From 7a8cf6f11dd176dcff1d6d3fff8c476f27d1e0e4 Mon Sep 17 00:00:00 2001 From: alofro Date: Sat, 2 Mar 2024 18:55:56 +0100 Subject: [PATCH] update solution files --- .../2.1.solutions_basicterms.ipynb | 1851 ++++++++++++++++- .../2.2.solutions_dataframe.ipynb | 15 +- .../2.3.solutions_datenrundreise.ipynb | 1121 +++++----- .../solutions.files/2.5.solutions_fe.ipynb | 540 ++--- .../2.6.solutions_selection.ipynb | 54 +- .../solutions.files/2.8.solutions_na.ipynb | 100 +- .../3.1.solutions_frequency.ipynb | 91 +- .../3.4.solutions_variance.ipynb | 18 +- .../Musterloesung_Projektaufgabe.ipynb | 971 ++++----- ...nscombe.ipynb => solutions_anscombe.ipynb} | 6 +- .../solutions.files/solutions_outlier.ipynb | 180 +- 11 files changed, 3416 insertions(+), 1531 deletions(-) rename content/descriptive_statistics/solutions.files/{3.8.solutions_anscombe.ipynb => solutions_anscombe.ipynb} (99%) diff --git a/content/basics/solutions.files/2.1.solutions_basicterms.ipynb b/content/basics/solutions.files/2.1.solutions_basicterms.ipynb index 29089666..c8c869b2 100644 --- a/content/basics/solutions.files/2.1.solutions_basicterms.ipynb +++ b/content/basics/solutions.files/2.1.solutions_basicterms.ipynb @@ -2,23 +2,353 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 56, "id": "7a77604b-97f1-4652-b929-8f66cd4a3b32", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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Patron Type CodePatron Type DefinitionTotal CheckoutsTotal RenewalsAge RangeHome Library CodeHome Library DefinitionCirculation Active MonthCirculation Active YearNotice Preference CodeNotice Preference DefinitionProvided Email AddressYear Patron RegisteredWithin San Francisco County
05Staff5315NaNb2BayviewMar2023.0zEmailTrue2003False
15Staff480378NaNe9ExcelsiorJun2023.0zEmailTrue2003False
25Staff703345 to 54 yearsn4Noe ValleyJan2023.0zEmailTrue2011False
35Staff39342140NaNo2Ocean ViewJul2023.0zEmailTrue2003False
45Staff11181035NaNo7OrtegaJul2023.0zEmailTrue2003False
.............................................
4362850Adult2635 to 44 yearsyjjBookmobileOct2022.0zEmailTrue2020NaN
4362862Teen3010 to 19 yearsyjjBookmobileNov2015.0zEmailTrue2011NaN
4362870Adult6060 to 64 yearsylwBookmobileMar2022.0zEmailTrue2022NaN
43628815Teacher Card4035 to 44 yearsylwBookmobileSep2020.0zEmailTrue2019NaN
43628955Retired Staff30910175 years and overylwBookmobileJul2023.0zEmailTrue2003NaN
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436290 rows × 14 columns

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" + ], + "text/plain": [ + " Patron Type Code Patron Type Definition Total Checkouts \\\n", + "0 5 Staff 53 \n", + "1 5 Staff 480 \n", + "2 5 Staff 70 \n", + "3 5 Staff 3934 \n", + "4 5 Staff 1118 \n", + "... ... ... ... \n", + "436285 0 Adult 2 \n", + "436286 2 Teen 3 \n", + "436287 0 Adult 6 \n", + "436288 15 Teacher Card 4 \n", + "436289 55 Retired Staff 309 \n", + "\n", + " Total Renewals Age Range Home Library Code \\\n", + "0 15 NaN b2 \n", + "1 378 NaN e9 \n", + "2 33 45 to 54 years n4 \n", + "3 2140 NaN o2 \n", + "4 1035 NaN o7 \n", + "... ... ... ... \n", + "436285 6 35 to 44 years yjj \n", + "436286 0 10 to 19 years yjj \n", + "436287 0 60 to 64 years ylw \n", + "436288 0 35 to 44 years ylw \n", + "436289 101 75 years and over ylw \n", + "\n", + " Home Library Definition Circulation Active Month \\\n", + "0 Bayview Mar \n", + "1 Excelsior Jun \n", + "2 Noe Valley Jan \n", + "3 Ocean View Jul \n", + "4 Ortega Jul \n", + "... ... ... \n", + "436285 Bookmobile Oct \n", + "436286 Bookmobile Nov \n", + "436287 Bookmobile Mar \n", + "436288 Bookmobile Sep \n", + "436289 Bookmobile Jul \n", + "\n", + " Circulation Active Year Notice Preference Code \\\n", + "0 2023.0 z \n", + "1 2023.0 z \n", + "2 2023.0 z \n", + "3 2023.0 z \n", + "4 2023.0 z \n", + "... ... ... \n", + "436285 2022.0 z \n", + "436286 2015.0 z \n", + "436287 2022.0 z \n", + "436288 2020.0 z \n", + "436289 2023.0 z \n", + "\n", + " Notice Preference Definition Provided Email Address \\\n", + "0 Email True \n", + "1 Email True \n", + "2 Email True \n", + "3 Email True \n", + "4 Email True \n", + "... ... ... \n", + "436285 Email True \n", + "436286 Email True \n", + "436287 Email True \n", + "436288 Email True \n", + "436289 Email True \n", + "\n", + " Year Patron Registered Within San Francisco County \n", + "0 2003 False \n", + "1 2003 False \n", + "2 2011 False \n", + "3 2003 False \n", + "4 2003 False \n", + "... ... ... \n", + "436285 2020 NaN \n", + "436286 2011 NaN \n", + "436287 2022 NaN \n", + "436288 2019 NaN \n", + "436289 2003 NaN \n", + "\n", + "[436290 rows x 14 columns]" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import pandas as pd\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")\n", + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + " )\n", "#eine erste Übersicht verschaffen:\n", "df" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "ca23bd32-ecfb-4ea4-aaae-01c08e37ebfc", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "14" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# 1. Wie viele Merkmale besitzt der Datensatz? Die Merkmale entsprechen den Spalten\n", "len(df.columns)" @@ -26,10 +356,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "11ad2e54-ad95-4f80-a533-d1700c3b6f0a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "436290" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# 2.Wie groß ist die Stichprobengröße des Datensatzes?\n", "len(df)" @@ -37,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "b664e067-47f6-4ac1-bd95-a2862d24adb6", "metadata": {}, "outputs": [], @@ -55,7 +396,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "ef440c74-68b2-44e3-a7b1-3c028da134a5", "metadata": {}, "outputs": [], @@ -75,17 +416,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "d5b4fc74-4468-4cb4-bcba-0f63e7cb7719", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2022 0.119583\n", + "2019 0.101515\n", + "2003 0.094052\n", + "2021 0.074799\n", + "2020 0.073369\n", + "2017 0.067203\n", + "2018 0.065603\n", + "2023 0.060249\n", + "2016 0.049781\n", + "2015 0.046201\n", + "2014 0.036593\n", + "2013 0.030553\n", + "2012 0.029066\n", + "2011 0.028348\n", + "2009 0.026109\n", + "2010 0.025779\n", + "2008 0.023154\n", + "2007 0.014862\n", + "2006 0.012042\n", + "2005 0.010910\n", + "2004 0.010229\n", + "Name: Year Patron Registered, dtype: float64" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df['Year Patron Registered'].value_counts(normalize=True)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "9ea4b26b-6139-4698-948a-13ce6ac985f4", "metadata": {}, "outputs": [], @@ -103,7 +476,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "1f293941-1899-45cb-842a-ea12ab9e4da9", "metadata": {}, "outputs": [], @@ -118,7 +491,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "c381957c-c4f7-4c94-85f0-81d29e802ebf", "metadata": {}, "outputs": [], @@ -131,7 +504,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "1f92e797-4613-402c-aed1-5336d4037d57", "metadata": {}, "outputs": [], @@ -141,7 +514,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "96bccd59-35b6-4ba0-b1d1-28e36cd65c33", "metadata": {}, "outputs": [], @@ -151,7 +524,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "d4e121f7-5d4c-4505-a205-a73b8c02347e", "metadata": {}, "outputs": [], @@ -163,7 +536,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "b142bd18-a0a3-488e-91f0-786c49ebc28c", "metadata": {}, "outputs": [], @@ -173,35 +546,1455 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "b14365da-88c7-4ca4-bad3-f9f96b371f1b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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Patron Type CodePatron Type DefinitionTotal CheckoutsTotal RenewalsAge RangeHome Library CodeHome Library DefinitionCirculation Active MonthCirculation Active YearNotice Preference CodeNotice Preference DefinitionProvided Email AddressYear Patron RegisteredWithin San Francisco County
451Juvenile000 to 9 yearsxMainNaNNaNzEmailTrue2021False
642Teen0010 to 19 yearsxMainNaNNaNzEmailTrue2021False
653Senior0075 years and overm2MarinaNaNNaNzEmailTrue2021False
7210Visitor0025 to 34 yearsxMainNaNNaNzEmailTrue2023False
861Juvenile000 to 9 yearsxMainNaNNaNzEmailTrue2023False
.............................................
4362622Teen0010 to 19 yearsxMainNaNNaNNaNNoneFalse2023NaN
4362682Teen0010 to 19 yearsxMainNaNNaNNaNNoneFalse2023NaN
4362730Adult0035 to 44 yearsxMainNaNNaNNaNNoneFalse2021NaN
4362752Teen0010 to 19 yearsxMainNaNNaNNaNNoneFalse2023NaN
4362800Adult0025 to 34 yearsxMainNaNNaNNaNNoneFalse2023NaN
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39513 rows × 14 columns

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Patron Type CodePatron Type DefinitionTotal CheckoutsTotal RenewalsAge RangeHome Library CodeHome Library DefinitionCirculation Active MonthCirculation Active YearNotice Preference CodeNotice Preference DefinitionProvided Email AddressYear Patron RegisteredWithin San Francisco County
314Welcome1120 to 24 yearsg4Glen ParkAug2022.0zEmailTrue2022False
3710Visitor3320 to 24 yearsp5PortolaAug2022.0zEmailTrue2022False
4110Visitor3320 to 24 yearsg6Golden Gate ValleyNov2022.0zEmailTrue2022False
560Adult5420 to 24 yearsxMainMay2022.0zEmailTrue2021False
5710Visitor6120 to 24 yearsxMainJul2023.0zEmailTrue2023False
.............................................
