 5 4.5 3.0 9.34 \n", + "\n", + " Research Chance of Admit \n", + "0 1 0.92 \n", + "1 1 0.72 \n", + "2 1 0.80 \n", + "3 0 0.65 \n", + "4 1 0.90 \n" + ] + }, + { + "data": { + "text/html": [ + "
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Serial No.GRE ScoreTOEFL ScoreUniversity RatingSOPLORCGPAResearchChance of Admit
0133711844.54.59.6510.92
1231610433.03.58.0010.72
2332211033.52.58.6710.80
3431410322.03.08.2100.65
4533011554.53.09.3410.90
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Serial No.GRE ScoreTOEFL ScoreUniversity RatingSOPLORCGPAResearchChance of Admit
0FalseFalseFalseFalseFalseFalseFalseFalseFalse
1FalseFalseFalseFalseFalseFalseFalseFalseFalse
2FalseFalseFalseFalseFalseFalseFalseFalseFalse
3FalseFalseFalseFalseFalseFalseFalseFalseFalse
4FalseFalseFalseFalseFalseFalseFalseFalseFalse
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380FalseFalseFalseFalseFalseFalseFalseFalseFalse
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" + ], + "text/plain": [ + " Serial No. GRE Score TOEFL Score University Rating SOP LOR \\\n", + "0 False False False False False False \n", + "1 False False False False False False \n", + "2 False False False False False False \n", + "3 False False False False False False \n", + "4 False False False False False False \n", + ".. ... ... ... ... ... ... \n", + "380 False False False False False False \n", + "381 False False False False False False \n", + "382 False False False False False False \n", + "383 False False False False False False \n", + "384 False False False False False False \n", + "\n", + " CGPA Research Chance of Admit \n", + "0 False False False \n", + "1 False False False \n", + "2 False False False \n", + "3 False False False \n", + "4 False False False \n", + ".. ... ... ... \n", + "380 False False False \n", + "381 False False False \n", + "382 False False False \n", + "383 False False False \n", + "384 False False False \n", + "\n", + "[385 rows x 9 columns]" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#print(admissions.isnull())\n", + "admissions.isnull()" + ] }, { "cell_type": "markdown", @@ -313,17 +1150,231 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 91, "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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Serial No.GRE ScoreTOEFL ScoreUniversity RatingSOPLORCGPAResearchChance of Admit
Serial No.
1133711844.54.59.6510.92
2231610433.03.58.0010.72
3332211033.52.58.6710.80
4431410322.03.08.2100.65
5533011554.53.09.3410.90
..............................
38138132411033.53.59.0410.82
38238232510733.03.59.1110.84
38338333011645.04.59.4510.91
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38538533311745.04.09.6610.95
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385 rows × 9 columns

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" + ], + "text/plain": [ + " Serial No. GRE Score TOEFL Score University Rating SOP LOR \\\n", + "Serial No. \n", + "1 1 337 118 4 4.5 4.5 \n", + "2 2 316 104 3 3.0 3.5 \n", + "3 3 322 110 3 3.5 2.5 \n", + "4 4 314 103 2 2.0 3.0 \n", + "5 5 330 115 5 4.5 3.0 \n", + "... ... ... ... ... ... ... \n", + "381 381 324 110 3 3.5 3.5 \n", + "382 382 325 107 3 3.0 3.5 \n", + "383 383 330 116 4 5.0 4.5 \n", + "384 384 312 103 3 3.5 4.0 \n", + "385 385 333 117 4 5.0 4.0 \n", + "\n", + " CGPA Research Chance of Admit \n", + "Serial No. \n", + "1 9.65 1 0.92 \n", + "2 8.00 1 0.72 \n", + "3 8.67 1 0.80 \n", + "4 8.21 0 0.65 \n", + "5 9.34 1 0.90 \n", + "... ... ... ... \n", + "381 9.04 1 0.82 \n", + "382 9.11 1 0.84 \n", + "383 9.45 1 0.91 \n", + "384 8.78 0 0.67 \n", + "385 9.66 1 0.95 \n", + "\n", + "[385 rows x 9 columns]" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "admissions.set_index([\"Serial No.\"], inplace=False, drop=False)\n" + ] }, { "cell_type": "markdown", @@ -334,10 +1385,133 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 105, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "49\n", + "168\n" + ] + }, + { + "data": { + "text/html": [ + "
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GRE ScoreCGPA
03379.65
13168.00
23228.67
33148.21
43309.34
.........
3803249.04
3813259.11
3823309.45
3833128.78
3843339.66
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385 rows × 2 columns

