diff --git a/your-code/main.ipynb b/your-code/main.ipynb index f50ae3d..5c1a81b 100755 --- a/your-code/main.ipynb +++ b/your-code/main.ipynb @@ -18,11 +18,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "import numpy as np\n", + "import pandas as pd" ] }, { @@ -34,8 +36,10 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 7, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "lst = [5.7, 75.2, 74.4, 84.0, 66.5, 66.3, 55.8, 75.7, 29.1, 43.7]" @@ -43,11 +47,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "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" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "pandas_lst = pd.Series(lst)\n", + "pandas_lst" ] }, { @@ -61,11 +88,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "74.4" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "pandas_lst[2]" ] }, { @@ -77,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -95,11 +134,145 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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01234
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357.40.196.14.269.5
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" + ], + "text/plain": [ + " Score_1 Score_3 Score_5\n", + "0 53.1 67.5 78.4\n", + "1 61.3 30.8 87.6\n", + "2 20.6 44.2 91.8\n", + "3 57.4 96.1 69.5\n", + "4 83.6 85.4 35.9\n", + "5 49.0 0.1 89.1\n", + "6 23.3 95.0 26.9\n", + "7 27.6 53.8 68.5\n", + "8 96.6 53.4 50.1\n", + "9 73.7 43.2 34.7" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "pandas_df[['Score_1', 'Score_3', 'Score_5']]" ] }, { @@ -152,11 +571,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "56.95000000000001" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "\n", + "sum(pandas_df[\"Score_3\"])/len(pandas_df[\"Score_3\"])" ] }, { @@ -168,11 +600,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "88.8" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "pandas_df[\"Score_4\"].max()" ] }, { @@ -184,11 +628,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "40.75" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "pandas_df[\"Score_2\"].median()" ] }, { @@ -200,7 +656,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -221,11 +677,134 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "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": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "orders_df = pd.DataFrame(orders)\n", + "orders_df" ] }, { @@ -237,11 +816,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total qty ordered : 2978\n", + "Total Revenue generated : 1496348.9\n" + ] + } + ], "source": [ - "# your code here" + "# your code here\n", + "print(\"Total qty ordered : \", sum(orders_df[\"Quantity\"]))\n", + "print(\"Total Revenue generated : \", sum(orders_df[\"Revenue\"]*orders_df[\"Quantity\"]))" ] }, { @@ -253,12 +843,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "11.77" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "orders_df[\"UnitPrice\"].max() - orders_df[\"UnitPrice\"].min()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -277,7 +886,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.7.6" } }, "nbformat": 4,