4362150Adult0020 to 24 yearsxMainNaNNaNzEmailTrue2023NaN
43624016Digital Access Card0020 to 24 yearsxMainJun2023.0NaNNoneFalse2023NaN
4362454Welcome0020 to 24 yearsxMainAug2021.0NaNNoneFalse2021NaN
4362670Adult0020 to 24 yearsxMainMay2023.0NaNNoneFalse2023NaN
43627416Digital Access Card0020 to 24 yearsxMainDec2021.0NaNNoneFalse2021NaN
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25381 rows × 14 columns

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Staff0.0020140.0003260.001847
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35 to 44 years0.1977660.0955850.187697
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Patron Type Definition
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\n", + "
" + ], + "text/plain": [ + "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", + "Patron Type Definition \n", + "Adult 0.001193 0.081323 0.939364 \n", + "At User Adult 0.000000 0.000045 0.000197 \n", + "At User Juvenile 0.000122 0.000045 0.000000 \n", + "At User Senior 0.000000 0.000000 0.000000 \n", + "At User Teen 0.000000 0.000120 0.000000 \n", + "At User Welcome 0.000000 0.000015 0.000039 \n", + "Business 0.000000 0.000000 0.000000 \n", + "Digital Access Card 0.000092 0.000897 0.010598 \n", + "Juvenile 0.997614 0.308853 0.000039 \n", + "Library By Mail 0.000000 0.000000 0.000118 \n", + "Retired Staff 0.000000 0.000000 0.000000 \n", + "Senior 0.000214 0.000000 0.000000 \n", + "Staff 0.000031 0.000000 0.000473 \n", + "Teacher Card 0.000153 0.000030 0.001891 \n", + "Teen 0.000031 0.606474 0.000079 \n", + "Visitor 0.000000 0.000090 0.001103 \n", + "Welcome 0.000551 0.002109 0.046097 \n", + "\n", + "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", + "Patron Type Definition \n", + "Adult 0.934153 0.944811 0.950661 \n", + "At User Adult 0.000086 0.000318 0.000600 \n", + "At User Juvenile 0.000000 0.000000 0.000000 \n", + "At User Senior 0.000000 0.000000 0.000000 \n", + "At User Teen 0.000000 0.000000 0.000000 \n", + "At User Welcome 0.000054 0.000037 0.000041 \n", + "Business 0.000000 0.000000 0.000000 \n", + "Digital Access Card 0.012874 0.014268 0.010555 \n", + "Juvenile 0.000011 0.000024 0.000000 \n", + "Library By Mail 0.000086 0.000110 0.000103 \n", + "Retired Staff 0.000011 0.000012 0.000021 \n", + "Senior 0.000000 0.000000 0.000021 \n", + "Staff 0.000788 0.001211 0.002463 \n", + "Teacher Card 0.008503 0.011136 0.013783 \n", + "Teen 0.000000 0.000012 0.000000 \n", + "Visitor 0.000475 0.000318 0.000331 \n", + "Welcome 0.042959 0.027741 0.021420 \n", + "\n", + "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", + "Patron Type Definition \n", + "Adult 0.952558 0.958253 0.013716 \n", + "At User Adult 0.001048 0.001359 0.000000 \n", + "At User Juvenile 0.000000 0.000000 0.000000 \n", + "At User Senior 0.000000 0.000000 0.001514 \n", + "At User Teen 0.000000 0.000000 0.000000 \n", + "At User Welcome 0.000000 0.000000 0.000000 \n", + "Business 0.000000 0.000000 0.000032 \n", + "Digital Access Card 0.008964 0.007024 0.004099 \n", + "Juvenile 0.000052 0.000000 0.000000 \n", + "Library By Mail 0.000315 0.000227 0.000820 \n", + "Retired Staff 0.000577 0.000736 0.002428 \n", + "Senior 0.000105 0.000906 0.957905 \n", + "Staff 0.002464 0.001190 0.000946 \n", + "Teacher Card 0.012739 0.009233 0.004730 \n", + "Teen 0.000000 0.000000 0.000000 \n", + "Visitor 0.000262 0.000397 0.000378 \n", + "Welcome 0.020916 0.020675 0.013433 \n", + "\n", + "Age Range 75 years and over All \n", + "Patron Type Definition \n", + "Adult 0.001036 0.630652 \n", + "At User Adult 0.000000 0.000264 \n", + "At User Juvenile 0.000000 0.000016 \n", + "At User Senior 0.001555 0.000179 \n", + "At User Teen 0.000000 0.000018 \n", + "At User Welcome 0.000052 0.000030 \n", + "Business 0.000000 0.000002 \n", + "Digital Access Card 0.002487 0.008439 \n", + "Juvenile 0.000000 0.122349 \n", + "Library By Mail 0.003057 0.000276 \n", + "Retired Staff 0.001866 0.000322 \n", + "Senior 0.980308 0.113285 \n", + "Staff 0.000207 0.000933 \n", + "Teacher Card 0.001347 0.006893 \n", + "Teen 0.000000 0.093140 \n", + "Visitor 0.000207 0.000340 \n", + "Welcome 0.007877 0.022863 " + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.crosstab(\n", + " df['Patron Type Definition'],\n", + " df['Age Range'],\n", + " margins=True,\n", + " normalize=1\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1997eb97-92f5-4571-b5e3-2cddb2f87c4d", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/content/basics/solutions.files/2.2.solutions_dataframe.ipynb b/content/basics/solutions.files/2.2.solutions_dataframe.ipynb index b766df78..b02e7329 100644 --- a/content/basics/solutions.files/2.2.solutions_dataframe.ipynb +++ b/content/basics/solutions.files/2.2.solutions_dataframe.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -26,11 +26,18 @@ "df = pd.DataFrame(data)\n", "print(df)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -44,9 +51,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/content/basics/solutions.files/2.3.solutions_datenrundreise.ipynb b/content/basics/solutions.files/2.3.solutions_datenrundreise.ipynb index 345ee4cf..b3784cf0 100644 --- a/content/basics/solutions.files/2.3.solutions_datenrundreise.ipynb +++ b/content/basics/solutions.files/2.3.solutions_datenrundreise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 64, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -26,6 +26,7 @@ " \n", " \n", " \n", + " Unnamed: 0\n", " Patron Type Code\n", " Patron Type Definition\n", " Total Checkouts\n", @@ -39,258 +40,257 @@ " Notice Preference Definition\n", " Provided Email Address\n", " Year Patron Registered\n", - " Outside of County\n", - " Supervisor District\n", + " Within San Francisco County\n", " \n", " \n", " \n", " \n", + " 0\n", + " 123022\n", + " 2\n", + " Teen\n", " 0\n", " 0\n", - " ADULT\n", - " 1092\n", - " 761\n", - " 60 to 64 years\n", - " M6\n", - " Mission\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", - " False\n", - " 2003\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Oct\n", + " 2022.0\n", + " z\n", + " Email\n", + " True\n", + " 2022\n", " False\n", - " 9.0\n", " \n", " \n", - " 1\n", + " 1\n", + " 125054\n", " 0\n", - " ADULT\n", + " Adult\n", " 0\n", " 0\n", - " 20 to 24 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2014\n", + " 2021\n", " False\n", - " 5.0\n", " \n", " \n", - " 2\n", + " 2\n", + " 87884\n", + " 0\n", + " Adult\n", + " 0\n", " 0\n", - " ADULT\n", - " 31\n", - " 22\n", " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " April\n", - " 2016\n", + " x\n", + " Main\n", + " None\n", + " NaN\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2010\n", + " 2023\n", " False\n", - " 4.0\n", " \n", " \n", - " 3\n", + " 3\n", + " 409236\n", " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 45 to 54 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", - " a\n", - " print\n", - " False\n", - " 2016\n", + " Adult\n", + " 19\n", + " 40\n", + " 20 to 24 years\n", + " p9\n", + " Presidio\n", + " Jul\n", + " 2023.0\n", + " z\n", + " Email\n", " True\n", - " NaN\n", + " 2021\n", + " False\n", " \n", " \n", - " 4\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 25 to 34 years\n", - " X\n", - " Main Library\n", - " None\n", - " None\n", + " 4\n", + " 47911\n", + " 3\n", + " Senior\n", + " 1079\n", + " 197\n", + " 75 years and over\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", + " 2003\n", " False\n", - " 3.0\n", " \n", " \n", - " 5\n", + " 5\n", + " 393489\n", " 0\n", - " ADULT\n", - " 126\n", - " 11\n", + " Adult\n", + " 10\n", + " 5\n", " 45 to 54 years\n", - " M2\n", - " Marina\n", - " January\n", - " 2016\n", - " z\n", - " email\n", - " True\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", + " None\n", + " None\n", + " False\n", " 2003\n", " False\n", - " 2.0\n", " \n", " \n", - " 6\n", - " 3\n", - " SENIOR\n", + " 6\n", + " 5884\n", " 0\n", + " Adult\n", " 0\n", - " 65 to 74 years\n", - " C2\n", - " Chinatown\n", - " None\n", - " None\n", + " 0\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Mar\n", + " 2020.0\n", " z\n", - " email\n", - " True\n", - " 2015\n", + " Email\n", " True\n", - " NaN\n", + " 2020\n", + " False\n", " \n", " \n", - " 7\n", - " 0\n", - " ADULT\n", - " 3002\n", - " 1689\n", - " 25 to 34 years\n", - " P5\n", - " Portola\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", + " 7\n", + " 329892\n", + " 2\n", + " Teen\n", + " 137\n", + " 0\n", + " 10 to 19 years\n", + " yb\n", + " Bookmobile\n", + " Feb\n", + " 2021.0\n", + " z\n", + " Email\n", " True\n", - " 2004\n", + " 2009\n", " False\n", - " 9.0\n", " \n", " \n", - " 8\n", + " 8\n", + " 49195\n", + " 1\n", + " Juvenile\n", " 0\n", - " ADULT\n", - " 4\n", " 0\n", - " 25 to 34 years\n", - " C2\n", - " Chinatown\n", - " July\n", - " 2014\n", - " p\n", - " phone\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Apr\n", + " 2020.0\n", + " z\n", + " Email\n", " True\n", - " 2014\n", + " 2017\n", " False\n", - " 5.0\n", " \n", " \n", - " 9\n", - " 0\n", - " ADULT\n", - " 20\n", - " 0\n", - " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " June\n", - " 2015\n", + " 9\n", + " 298115\n", + " 1\n", + " Juvenile\n", + " 6\n", + " 23\n", + " 0 to 9 years\n", + " m2\n", + " Marina\n", + " May\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2011\n", + " 2021\n", " False\n", - " 7.