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" + ], + "text/plain": [ + " GRE Score CGPA\n", + "0 337 9.65\n", + "1 316 8.00\n", + "2 322 8.67\n", + "3 314 8.21\n", + "4 330 9.34\n", + ".. ... ...\n", + "380 324 9.04\n", + "381 325 9.11\n", + "382 330 9.45\n", + "383 312 8.78\n", + "384 333 9.66\n", + "\n", + "[385 rows x 2 columns]" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(admissions[\"GRE Score\"].nunique())\n", + "print(admissions[\"CGPA\"].nunique())\n", + "subset = admissions[[\"GRE Score\", \"CGPA\"]]\n", + "subset \n", + "\n", + "# it's not possible " + ] }, { "cell_type": "markdown", @@ -348,10 +1522,217 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 93, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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Serial No.GRE ScoreTOEFL ScoreUniversity RatingSOPLORCGPAResearchChance of Admit
0133711844.54.59.6510.92
1231610433.03.58.0010.72
2332211033.52.58.6710.80
3431410322.03.08.2100.65
4533011554.53.09.3410.90
..............................
38038132411033.53.59.0410.82
38138232510733.03.59.1110.84
38238333011645.04.59.4510.91
38338431210333.54.08.7800.67
38438533311745.04.09.6610.95
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385 rows × 9 columns

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" + ], + "text/plain": [ + " Serial No. GRE Score TOEFL Score University Rating SOP LOR CGPA \\\n", + "0 1 337 118 4 4.5 4.5 9.65 \n", + "1 2 316 104 3 3.0 3.5 8.00 \n", + "2 3 322 110 3 3.5 2.5 8.67 \n", + "3 4 314 103 2 2.0 3.0 8.21 \n", + "4 5 330 115 5 4.5 3.0 9.34 \n", + ".. ... ... ... ... ... ... ... \n", + "380 381 324 110 3 3.5 3.5 9.04 \n", + "381 382 325 107 3 3.0 3.5 9.11 \n", + "382 383 330 116 4 5.0 4.5 9.45 \n", + "383 384 312 103 3 3.5 4.0 8.78 \n", + "384 385 333 117 4 5.0 4.0 9.66 \n", + "\n", + " Research Chance of Admit \n", + "0 1 0.92 \n", + "1 1 0.72 \n", + "2 1 0.80 \n", + "3 0 0.65 \n", + "4 1 0.90 \n", + ".. ... ... \n", + "380 1 0.82 \n", + "381 1 0.84 \n", + "382 1 0.91 \n", + "383 0 0.67 \n", + "384 1 0.95 \n", + "\n", + "[385 rows x 9 columns]" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "admissions[admissions[\"CGPA\"] > 9 & (admissions[\"Research\"] == 1)]" + ] }, { "cell_type": "markdown", @@ -362,17 +1743,220 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 94, "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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Serial No.GRE ScoreTOEFL ScoreUniversity RatingSOPLORCGPAResearchChance of Admit
0133711844.54.59.6510.92
1231610433.03.58.0010.72
2332211033.52.58.6710.80
3431410322.03.08.2100.65
4533011554.53.09.3410.90
..............................
38038132411033.53.59.0410.82
38138232510733.03.59.1110.84
38238333011645.04.59.4510.91
38338431210333.54.08.7800.67
38438533311745.04.09.6610.95
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385 rows × 9 columns

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" + ], + "text/plain": [ + " Serial No. GRE Score TOEFL Score University Rating SOP LOR CGPA \\\n", + "0 1 337 118 4 4.5 4.5 9.65 \n", + "1 2 316 104 3 3.0 3.5 8.00 \n", + "2 3 322 110 3 3.5 2.5 8.67 \n", + "3 4 314 103 2 2.0 3.0 8.21 \n", + "4 5 330 115 5 4.5 3.0 9.34 \n", + ".. ... ... ... ... ... ... ... \n", + "380 381 324 110 3 3.5 3.5 9.04 \n", + "381 382 325 107 3 3.0 3.5 9.11 \n", + "382 383 330 116 4 5.0 4.5 9.45 \n", + "383 384 312 103 3 3.5 4.0 8.78 \n", + "384 385 333 117 4 5.0 4.0 9.66 \n", + "\n", + " Research Chance of Admit \n", + "0 1 0.92 \n", + "1 1 0.72 \n", + "2 1 0.80 \n", + "3 0 0.65 \n", + "4 1 0.90 \n", + ".. ... ... \n", + "380 1 0.82 \n", + "381 1 0.84 \n", + "382 1 0.91 \n", + "383 0 0.67 \n", + "384 1 0.95 \n", + "\n", + "[385 rows x 9 columns]" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#a = (admissions.loc[(admissions[\"CGPA\"] > 9)]) & (admissions.loc[(admissions[\"SOP\"] < 3.5)])\n", + "#print(a)\n", + "\n", + "admissions[admissions[\"CGPA\"] > 9 & (admissions[\"SOP\"] < 3.5)]" + ] }, { "cell_type": "markdown", @@ -449,7 +2033,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.8" + "version": "3.12.0" }, "toc": { "base_numbering": "",