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 0 ADULT 1092 761 \n", - "1 0 ADULT 0 0 \n", - "2 0 ADULT 31 22 \n", - "3 0 ADULT 0 0 \n", - "4 0 ADULT 0 0 \n", - "5 0 ADULT 126 11 \n", - "6 3 SENIOR 0 0 \n", - "7 0 ADULT 3002 1689 \n", - "8 0 ADULT 4 0 \n", - "9 0 ADULT 20 0 \n", + " Unnamed: 0 Patron Type Code Patron Type Definition Total Checkouts \\\n", + "0 123022 2 Teen 0 \n", + "1 125054 0 Adult 0 \n", + "2 87884 0 Adult 0 \n", + "3 409236 0 Adult 19 \n", + "4 47911 3 Senior 1079 \n", + "5 393489 0 Adult 10 \n", + "6 5884 0 Adult 0 \n", + "7 329892 2 Teen 137 \n", + "8 49195 1 Juvenile 0 \n", + "9 298115 1 Juvenile 6 \n", "\n", - " Age Range Home Library Code Home Library Definition \\\n", - "0 60 to 64 years M6 Mission \n", - "1 20 to 24 years P1 Park \n", - "2 25 to 34 years S7 Sunset \n", - "3 45 to 54 years P1 Park \n", - "4 25 to 34 years X Main Library \n", - "5 45 to 54 years M2 Marina \n", - "6 65 to 74 years C2 Chinatown \n", - "7 25 to 34 years P5 Portola \n", - "8 25 to 34 years C2 Chinatown \n", - "9 25 to 34 years S7 Sunset \n", + " Total Renewals Age Range Home Library Code \\\n", + "0 0 10 to 19 years x \n", + "1 0 25 to 34 years x \n", + "2 0 25 to 34 years x \n", + "3 40 20 to 24 years p9 \n", + "4 197 75 years and over x \n", + "5 5 45 to 54 years x \n", + "6 0 25 to 34 years x \n", + "7 0 10 to 19 years yb \n", + "8 0 10 to 19 years x \n", + "9 23 0 to 9 years m2 \n", "\n", - " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 July 2016 p \n", - "1 None None z \n", - "2 April 2016 z \n", - "3 None None a \n", - "4 None None z \n", - "5 January 2016 z \n", - "6 None None z \n", - "7 July 2016 p \n", - "8 July 2014 p \n", - "9 June 2015 z \n", + " Home Library Definition Circulation Active Month Circulation Active Year \\\n", + "0 Main Oct 2022.0 \n", + "1 Main Jul 2023.0 \n", + "2 Main None NaN \n", + "3 Presidio Jul 2023.0 \n", + "4 Main Jul 2023.0 \n", + "5 Main Jul 2023.0 \n", + "6 Main Mar 2020.0 \n", + "7 Bookmobile Feb 2021.0 \n", + "8 Main Apr 2020.0 \n", + "9 Marina May 2023.0 \n", "\n", - " Notice Preference Definition Provided Email Address \\\n", - "0 phone False \n", - "1 email True \n", - "2 email True \n", - "3 print False \n", - "4 email True \n", - "5 email True \n", - "6 email True \n", - "7 phone True \n", - "8 phone True \n", - "9 email True \n", + " Notice Preference Code Notice Preference Definition Provided Email Address \\\n", + "0 z Email True \n", + "1 z Email True \n", + "2 z Email True \n", + "3 z Email True \n", + "4 z Email True \n", + "5 None None False \n", + "6 z Email True \n", + "7 z Email True \n", + "8 z Email True \n", + "9 z Email True \n", "\n", - " Year Patron Registered Outside of County Supervisor District \n", - "0 2003 False 9.0 \n", - "1 2014 False 5.0 \n", - "2 2010 False 4.0 \n", - "3 2016 True NaN \n", - "4 2015 False 3.0 \n", - "5 2003 False 2.0 \n", - "6 2015 True NaN \n", - "7 2004 False 9.0 \n", - "8 2014 False 5.0 \n", - "9 2011 False 7.0 " + " Year Patron Registered Within San Francisco County \n", + "0 2022 False \n", + "1 2021 False \n", + "2 2023 False \n", + "3 2021 False \n", + "4 2003 False \n", + "5 2003 False \n", + "6 2020 False \n", + "7 2009 False \n", + "8 2017 False \n", + "9 2021 False " ] }, - "execution_count": 64, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -298,7 +298,9 @@ "source": [ "import pandas as pd\n", "\n", - "df = pd.read_csv('../data/Library_Usage_Small.csv')\n", + "df = pd.read_csv('../data/Library_Usage_Small.csv',\n", + " low_memory=False\n", + " )\n", "df.to_json('../data/Library_Usage_Small.json')\n", "df = pd.read_json('../data/Library_Usage_Small.json')\n", "df" @@ -306,7 +308,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -330,6 +332,7 @@ " \n", " \n", " \n", + " Unnamed: 0\n", " Patron Type Code\n", " Patron Type Definition\n", " Total Checkouts\n", @@ -343,258 +346,257 @@ " Notice Preference Definition\n", " Provided Email Address\n", " Year Patron Registered\n", - " Outside of County\n", - " Supervisor District\n", + " Within San Francisco County\n", " \n", " \n", " \n", " \n", + " 0\n", + " 123022\n", + " 2\n", + " Teen\n", " 0\n", " 0\n", - " ADULT\n", - " 1092\n", - " 761\n", - " 60 to 64 years\n", - " M6\n", - " Mission\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", - " False\n", - " 2003\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Oct\n", + " 2022.0\n", + " z\n", + " Email\n", + " True\n", + " 2022\n", " False\n", - " 9.0\n", " \n", " \n", - " 1\n", + " 1\n", + " 125054\n", " 0\n", - " ADULT\n", + " Adult\n", " 0\n", " 0\n", - " 20 to 24 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2014\n", + " 2021\n", " False\n", - " 5.0\n", " \n", " \n", - " 2\n", + " 2\n", + " 87884\n", + " 0\n", + " Adult\n", + " 0\n", " 0\n", - " ADULT\n", - " 31\n", - " 22\n", " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " April\n", - " 2016\n", + " x\n", + " Main\n", + " None\n", + " NaN\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2010\n", + " 2023\n", " False\n", - " 4.0\n", " \n", " \n", - " 3\n", - " 0\n", - " ADULT\n", + " 3\n", + " 409236\n", " 0\n", - " 0\n", - " 45 to 54 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", - " a\n", - " print\n", - " False\n", - " 2016\n", + " Adult\n", + " 19\n", + " 40\n", + " 20 to 24 years\n", + " p9\n", + " Presidio\n", + " Jul\n", + " 2023.0\n", + " z\n", + " Email\n", " True\n", - " NaN\n", + " 2021\n", + " False\n", " \n", " \n", - " 4\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 25 to 34 years\n", - " X\n", - " Main Library\n", - " None\n", - " None\n", + " 4\n", + " 47911\n", + " 3\n", + " Senior\n", + " 1079\n", + " 197\n", + " 75 years and over\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", + " 2003\n", " False\n", - " 3.0\n", " \n", " \n", - " 5\n", + " 5\n", + " 393489\n", " 0\n", - " ADULT\n", - " 126\n", - " 11\n", + " Adult\n", + " 10\n", + " 5\n", " 45 to 54 years\n", - " M2\n", - " Marina\n", - " January\n", - " 2016\n", - " z\n", - " email\n", - " True\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", + " None\n", + " None\n", + " False\n", " 2003\n", " False\n", - " 2.0\n", " \n", " \n", - " 6\n", - " 3\n", - " SENIOR\n", + " 6\n", + " 5884\n", " 0\n", + " Adult\n", " 0\n", - " 65 to 74 years\n", - " C2\n", - " Chinatown\n", - " None\n", - " None\n", + " 0\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Mar\n", + " 2020.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", - " True\n", - " NaN\n", + " 2020\n", + " False\n", " \n", " \n", - " 7\n", - " 0\n", - " ADULT\n", - " 3002\n", - " 1689\n", - " 25 to 34 years\n", - " P5\n", - " Portola\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", + " 7\n", + " 329892\n", + " 2\n", + " Teen\n", + " 137\n", + " 0\n", + " 10 to 19 years\n", + " yb\n", + " Bookmobile\n", + " Feb\n", + " 2021.0\n", + " z\n", + " Email\n", " True\n", - " 2004\n", + " 2009\n", " False\n", - " 9.0\n", " \n", " \n", - " 8\n", + " 8\n", + " 49195\n", + " 1\n", + " Juvenile\n", " 0\n", - " ADULT\n", - " 4\n", " 0\n", - " 25 to 34 years\n", - " C2\n", - " Chinatown\n", - " July\n", - " 2014\n", - " p\n", - " phone\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Apr\n", + " 2020.0\n", + " z\n", + " Email\n", " True\n", - " 2014\n", + " 2017\n", " False\n", - " 5.0\n", " \n", " \n", - " 9\n", - " 0\n", - " ADULT\n", - " 20\n", - " 0\n", - " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " June\n", - " 2015\n", + " 9\n", + " 298115\n", + " 1\n", + " Juvenile\n", + " 6\n", + " 23\n", + " 0 to 9 years\n", + " m2\n", + " Marina\n", + " May\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2011\n", + " 2021\n", " False\n", - " 7.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 0 ADULT 1092 761 \n", - "1 0 ADULT 0 0 \n", - "2 0 ADULT 31 22 \n", - "3 0 ADULT 0 0 \n", - "4 0 ADULT 0 0 \n", - "5 0 ADULT 126 11 \n", - "6 3 SENIOR 0 0 \n", - "7 0 ADULT 3002 1689 \n", - "8 0 ADULT 4 0 \n", - "9 0 ADULT 20 0 \n", + " Unnamed: 0 Patron Type Code Patron Type Definition Total Checkouts \\\n", + "0 123022 2 Teen 0 \n", + "1 125054 0 Adult 0 \n", + "2 87884 0 Adult 0 \n", + "3 409236 0 Adult 19 \n", + "4 47911 3 Senior 1079 \n", + "5 393489 0 Adult 10 \n", + "6 5884 0 Adult 0 \n", + "7 329892 2 Teen 137 \n", + "8 49195 1 Juvenile 0 \n", + "9 298115 1 Juvenile 6 \n", "\n", - " Age Range Home Library Code Home Library Definition \\\n", - "0 60 to 64 years M6 Mission \n", - "1 20 to 24 years P1 Park \n", - "2 25 to 34 years S7 Sunset \n", - "3 45 to 54 years P1 Park \n", - "4 25 to 34 years X Main Library \n", - "5 45 to 54 years M2 Marina \n", - "6 65 to 74 years C2 Chinatown \n", - "7 25 to 34 years P5 Portola \n", - "8 25 to 34 years C2 Chinatown \n", - "9 25 to 34 years S7 Sunset \n", + " Total Renewals Age Range Home Library Code \\\n", + "0 0 10 to 19 years x \n", + "1 0 25 to 34 years x \n", + "2 0 25 to 34 years x \n", + "3 40 20 to 24 years p9 \n", + "4 197 75 years and over x \n", + "5 5 45 to 54 years x \n", + "6 0 25 to 34 years x \n", + "7 0 10 to 19 years yb \n", + "8 0 10 to 19 years x \n", + "9 23 0 to 9 years m2 \n", "\n", - " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 July 2016 p \n", - "1 None None z \n", - "2 April 2016 z \n", - "3 None None a \n", - "4 None None z \n", - "5 January 2016 z \n", - "6 None None z \n", - "7 July 2016 p \n", - "8 July 2014 p \n", - "9 June 2015 z \n", + " Home Library Definition Circulation Active Month Circulation Active Year \\\n", + "0 Main Oct 2022.0 \n", + "1 Main Jul 2023.0 \n", + "2 Main None NaN \n", + "3 Presidio Jul 2023.0 \n", + "4 Main Jul 2023.0 \n", + "5 Main Jul 2023.0 \n", + "6 Main Mar 2020.0 \n", + "7 Bookmobile Feb 2021.0 \n", + "8 Main Apr 2020.0 \n", + "9 Marina May 2023.0 \n", "\n", - " Notice Preference Definition Provided Email Address \\\n", - "0 phone False \n", - "1 email True \n", - "2 email True \n", - "3 print False \n", - "4 email True \n", - "5 email True \n", - "6 email True \n", - "7 phone True \n", - "8 phone True \n", - "9 email True \n", + " Notice Preference Code Notice Preference Definition Provided Email Address \\\n", + "0 z Email True \n", + "1 z Email True \n", + "2 z Email True \n", + "3 z Email True \n", + "4 z Email True \n", + "5 None None False \n", + "6 z Email True \n", + "7 z Email True \n", + "8 z Email True \n", + "9 z Email True \n", "\n", - " Year Patron Registered Outside of County Supervisor District \n", - "0 2003 False 9.0 \n", - "1 2014 False 5.0 \n", - "2 2010 False 4.0 \n", - "3 2016 True NaN \n", - "4 2015 False 3.0 \n", - "5 2003 False 2.0 \n", - "6 2015 True NaN \n", - "7 2004 False 9.0 \n", - "8 2014 False 5.0 \n", - "9 2011 False 7.0 " + " Year Patron Registered Within San Francisco County \n", + "0 2022 False \n", + "1 2021 False \n", + "2 2023 False \n", + "3 2021 False \n", + "4 2003 False \n", + "5 2003 False \n", + "6 2020 False \n", + "7 2009 False \n", + "8 2017 False \n", + "9 2021 False " ] }, - "execution_count": 41, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -608,7 +610,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -632,6 +634,7 @@ " \n", " \n", " \n", + " Unnamed: 0\n", " Patron Type Code\n", " Patron Type Definition\n", " Total Checkouts\n", @@ -645,258 +648,257 @@ " Notice Preference Definition\n", " Provided Email Address\n", " Year Patron Registered\n", - " Outside of County\n", - " Supervisor District\n", + " Within San Francisco County\n", " \n", " \n", " \n", " \n", + " 0\n", + " 123022\n", + " 2\n", + " Teen\n", " 0\n", " 0\n", - " ADULT\n", - " 1092\n", - " 761\n", - " 60 to 64 years\n", - " M6\n", - " Mission\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", - " False\n", - " 2003\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Oct\n", + " 2022.0\n", + " z\n", + " Email\n", + " True\n", + " 2022\n", " False\n", - " 9.0\n", " \n", " \n", - " 1\n", + " 1\n", + " 125054\n", " 0\n", - " ADULT\n", + " Adult\n", " 0\n", " 0\n", - " 20 to 24 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2014\n", + " 2021\n", " False\n", - " 5.0\n", " \n", " \n", - " 2\n", + " 2\n", + " 87884\n", + " 0\n", + " Adult\n", + " 0\n", " 0\n", - " ADULT\n", - " 31\n", - " 22\n", " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " April\n", - " 2016\n", + " x\n", + " Main\n", + " None\n", + " NaN\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2010\n", + " 2023\n", " False\n", - " 4.0\n", " \n", " \n", - " 3\n", - " 0\n", - " ADULT\n", + " 3\n", + " 409236\n", " 0\n", - " 0\n", - " 45 to 54 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", - " a\n", - " print\n", - " False\n", - " 2016\n", + " Adult\n", + " 19\n", + " 40\n", + " 20 to 24 years\n", + " p9\n", + " Presidio\n", + " Jul\n", + " 2023.0\n", + " z\n", + " Email\n", " True\n", - " NaN\n", + " 2021\n", + " False\n", " \n", " \n", - " 4\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 25 to 34 years\n", - " X\n", - " Main Library\n", - " None\n", - " None\n", + " 4\n", + " 47911\n", + " 3\n", + " Senior\n", + " 1079\n", + " 197\n", + " 75 years and over\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", + " 2003\n", " False\n", - " 3.0\n", " \n", " \n", - " 5\n", + " 5\n", + " 393489\n", " 0\n", - " ADULT\n", - " 126\n", - " 11\n", + " Adult\n", + " 10\n", + " 5\n", " 45 to 54 years\n", - " M2\n", - " Marina\n", - " January\n", - " 2016\n", - " z\n", - " email\n", - " True\n", + " x\n", + " Main\n", + " Jul\n", + " 2023.0\n", + " None\n", + " None\n", + " False\n", " 2003\n", " False\n", - " 2.0\n", " \n", " \n", - " 6\n", - " 3\n", - " SENIOR\n", + " 6\n", + " 5884\n", " 0\n", + " Adult\n", " 0\n", - " 65 to 74 years\n", - " C2\n", - " Chinatown\n", - " None\n", - " None\n", + " 0\n", + " 25 to 34 years\n", + " x\n", + " Main\n", + " Mar\n", + " 2020.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", - " True\n", - " NaN\n", + " 2020\n", + " False\n", " \n", " \n", - " 7\n", - " 0\n", - " ADULT\n", - " 3002\n", - " 1689\n", - " 25 to 34 years\n", - " P5\n", - " Portola\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", + " 7\n", + " 329892\n", + " 2\n", + " Teen\n", + " 137\n", + " 0\n", + " 10 to 19 years\n", + " yb\n", + " Bookmobile\n", + " Feb\n", + " 2021.0\n", + " z\n", + " Email\n", " True\n", - " 2004\n", + " 2009\n", " False\n", - " 9.0\n", " \n", " \n", - " 8\n", + " 8\n", + " 49195\n", + " 1\n", + " Juvenile\n", " 0\n", - " ADULT\n", - " 4\n", " 0\n", - " 25 to 34 years\n", - " C2\n", - " Chinatown\n", - " July\n", - " 2014\n", - " p\n", - " phone\n", + " 10 to 19 years\n", + " x\n", + " Main\n", + " Apr\n", + " 2020.0\n", + " z\n", + " Email\n", " True\n", - " 2014\n", + " 2017\n", " False\n", - " 5.0\n", " \n", " \n", - " 9\n", - " 0\n", - " ADULT\n", - " 20\n", - " 0\n", - " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " June\n", - " 2015\n", + " 9\n", + " 298115\n", + " 1\n", + " Juvenile\n", + " 6\n", + " 23\n", + " 0 to 9 years\n", + " m2\n", + " Marina\n", + " May\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2011\n", + " 2021\n", " False\n", - " 7.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 0 ADULT 1092 761 \n", - "1 0 ADULT 0 0 \n", - "2 0 ADULT 31 22 \n", - "3 0 ADULT 0 0 \n", - "4 0 ADULT 0 0 \n", - "5 0 ADULT 126 11 \n", - "6 3 SENIOR 0 0 \n", - "7 0 ADULT 3002 1689 \n", - "8 0 ADULT 4 0 \n", - "9 0 ADULT 20 0 \n", + " Unnamed: 0 Patron Type Code Patron Type Definition Total Checkouts \\\n", + "0 123022 2 Teen 0 \n", + "1 125054 0 Adult 0 \n", + "2 87884 0 Adult 0 \n", + "3 409236 0 Adult 19 \n", + "4 47911 3 Senior 1079 \n", + "5 393489 0 Adult 10 \n", + "6 5884 0 Adult 0 \n", + "7 329892 2 Teen 137 \n", + "8 49195 1 Juvenile 0 \n", + "9 298115 1 Juvenile 6 \n", "\n", - " Age Range Home Library Code Home Library Definition \\\n", - "0 60 to 64 years M6 Mission \n", - "1 20 to 24 years P1 Park \n", - "2 25 to 34 years S7 Sunset \n", - "3 45 to 54 years P1 Park \n", - "4 25 to 34 years X Main Library \n", - "5 45 to 54 years M2 Marina \n", - "6 65 to 74 years C2 Chinatown \n", - "7 25 to 34 years P5 Portola \n", - "8 25 to 34 years C2 Chinatown \n", - "9 25 to 34 years S7 Sunset \n", + " Total Renewals Age Range Home Library Code \\\n", + "0 0 10 to 19 years x \n", + "1 0 25 to 34 years x \n", + "2 0 25 to 34 years x \n", + "3 40 20 to 24 years p9 \n", + "4 197 75 years and over x \n", + "5 5 45 to 54 years x \n", + "6 0 25 to 34 years x \n", + "7 0 10 to 19 years yb \n", + "8 0 10 to 19 years x \n", + "9 23 0 to 9 years m2 \n", "\n", - " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 July 2016 p \n", - "1 None None z \n", - "2 April 2016 z \n", - "3 None None a \n", - "4 None None z \n", - "5 January 2016 z \n", - "6 None None z \n", - "7 July 2016 p \n", - "8 July 2014 p \n", - "9 June 2015 z \n", + " Home Library Definition Circulation Active Month Circulation Active Year \\\n", + "0 Main Oct 2022.0 \n", + "1 Main Jul 2023.0 \n", + "2 Main None NaN \n", + "3 Presidio Jul 2023.0 \n", + "4 Main Jul 2023.0 \n", + "5 Main Jul 2023.0 \n", + "6 Main Mar 2020.0 \n", + "7 Bookmobile Feb 2021.0 \n", + "8 Main Apr 2020.0 \n", + "9 Marina May 2023.0 \n", "\n", - " Notice Preference Definition Provided Email Address \\\n", - "0 phone False \n", - "1 email True \n", - "2 email True \n", - "3 print False \n", - "4 email True \n", - "5 email True \n", - "6 email True \n", - "7 phone True \n", - "8 phone True \n", - "9 email True \n", + " Notice Preference Code Notice Preference Definition Provided Email Address \\\n", + "0 z Email True \n", + "1 z Email True \n", + "2 z Email True \n", + "3 z Email True \n", + "4 z Email True \n", + "5 None None False \n", + "6 z Email True \n", + "7 z Email True \n", + "8 z Email True \n", + "9 z Email True \n", "\n", - " Year Patron Registered Outside of County Supervisor District \n", - "0 2003 False 9.0 \n", - "1 2014 False 5.0 \n", - "2 2010 False 4.0 \n", - "3 2016 True NaN \n", - "4 2015 False 3.0 \n", - "5 2003 False 2.0 \n", - "6 2015 True NaN \n", - "7 2004 False 9.0 \n", - "8 2014 False 5.0 \n", - "9 2011 False 7.0 " + " Year Patron Registered Within San Francisco County \n", + "0 2022 False \n", + "1 2021 False \n", + "2 2023 False \n", + "3 2021 False \n", + "4 2003 False \n", + "5 2003 False \n", + "6 2020 False \n", + "7 2009 False \n", + "8 2017 False \n", + "9 2021 False " ] }, - "execution_count": 42, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -909,17 +911,26 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ - "df.to_csv('../data/Library_Usage_Small_Copy.csv')" + "df.to_csv('../data/Library_Usage_Small_Copy.csv')\n", + "#df.to_csv('../data/Library_Usage_Small_Copy.csv', index=False) \n", + "#Vergleiche die resultierenden Dateien!" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -933,9 +944,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/content/basics/solutions.files/2.5.solutions_fe.ipynb b/content/basics/solutions.files/2.5.solutions_fe.ipynb index 246c54a5..0fe0814a 100644 --- a/content/basics/solutions.files/2.5.solutions_fe.ipynb +++ b/content/basics/solutions.files/2.5.solutions_fe.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -39,100 +39,94 @@ " Notice Preference Definition\n", " Provided Email Address\n", " Year Patron Registered\n", - " Outside of County\n", - " Supervisor District\n", + " Within San Francisco County\n", " \n", " \n", " \n", " \n", " 0\n", - " 0\n", - " ADULT\n", - " 1092\n", - " 761\n", - " 60 to 64 years\n", - " M6\n", - " Mission\n", - " July\n", - " 2016\n", - " p\n", - " phone\n", - " False\n", + " 5\n", + " Staff\n", + " 53\n", + " 15\n", + " NaN\n", + " b2\n", + " Bayview\n", + " Mar\n", + " 2023.0\n", + " z\n", + " Email\n", + " True\n", " 2003\n", " False\n", - " 9.0\n", " \n", " \n", " 1\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 20 to 24 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", + " 5\n", + " Staff\n", + " 480\n", + " 378\n", + " NaN\n", + " e9\n", + " Excelsior\n", + " Jun\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2014\n", + " 2003\n", " False\n", - " 5.0\n", " \n", " \n", " 2\n", - " 0\n", - " ADULT\n", - " 31\n", - " 22\n", - " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " April\n", - " 2016\n", + " 5\n", + " Staff\n", + " 70\n", + " 33\n", + " 45 to 54 years\n", + " n4\n", + " Noe Valley\n", + " Jan\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2010\n", + " 2011\n", " False\n", - " 4.0\n", " \n", " \n", " 3\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 45 to 54 years\n", - " P1\n", - " Park\n", - " None\n", - " None\n", - " a\n", - " print\n", - " False\n", - " 2016\n", - " True\n", + " 5\n", + " Staff\n", + " 3934\n", + " 2140\n", " NaN\n", + " o2\n", + " Ocean View\n", + " Jul\n", + " 2023.0\n", + " z\n", + " Email\n", + " True\n", + " 2003\n", + " False\n", " \n", " \n", " 4\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 25 to 34 years\n", - " X\n", - " Main Library\n", - " None\n", - " None\n", + " 5\n", + " Staff\n", + " 1118\n", + " 1035\n", + " NaN\n", + " o7\n", + " Ortega\n", + " Jul\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", + " 2003\n", " False\n", - " 3.0\n", " \n", " \n", "\n", @@ -140,42 +134,42 @@ ], "text/plain": [ " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 0 ADULT 1092 761 \n", - "1 0 ADULT 0 0 \n", - "2 0 ADULT 31 22 \n", - "3 0 ADULT 0 0 \n", - "4 0 ADULT 0 0 \n", + "0 5 Staff 53 15 \n", + "1 5 Staff 480 378 \n", + "2 5 Staff 70 33 \n", + "3 5 Staff 3934 2140 \n", + "4 5 Staff 1118 1035 \n", "\n", " Age Range Home Library Code Home Library Definition \\\n", - "0 60 to 64 years M6 Mission \n", - "1 20 to 24 years P1 Park \n", - "2 25 to 34 years S7 Sunset \n", - "3 45 to 54 years P1 Park \n", - "4 25 to 34 years X Main Library \n", + "0 NaN b2 Bayview \n", + "1 NaN e9 Excelsior \n", + "2 45 to 54 years n4 Noe Valley \n", + "3 NaN o2 Ocean View \n", + "4 NaN o7 Ortega \n", "\n", - " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 July 2016 p \n", - "1 None None z \n", - "2 April 2016 z \n", - "3 None None a \n", - "4 None None z \n", + " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", + "0 Mar 2023.0 z \n", + "1 Jun 2023.0 z \n", + "2 Jan 2023.0 z \n", + "3 Jul 2023.0 z \n", + "4 Jul 2023.0 z \n", "\n", " Notice Preference Definition Provided Email Address \\\n", - "0 phone False \n", - "1 email True \n", - "2 email True \n", - "3 print False \n", - "4 email True \n", + "0 Email True \n", + "1 Email True \n", + "2 Email True \n", + "3 Email True \n", + "4 Email True \n", "\n", - " Year Patron Registered Outside of County Supervisor District \n", - "0 2003 False 9.0 \n", - "1 2014 False 5.0 \n", - "2 2010 False 4.0 \n", - "3 2016 True NaN \n", - "4 2015 False 3.0 " + " Year Patron Registered Within San Francisco County \n", + "0 2003 False \n", + "1 2003 False \n", + "2 2011 False \n", + "3 2003 False \n", + "4 2003 False " ] }, - "execution_count": 6, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -183,67 +177,107 @@ "source": [ "import pandas as pd\n", "\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")\n", + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + " )\n", "df.head()" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 2016.0\n", - "1 NaN\n", - "2 2016.0\n", - "3 NaN\n", - "4 NaN\n", + "0 2023.0\n", + "1 2023.0\n", + "2 2023.0\n", + "3 2023.0\n", + "4 2023.0\n", " ... \n", - "423443 2015.0\n", - "423444 2016.0\n", - "423445 2016.0\n", - "423446 2015.0\n", - "423447 NaN\n", - "Name: Circulation Active Year, Length: 423448, dtype: float64" + "436285 2022.0\n", + "436286 2015.0\n", + "436287 2022.0\n", + "436288 2020.0\n", + "436289 2023.0\n", + "Name: Circulation Active Year, Length: 436290, dtype: float64" ] }, - "execution_count": 7, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Circulation Active Year'] = pd.to_numeric(\n", - " df['Circulation Active Year'], errors='coerce'\n", + " df['Circulation Active Year'], \n", + " errors='coerce'\n", ")\n", "df['Circulation Active Year']" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 436290 entries, 0 to 436289\n", + "Data columns (total 14 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Patron Type Code 436290 non-null int64 \n", + " 1 Patron Type Definition 436290 non-null object \n", + " 2 Total Checkouts 436290 non-null int64 \n", + " 3 Total Renewals 436290 non-null int64 \n", + " 4 Age Range 435378 non-null object \n", + " 5 Home Library Code 436288 non-null object \n", + " 6 Home Library Definition 436290 non-null object \n", + " 7 Circulation Active Month 396777 non-null object \n", + " 8 Circulation Active Year 396777 non-null float64\n", + " 9 Notice Preference Code 393301 non-null object \n", + " 10 Notice Preference Definition 436290 non-null object \n", + " 11 Provided Email Address 436290 non-null bool \n", + " 12 Year Patron Registered 436290 non-null int64 \n", + " 13 Within San Francisco County 435083 non-null object \n", + "dtypes: bool(1), float64(1), int64(4), object(8)\n", + "memory usage: 43.7+ MB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 1900-07-01\n", - "1 NaT\n", - "2 1900-04-01\n", - "3 NaT\n", - "4 NaT\n", + "0 1900-03-01\n", + "1 1900-06-01\n", + "2 1900-01-01\n", + "3 1900-07-01\n", + "4 1900-07-01\n", " ... \n", - "423443 1900-03-01\n", - "423444 1900-07-01\n", - "423445 1900-07-01\n", - "423446 1900-04-01\n", - "423447 NaT\n", - "Name: Circulation Active Month, Length: 423448, dtype: datetime64[ns]" + "436285 1900-10-01\n", + "436286 1900-11-01\n", + "436287 1900-03-01\n", + "436288 1900-09-01\n", + "436289 1900-07-01\n", + "Name: Circulation Active Month, Length: 436290, dtype: datetime64[ns]" ] }, - "execution_count": 8, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -252,34 +286,34 @@ "df['Circulation Active Month'] = pd.to_datetime(\n", " df['Circulation Active Month'],\n", " errors='coerce',\n", - " format=\"%B\"\n", + " format=\"%b\"\n", ")\n", "df['Circulation Active Month']" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 7.0\n", - "1 NaN\n", - "2 4.0\n", - "3 NaN\n", - "4 NaN\n", - " ... \n", - "423443 3.0\n", - "423444 7.0\n", - "423445 7.0\n", - "423446 4.0\n", - "423447 NaN\n", - "Name: Circulation Active Month, Length: 423448, dtype: float64" + "0 3.0\n", + "1 6.0\n", + "2 1.0\n", + "3 7.0\n", + "4 7.0\n", + " ... \n", + "436285 10.0\n", + "436286 11.0\n", + "436287 3.0\n", + "436288 9.0\n", + "436289 7.0\n", + "Name: Circulation Active Month, Length: 436290, dtype: float64" ] }, - "execution_count": 9, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -291,7 +325,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -302,27 +336,27 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 163.0\n", - "1 0.0\n", - "2 76.0\n", - "3 0.0\n", - "4 0.0\n", + "0 243.0\n", + "1 246.0\n", + "2 145.0\n", + "3 247.0\n", + "4 247.0\n", " ... \n", - "423443 75.0\n", - "423444 7.0\n", - "423445 31.0\n", - "423446 148.0\n", - "423447 0.0\n", - "Name: Membership Duration, Length: 423448, dtype: float64" + "436285 34.0\n", + "436286 59.0\n", + "436287 3.0\n", + "436288 21.0\n", + "436289 247.0\n", + "Name: Membership Duration, Length: 436290, dtype: float64" ] }, - "execution_count": 11, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -334,7 +368,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -371,106 +405,100 @@ " Notice Preference Definition\n", " Provided Email Address\n", " Year Patron Registered\n", - " Outside of County\n", - " Supervisor District\n", + " Within San Francisco County\n", " Membership Duration\n", " \n", " \n", " \n", " \n", " 0\n", - " 0\n", - " ADULT\n", - " 1092\n", - " 761\n", - " 60 to 64 years\n", - " M6\n", - " Mission\n", - " 7.0\n", - " 2016.0\n", - " p\n", - " phone\n", - " False\n", + " 5\n", + " Staff\n", + " 53\n", + " 15\n", + " NaN\n", + " b2\n", + " Bayview\n", + " 3.0\n", + " 2023.0\n", + " z\n", + " Email\n", + " True\n", " 2003\n", " False\n", - " 9.0\n", - " 163.0\n", + " 243.0\n", " \n", " \n", " 1\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 20 to 24 years\n", - " P1\n", - " Park\n", - " NaN\n", + " 5\n", + " Staff\n", + " 480\n", + " 378\n", " NaN\n", + " e9\n", + " Excelsior\n", + " 6.0\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2014\n", + " 2003\n", " False\n", - " 5.0\n", - " 0.0\n", + " 246.0\n", " \n", " \n", " 2\n", - " 0\n", - " ADULT\n", - " 31\n", - " 22\n", - " 25 to 34 years\n", - " S7\n", - " Sunset\n", - " 4.0\n", - " 2016.0\n", + " 5\n", + " Staff\n", + " 70\n", + " 33\n", + " 45 to 54 years\n", + " n4\n", + " Noe Valley\n", + " 1.0\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2010\n", + " 2011\n", " False\n", - " 4.0\n", - " 76.0\n", + " 145.0\n", " \n", " \n", " 3\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 45 to 54 years\n", - " P1\n", - " Park\n", - " NaN\n", + " 5\n", + " Staff\n", + " 3934\n", + " 2140\n", " NaN\n", - " a\n", - " print\n", - " False\n", - " 2016\n", + " o2\n", + " Ocean View\n", + " 7.0\n", + " 2023.0\n", + " z\n", + " Email\n", " True\n", - " NaN\n", - " 0.0\n", + " 2003\n", + " False\n", + " 247.0\n", " \n", " \n", " 4\n", - " 0\n", - " ADULT\n", - " 0\n", - " 0\n", - " 25 to 34 years\n", - " X\n", - " Main Library\n", - " NaN\n", + " 5\n", + " Staff\n", + " 1118\n", + " 1035\n", " NaN\n", + " o7\n", + " Ortega\n", + " 7.0\n", + " 2023.0\n", " z\n", - " email\n", + " Email\n", " True\n", - " 2015\n", + " 2003\n", " False\n", - " 3.0\n", - " 0.0\n", + " 247.0\n", " \n", " \n", "\n", @@ -478,49 +506,42 @@ ], "text/plain": [ " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 0 ADULT 1092 761 \n", - "1 0 ADULT 0 0 \n", - "2 0 ADULT 31 22 \n", - "3 0 ADULT 0 0 \n", - "4 0 ADULT 0 0 \n", + "0 5 Staff 53 15 \n", + "1 5 Staff 480 378 \n", + "2 5 Staff 70 33 \n", + "3 5 Staff 3934 2140 \n", + "4 5 Staff 1118 1035 \n", "\n", " Age Range Home Library Code Home Library Definition \\\n", - "0 60 to 64 years M6 Mission \n", - "1 20 to 24 years P1 Park \n", - "2 25 to 34 years S7 Sunset \n", - "3 45 to 54 years P1 Park \n", - "4 25 to 34 years X Main Library \n", + "0 NaN b2 Bayview \n", + "1 NaN e9 Excelsior \n", + "2 45 to 54 years n4 Noe Valley \n", + "3 NaN o2 Ocean View \n", + "4 NaN o7 Ortega \n", "\n", " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 7.0 2016.0 p \n", - "1 NaN NaN z \n", - "2 4.0 2016.0 z \n", - "3 NaN NaN a \n", - "4 NaN NaN z \n", + "0 3.0 2023.0 z \n", + "1 6.0 2023.0 z \n", + "2 1.0 2023.0 z \n", + "3 7.0 2023.0 z \n", + "4 7.0 2023.0 z \n", "\n", " Notice Preference Definition Provided Email Address \\\n", - "0 phone False \n", - "1 email True \n", - "2 email True \n", - "3 print False \n", - "4 email True \n", - "\n", - " Year Patron Registered Outside of County Supervisor District \\\n", - "0 2003 False 9.0 \n", - "1 2014 False 5.0 \n", - "2 2010 False 4.0 \n", - "3 2016 True NaN \n", - "4 2015 False 3.0 \n", + "0 Email True \n", + "1 Email True \n", + "2 Email True \n", + "3 Email True \n", + "4 Email True \n", "\n", - " Membership Duration \n", - "0 163.0 \n", - "1 0.0 \n", - "2 76.0 \n", - "3 0.0 \n", - "4 0.0 " + " Year Patron Registered Within San Francisco County Membership Duration \n", + "0 2003 False 243.0 \n", + "1 2003 False 246.0 \n", + "2 2011 False 145.0 \n", + "3 2003 False 247.0 \n", + "4 2003 False 247.0 " ] }, - "execution_count": 12, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -528,11 +549,18 @@ "source": [ "df.head()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -546,9 +574,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/content/basics/solutions.files/2.6.solutions_selection.ipynb b/content/basics/solutions.files/2.6.solutions_selection.ipynb index 2b92dbd3..c745674e 100644 --- a/content/basics/solutions.files/2.6.solutions_selection.ipynb +++ b/content/basics/solutions.files/2.6.solutions_selection.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -17,38 +17,40 @@ " dtype='object')" ] }, - "execution_count": 6, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")\n", + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + " )\n", "df.columns" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "34642\n", + "32692\n", "9\n", - "20736\n" + "20656\n" ] } ], "source": [ - "# Filter Sie den Datensatz nach Kindern unter 10 Jahren. Wie viele Einträge erhalten Sie?\n", + "# Filtere den Datensatz nach Kindern unter 10 Jahren. Wie viele Einträge erhältst Du?\n", "\n", "print(len(df[df['Age Range'] == '0 to 9 years']))\n", "\n", - "# alternative\n", + "# Alternative\n", "#(df['Age Range'] == '0 to 9 years').sum()\n", "\n", "# Gibt es Personen mit mehr als 20000 Ausleihen?\n", @@ -68,29 +70,25 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": {}, "outputs": [ { - "ename": "KeyError", - "evalue": "'Membership Duration'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3628\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3629\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3630\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m: 'Membership Duration'", - "\nThe above exception was the direct cause of the following exception:\n", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/var/folders/xc/0ys6f7w12cq2dq1xqlg9nmcm0000gn/T/ipykernel_8849/1805301601.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0;31m#### ###\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Membership Duration'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 28\u001b[0m \u001b[0;31m# alternative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3503\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3504\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3505\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3506\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3507\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3629\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3630\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3631\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3632\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3633\u001b[0m \u001b[0;31m# If we have a listlike key, _check_indexing_error will raise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m: 'Membership Duration'" + "name": "stdout", + "output_type": "stream", + "text": [ + "0.09056590799697449\n" ] + }, + { + "data": { + "text/plain": [ + "0.09056590799697449" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -108,7 +106,7 @@ "#df['Circulation Active Month'] = pd.to_datetime(\n", "# df['Circulation Active Month'],\n", "# errors='coerce',\n", - "# format=\"%B\"\n", + "# format=\"%b\"\n", "#)\n", "#\n", "#df['Circulation Active Month'] = df['Circulation Active Month'].dt.month\n", diff --git a/content/basics/solutions.files/2.8.solutions_na.ipynb b/content/basics/solutions.files/2.8.solutions_na.ipynb index 932495d4..bdb81358 100644 --- a/content/basics/solutions.files/2.8.solutions_na.ipynb +++ b/content/basics/solutions.files/2.8.solutions_na.ipynb @@ -2,41 +2,42 @@ "cells": [ { "cell_type": "code", - "execution_count": 16, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", - "df = pd.read_csv('../data/Library_Usage.csv')" + "df = pd.read_csv('../data/Library_Usage.csv',\n", + " low_memory=False\n", + " )" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Patron Type Code 0\n", - "Patron Type Definition 0\n", - "Total Checkouts 0\n", - "Total Renewals 0\n", - "Age Range 215\n", - "Home Library Code 40\n", - "Home Library Definition 0\n", - "Circulation Active Month 0\n", - "Circulation Active Year 0\n", - "Notice Preference Code 0\n", - "Notice Preference Definition 0\n", - "Provided Email Address 0\n", - "Year Patron Registered 0\n", - "Outside of County 0\n", - "Supervisor District 110310\n", + "Patron Type Code 0\n", + "Patron Type Definition 0\n", + "Total Checkouts 0\n", + "Total Renewals 0\n", + "Age Range 912\n", + "Home Library Code 2\n", + "Home Library Definition 0\n", + "Circulation Active Month 39513\n", + "Circulation Active Year 39513\n", + "Notice Preference Code 42989\n", + "Notice Preference Definition 0\n", + "Provided Email Address 0\n", + "Year Patron Registered 0\n", + "Within San Francisco County 1207\n", "dtype: int64" ] }, - "execution_count": 17, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -47,31 +48,30 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Patron Type Code 0\n", - "Patron Type Definition 0\n", - "Total Checkouts 0\n", - "Total Renewals 0\n", - "Age Range 215\n", - "Home Library Code 40\n", - "Home Library Definition 0\n", - "Circulation Active Month 0\n", - "Circulation Active Year 0\n", - "Notice Preference Code 0\n", - "Notice Preference Definition 0\n", - "Provided Email Address 0\n", - "Year Patron Registered 0\n", - "Outside of County 0\n", - "Supervisor District 110310\n", + "Patron Type Code 0\n", + "Patron Type Definition 0\n", + "Total Checkouts 0\n", + "Total Renewals 0\n", + "Age Range 912\n", + "Home Library Code 2\n", + "Home Library Definition 0\n", + "Circulation Active Month 39513\n", + "Circulation Active Year 39513\n", + "Notice Preference Code 42989\n", + "Notice Preference Definition 0\n", + "Provided Email Address 0\n", + "Year Patron Registered 0\n", + "Within San Francisco County 1207\n", "dtype: int64" ] }, - "execution_count": 18, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -82,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -101,12 +101,11 @@ "Notice Preference Definition 0\n", "Provided Email Address 0\n", "Year Patron Registered 0\n", - "Outside of County 0\n", - "Supervisor District 0\n", + "Within San Francisco County 0\n", "dtype: int64" ] }, - "execution_count": 19, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -118,16 +117,16 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "110480" + "78435" ] }, - "execution_count": 20, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -138,17 +137,24 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "df_clean.to_csv('../data/Library_Usage_Clean.csv', index=False)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -162,9 +168,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/content/descriptive_statistics/solutions.files/3.1.solutions_frequency.ipynb b/content/descriptive_statistics/solutions.files/3.1.solutions_frequency.ipynb index fb10873c..763764ec 100644 --- a/content/descriptive_statistics/solutions.files/3.1.solutions_frequency.ipynb +++ b/content/descriptive_statistics/solutions.files/3.1.solutions_frequency.ipynb @@ -25,7 +25,9 @@ "source": [ "import pandas as pd\n", "\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")\n", + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + " )\n", "df.columns" ] }, @@ -37,26 +39,27 @@ { "data": { "text/plain": [ - "2019 0.129112\n", - "2022 0.119824\n", - "2003 0.098150\n", - "2020 0.075493\n", - "2021 0.074507\n", - "2017 0.069590\n", - "2018 0.069231\n", - "2016 0.051591\n", - "2015 0.048282\n", - "2014 0.038955\n", - "2013 0.032589\n", - "2012 0.031818\n", - "2011 0.030392\n", - "2009 0.027677\n", - "2010 0.027187\n", - "2008 0.024616\n", - "2007 0.015785\n", - "2006 0.012763\n", - "2005 0.011596\n", - "2004 0.010839\n", + "2022 0.119583\n", + "2019 0.101515\n", + "2003 0.094052\n", + "2021 0.074799\n", + "2020 0.073369\n", + "2017 0.067203\n", + "2018 0.065603\n", + "2023 0.060249\n", + "2016 0.049781\n", + "2015 0.046201\n", + "2014 0.036593\n", + "2013 0.030553\n", + "2012 0.029066\n", + "2011 0.028348\n", + "2009 0.026109\n", + "2010 0.025779\n", + "2008 0.023154\n", + "2007 0.014862\n", + "2006 0.012042\n", + "2005 0.010910\n", + "2004 0.010229\n", "Name: Year Patron Registered, dtype: float64" ] }, @@ -77,16 +80,16 @@ { "data": { "text/plain": [ - "25 to 34 years 0.212729\n", - "35 to 44 years 0.184501\n", - "10 to 19 years 0.154337\n", - "45 to 54 years 0.111768\n", - "0 to 9 years 0.079420\n", - "65 to 74 years 0.073147\n", - "20 to 24 years 0.056132\n", - "55 to 59 years 0.044203\n", - "75 years and over 0.043266\n", - "60 to 64 years 0.040496\n", + "25 to 34 years 0.212847\n", + "35 to 44 years 0.187697\n", + "10 to 19 years 0.153561\n", + "45 to 54 years 0.110982\n", + "0 to 9 years 0.075089\n", + "65 to 74 years 0.072842\n", + "20 to 24 years 0.058296\n", + "75 years and over 0.044322\n", + "55 to 59 years 0.043815\n", + "60 to 64 years 0.040549\n", "Name: Age Range, dtype: float64" ] }, @@ -107,7 +110,7 @@ { "data": { "text/plain": [ - "927" + "912" ] }, "execution_count": 4, @@ -157,16 +160,16 @@ { "data": { "text/plain": [ - "25 to 34 years 0.214399\n", - "35 to 44 years 0.184109\n", - "10 to 19 years 0.154010\n", - "45 to 54 years 0.111531\n", - "0 to 9 years 0.079251\n", - "65 to 74 years 0.072992\n", - "20 to 24 years 0.056013\n", - "55 to 59 years 0.044110\n", - "75 years and over 0.043174\n", - "60 to 64 years 0.040410\n", + "25 to 34 years 0.214493\n", + "35 to 44 years 0.187304\n", + "10 to 19 years 0.153240\n", + "45 to 54 years 0.110750\n", + "0 to 9 years 0.074932\n", + "65 to 74 years 0.072690\n", + "20 to 24 years 0.058175\n", + "75 years and over 0.044230\n", + "55 to 59 years 0.043723\n", + "60 to 64 years 0.040464\n", "Name: Age Range, dtype: float64" ] }, @@ -187,7 +190,7 @@ { "data": { "text/plain": [ - "3.9185830657498233" + "3.8881000004302892" ] }, "execution_count": 8, @@ -207,7 +210,7 @@ { "data": { "text/plain": [ - "3.9185830657498233" + "3.8881000004302892" ] }, "execution_count": 9, diff --git a/content/descriptive_statistics/solutions.files/3.4.solutions_variance.ipynb b/content/descriptive_statistics/solutions.files/3.4.solutions_variance.ipynb index 93c15419..5b2c2168 100644 --- a/content/descriptive_statistics/solutions.files/3.4.solutions_variance.ipynb +++ b/content/descriptive_statistics/solutions.files/3.4.solutions_variance.ipynb @@ -2,27 +2,29 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")" + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + " )" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "3.3120898292646523" + "3.355838965971548" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -33,16 +35,16 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "3.9185830657498233" + "3.8881000004302892" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } diff --git a/content/descriptive_statistics/solutions.files/Musterloesung_Projektaufgabe.ipynb b/content/descriptive_statistics/solutions.files/Musterloesung_Projektaufgabe.ipynb index 713ca1f2..4cbc36fe 100644 --- a/content/descriptive_statistics/solutions.files/Musterloesung_Projektaufgabe.ipynb +++ b/content/descriptive_statistics/solutions.files/Musterloesung_Projektaufgabe.ipynb @@ -12,7 +12,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Grundlage: Datensatz der San Francisco Public Library, s.a. https://zbmed.github.io/2020-2021-ZK_Data_Librarian_Modul_3/organisation/dataset/" + "#### Grundlage: Datensatz der San Francisco Public Library, s.a. https://zbmed.github.io/2023-2024-ZK_Data_Librarian_Modul_3/organisation/dataset/" ] }, { @@ -38,7 +38,10 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true, + "tags": [] + }, "source": [ "##### Frage 4: Wie viele Ausleihen werden im Mittel pro Altersgruppe und pro Jahr getätigt? Ist die Streuung zwischen den Gruppen gleich?" ] @@ -87,7 +90,8 @@ "source": [ "df = pd.read_csv(\n", " \"../data/Library_Usage.csv\",\n", - " na_values=\"none\"\n", + " na_values=\"none\",\n", + " low_memory=False\n", ")\n", "# Einlesen des Datensatzes in das neu definierte DataFrame df mit Überschreibung \n", "#fehlender Werte" @@ -138,88 +142,88 @@ " \n", " \n", " 0\n", - " 1\n", - " Juvenile\n", - " 0\n", - " 0\n", - " 0 to 9 years\n", - " r3\n", - " Richmond\n", - " NaN\n", + " 5\n", + " Staff\n", + " 53\n", + " 15\n", " NaN\n", + " b2\n", + " Bayview\n", + " Mar\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2022\n", - " True\n", + " 2003\n", + " False\n", " \n", " \n", " 1\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " x\n", - " Main\n", - " NaN\n", + " 5\n", + " Staff\n", + " 480\n", + " 378\n", " NaN\n", + " e9\n", + " Excelsior\n", + " Jun\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2022\n", - " True\n", + " 2003\n", + " False\n", " \n", " \n", " 2\n", - " 0\n", - " Adult\n", - " 0\n", - " 0\n", - " 35 to 44 years\n", - " m4\n", - " Merced\n", - " NaN\n", - " NaN\n", + " 5\n", + " Staff\n", + " 70\n", + " 33\n", + " 45 to 54 years\n", + " n4\n", + " Noe Valley\n", + " Jan\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2019\n", - " True\n", + " 2011\n", + " False\n", " \n", " \n", " 3\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " x\n", - " Main\n", - " NaN\n", + " 5\n", + " Staff\n", + " 3934\n", + " 2140\n", " NaN\n", + " o2\n", + " Ocean View\n", + " Jul\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2021\n", - " True\n", + " 2003\n", + " False\n", " \n", " \n", " 4\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " b2\n", - " Bayview\n", - " NaN\n", + " 5\n", + " Staff\n", + " 1118\n", + " 1035\n", " NaN\n", + " o7\n", + " Ortega\n", + " Jul\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2013\n", - " True\n", + " 2003\n", + " False\n", " \n", " \n", "\n", @@ -227,25 +231,25 @@ ], "text/plain": [ " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 1 Juvenile 0 0 \n", - "1 2 Teen 0 0 \n", - "2 0 Adult 0 0 \n", - "3 2 Teen 0 0 \n", - "4 2 Teen 0 0 \n", + "0 5 Staff 53 15 \n", + "1 5 Staff 480 378 \n", + "2 5 Staff 70 33 \n", + "3 5 Staff 3934 2140 \n", + "4 5 Staff 1118 1035 \n", "\n", " Age Range Home Library Code Home Library Definition \\\n", - "0 0 to 9 years r3 Richmond \n", - "1 10 to 19 years x Main \n", - "2 35 to 44 years m4 Merced \n", - "3 10 to 19 years x Main \n", - "4 10 to 19 years b2 Bayview \n", + "0 NaN b2 Bayview \n", + "1 NaN e9 Excelsior \n", + "2 45 to 54 years n4 Noe Valley \n", + "3 NaN o2 Ocean View \n", + "4 NaN o7 Ortega \n", "\n", " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 NaN NaN z \n", - "1 NaN NaN z \n", - "2 NaN NaN z \n", - "3 NaN NaN z \n", - "4 NaN NaN z \n", + "0 Mar 2023.0 z \n", + "1 Jun 2023.0 z \n", + "2 Jan 2023.0 z \n", + "3 Jul 2023.0 z \n", + "4 Jul 2023.0 z \n", "\n", " Notice Preference Definition Provided Email Address \\\n", "0 Email True \n", @@ -254,12 +258,12 @@ "3 Email True \n", "4 Email True \n", "\n", - " Year Patron Registered Within San Francisco County \n", - "0 2022 True \n", - "1 2022 True \n", - "2 2019 True \n", - "3 2021 True \n", - "4 2013 True " + " Year Patron Registered Within San Francisco County \n", + "0 2003 False \n", + "1 2003 False \n", + "2 2011 False \n", + "3 2003 False \n", + "4 2003 False " ] }, "execution_count": 3, @@ -295,24 +299,23 @@ { "data": { "text/plain": [ - "Adult 271588\n", - "Juvenile 58767\n", - "Senior 47366\n", - "Teen 40340\n", - "Welcome 10587\n", - "Digital Access Card 3707\n", - "Teacher Card 3161\n", - "Staff 808\n", - "Retired Staff 209\n", - "At User Adult 128\n", - "Library By Mail 117\n", - "Visitor 111\n", - "Bibliocommons 109\n", - "At User Senior 76\n", - "At User Welcome 14\n", - "At User Teen 10\n", - "At User Juvenile 9\n", - "Business 8\n", + "Adult 274682\n", + "Juvenile 53281\n", + "Senior 49332\n", + "Teen 40561\n", + "Welcome 9966\n", + "Digital Access Card 3714\n", + "Teacher Card 3234\n", + "Staff 806\n", + "Retired Staff 215\n", + "Visitor 148\n", + "Library By Mail 120\n", + "At User Adult 118\n", + "At User Senior 78\n", + "At User Welcome 13\n", + "At User Teen 8\n", + "Business 7\n", + "At User Juvenile 7\n", "Name: Patron Type Definition, dtype: int64" ] }, @@ -340,16 +343,16 @@ { "data": { "text/plain": [ - "25 to 34 years 92790\n", - "35 to 44 years 80477\n", - "10 to 19 years 67320\n", - "45 to 54 years 48752\n", - "0 to 9 years 34642\n", - "65 to 74 years 31906\n", - "20 to 24 years 24484\n", - "55 to 59 years 19281\n", - "75 years and over 18872\n", - "60 to 64 years 17664\n", + "25 to 34 years 92669\n", + "35 to 44 years 81719\n", + "10 to 19 years 66857\n", + "45 to 54 years 48319\n", + "0 to 9 years 32692\n", + "65 to 74 years 31714\n", + "20 to 24 years 25381\n", + "75 years and over 19297\n", + "55 to 59 years 19076\n", + "60 to 64 years 17654\n", "Name: Age Range, dtype: int64" ] }, @@ -405,7 +408,7 @@ { "data": { "text/plain": [ - "101962" + "99549" ] }, "execution_count": 7, @@ -438,7 +441,7 @@ { "data": { "text/plain": [ - "50778" + "51011" ] }, "execution_count": 9, @@ -466,7 +469,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Es sind 101962 Kinder (bis 19 Jahre) und 50778 Senioren (ab 65 Jahren) registriert.\n" + "Es sind 99549 Kinder (bis 19 Jahre) und 51011 Senioren (ab 65 Jahren) registriert.\n" ] } ], @@ -490,16 +493,16 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "391614" + "393301" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -517,14 +520,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "391614 Nutzer möchten per Mail informiert werden.\n" + "393301 Nutzer möchten per Mail informiert werden.\n" ] } ], @@ -548,20 +551,18 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Email 391614\n", - "Phone 35559\n", - "Print 7242\n", - "None 2700\n", + "Email 393301\n", + "None 42989\n", "Name: Notice Preference Definition, dtype: int64" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -593,34 +594,34 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "benachrichtigung=df.loc[\n", " (df['Notice Preference Definition'] == \"Email\") | \n", - " (df['Notice Preference Definition'] == \"Print\")\n", + " (df['Notice Preference Definition'] == \"None\")\n", "] #Hilfsvariable für den Plot, damit nur die Merkmale 'email' und 'print' angezeigt werden" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 18, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -643,7 +644,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -697,45 +698,45 @@ " \n", " \n", " Email\n", - " 29979\n", - " 55109\n", - " 21740\n", - " 88098\n", - " 76322\n", - " 45360\n", - " 17403\n", - " 15438\n", - " 26988\n", - " 14340\n", - " 390777\n", + " 28740\n", + " 54936\n", + " 22701\n", + " 88200\n", + " 77618\n", + " 45165\n", + " 17336\n", + " 15539\n", + " 27170\n", + " 15069\n", + " 392474\n", " \n", " \n", - " Print\n", - " 1276\n", - " 665\n", - " 338\n", - " 1210\n", - " 1064\n", - " 683\n", - " 328\n", - " 346\n", - " 703\n", - " 579\n", - " 7192\n", + " None\n", + " 3952\n", + " 11921\n", + " 2680\n", + " 4469\n", + " 4101\n", + " 3154\n", + " 1740\n", + " 2115\n", + " 4544\n", + " 4228\n", + " 42904\n", " \n", " \n", " All\n", - " 31255\n", - " 55774\n", - " 22078\n", - " 89308\n", - " 77386\n", - " 46043\n", - " 17731\n", - " 15784\n", - " 27691\n", - " 14919\n", - " 397969\n", + " 32692\n", + " 66857\n", + " 25381\n", + " 92669\n", + " 81719\n", + " 48319\n", + " 19076\n", + " 17654\n", + " 31714\n", + " 19297\n", + " 435378\n", " \n", " \n", "\n", @@ -744,30 +745,30 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Notice Preference Definition \n", - "Email 29979 55109 21740 \n", - "Print 1276 665 338 \n", - "All 31255 55774 22078 \n", + "Email 28740 54936 22701 \n", + "None 3952 11921 2680 \n", + "All 32692 66857 25381 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Notice Preference Definition \n", - "Email 88098 76322 45360 \n", - "Print 1210 1064 683 \n", - "All 89308 77386 46043 \n", + "Email 88200 77618 45165 \n", + "None 4469 4101 3154 \n", + "All 92669 81719 48319 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Notice Preference Definition \n", - "Email 17403 15438 26988 \n", - "Print 328 346 703 \n", - "All 17731 15784 27691 \n", + "Email 17336 15539 27170 \n", + "None 1740 2115 4544 \n", + "All 19076 17654 31714 \n", "\n", "Age Range 75 years and over All \n", "Notice Preference Definition \n", - "Email 14340 390777 \n", - "Print 579 7192 \n", - "All 14919 397969 " + "Email 15069 392474 \n", + "None 4228 42904 \n", + "All 19297 435378 " ] }, - "execution_count": 19, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -789,7 +790,7 @@ "source": [ "----\n", "###### WICHTIG:\n", - "Beachte, dass die Summe der Nutzer, die per Mail informiert werden hier 390777 ergibt. Wir haben aber bei Frage 2 festgestellt, dass eigentlich 391614 Nutzer per Mail informiert werden möchten.\n", + "Beachte, dass die Summe der Nutzer, die per Mail informiert werden hier 392474 ergibt. Wir haben aber bei Frage 2 festgestellt, dass eigentlich 393301 Nutzer per Mail informiert werden möchten.\n", "Dies liegt daran, dass offensichtlich in einigen Einträgen (Zeilen des Datensatzes) zwar im Feld \"Notice Preference Definition\" der Wert \"Email\" steht, aber offensichtlich im Feld \"Age Range\" kein Eintrag steht. In der Kreuztabelle werden die beiden Merkmale 'Age Range' und 'Notice Preference Definition' betrachtet und somit nur die Einträge, wo entsprechednd beide Felder ausgefüllt sind.\n", "\n", "(Das ist übrigens unabhängig ob man die Kreuztabelle über die \"große\" Variable \"df\" oder \"benachrichtigung\" berechnet, probiere es gerne aus!)\n", @@ -799,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -851,42 +852,42 @@ " \n", " \n", " Email\n", - " 0.076716\n", - " 0.141024\n", - " 0.055633\n", - " 0.225443\n", - " 0.195308\n", - " 0.116076\n", - " 0.044534\n", - " 0.039506\n", - " 0.069062\n", - " 0.036696\n", + " 0.073228\n", + " 0.139974\n", + " 0.057841\n", + " 0.224728\n", + " 0.197766\n", + " 0.115078\n", + " 0.044171\n", + " 0.039592\n", + " 0.069228\n", + " 0.038395\n", " \n", " \n", - " Print\n", - " 0.177419\n", - " 0.092464\n", - " 0.046997\n", - " 0.168242\n", - " 0.147942\n", - " 0.094967\n", - " 0.045606\n", - " 0.048109\n", - " 0.097747\n", - " 0.080506\n", + " None\n", + " 0.092113\n", + " 0.277853\n", + " 0.062465\n", + " 0.104163\n", + " 0.095585\n", + " 0.073513\n", + " 0.040556\n", + " 0.049296\n", + " 0.105911\n", + " 0.098546\n", " \n", " \n", " All\n", - " 0.078536\n", - " 0.140147\n", - " 0.055477\n", - " 0.224409\n", - " 0.194452\n", - " 0.115695\n", - " 0.044554\n", - " 0.039661\n", - " 0.069581\n", - " 0.037488\n", + " 0.075089\n", + " 0.153561\n", + " 0.058296\n", + " 0.212847\n", + " 0.187697\n", + " 0.110982\n", + " 0.043815\n", + " 0.040549\n", + " 0.072842\n", + " 0.044322\n", " \n", " \n", "\n", @@ -895,30 +896,30 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Notice Preference Definition \n", - "Email 0.076716 0.141024 0.055633 \n", - "Print 0.177419 0.092464 0.046997 \n", - "All 0.078536 0.140147 0.055477 \n", + "Email 0.073228 0.139974 0.057841 \n", + "None 0.092113 0.277853 0.062465 \n", + "All 0.075089 0.153561 0.058296 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Notice Preference Definition \n", - "Email 0.225443 0.195308 0.116076 \n", - "Print 0.168242 0.147942 0.094967 \n", - "All 0.224409 0.194452 0.115695 \n", + "Email 0.224728 0.197766 0.115078 \n", + "None 0.104163 0.095585 0.073513 \n", + "All 0.212847 0.187697 0.110982 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Notice Preference Definition \n", - "Email 0.044534 0.039506 0.069062 \n", - "Print 0.045606 0.048109 0.097747 \n", - "All 0.044554 0.039661 0.069581 \n", + "Email 0.044171 0.039592 0.069228 \n", + "None 0.040556 0.049296 0.105911 \n", + "All 0.043815 0.040549 0.072842 \n", "\n", "Age Range 75 years and over \n", "Notice Preference Definition \n", - "Email 0.036696 \n", - "Print 0.080506 \n", - "All 0.037488 " + "Email 0.038395 \n", + "None 0.098546 \n", + "All 0.044322 " ] }, - "execution_count": 20, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -940,7 +941,7 @@ "\n", " Die Frage können wir wie folgt beantworten. \n", " Von allen Nutzern, die per Mail informiert werden möchten, sind\n", - " - ca. 8% in der Alterklasse 0 bis 9 Jahre,\n", + " - ca. 7% in der Alterklasse 0 bis 9 Jahre,\n", " - ca. 14% in der Altersklasse 10 bis 19 Jahre,\n", " \n", " ...\n", @@ -948,14 +949,14 @@ " - ca. 7% in der Altersklasse 65 bis 74 Jahre,\n", " - ca. 4% in der Altersklasse 75 Jahre und älter.\n", "\n", - "Im Vergleich dazu, sind von allen Nutzern, die per Post informiert werden möchten\n", - "- ca. 18% in der Altersklasse 0 bis 9 Jahre,\n", - "- ca. 9% in der Altersklasse 10 bis 19 Jahre,\n", + "Im Vergleich dazu, sind von allen Nutzern, die nicht informiert werden möchten\n", + "- ca. 9% in der Altersklasse 0 bis 9 Jahre,\n", + "- ca. 28% in der Altersklasse 10 bis 19 Jahre,\n", "\n", "...\n", "\n", - "- ca. 10% in der Altersklasse 65 bis 74 Jahre,\n", - "- ca. 8% in der Altersklasse 75 Jahre und älter.\n" + "- ca. 11% in der Altersklasse 65 bis 74 Jahre,\n", + "- ca. 10% in der Altersklasse 75 Jahre und älter.\n" ] }, { @@ -975,7 +976,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -987,7 +988,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1032,98 +1033,98 @@ " \n", " \n", " 0\n", - " 1\n", - " Juvenile\n", - " 0\n", - " 0\n", - " 0 to 9 years\n", - " r3\n", - " Richmond\n", - " NaN\n", + " 5\n", + " Staff\n", + " 53\n", + " 15\n", " NaN\n", + " b2\n", + " Bayview\n", + " Mar\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2022\n", - " True\n", - " NaN\n", - " NaN\n", + " 2003\n", + " False\n", + " 21.0\n", + " 2.523810\n", " \n", " \n", " 1\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " x\n", - " Main\n", - " NaN\n", + " 5\n", + " Staff\n", + " 480\n", + " 378\n", " NaN\n", + " e9\n", + " Excelsior\n", + " Jun\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2022\n", - " True\n", - " NaN\n", - " NaN\n", + " 2003\n", + " False\n", + " 21.0\n", + " 22.857143\n", " \n", " \n", " 2\n", - " 0\n", - " Adult\n", - " 0\n", - " 0\n", - " 35 to 44 years\n", - " m4\n", - " Merced\n", - " NaN\n", - " NaN\n", + " 5\n", + " Staff\n", + " 70\n", + " 33\n", + " 45 to 54 years\n", + " n4\n", + " Noe Valley\n", + " Jan\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2019\n", - " True\n", - " NaN\n", - " NaN\n", + " 2011\n", + " False\n", + " 13.0\n", + " 5.384615\n", " \n", " \n", " 3\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " x\n", - " Main\n", - " NaN\n", + " 5\n", + " Staff\n", + " 3934\n", + " 2140\n", " NaN\n", + " o2\n", + " Ocean View\n", + " Jul\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2021\n", - " True\n", - " NaN\n", - " NaN\n", + " 2003\n", + " False\n", + " 21.0\n", + " 187.333333\n", " \n", " \n", " 4\n", - " 2\n", - " Teen\n", - " 0\n", - " 0\n", - " 10 to 19 years\n", - " b2\n", - " Bayview\n", - " NaN\n", + " 5\n", + " Staff\n", + " 1118\n", + " 1035\n", " NaN\n", + " o7\n", + " Ortega\n", + " Jul\n", + " 2023.0\n", " z\n", " Email\n", " True\n", - " 2013\n", - " True\n", - " NaN\n", - " NaN\n", + " 2003\n", + " False\n", + " 21.0\n", + " 53.238095\n", " \n", " \n", "\n", @@ -1131,25 +1132,25 @@ ], "text/plain": [ " Patron Type Code Patron Type Definition Total Checkouts Total Renewals \\\n", - "0 1 Juvenile 0 0 \n", - "1 2 Teen 0 0 \n", - "2 0 Adult 0 0 \n", - "3 2 Teen 0 0 \n", - "4 2 Teen 0 0 \n", + "0 5 Staff 53 15 \n", + "1 5 Staff 480 378 \n", + "2 5 Staff 70 33 \n", + "3 5 Staff 3934 2140 \n", + "4 5 Staff 1118 1035 \n", "\n", " Age Range Home Library Code Home Library Definition \\\n", - "0 0 to 9 years r3 Richmond \n", - "1 10 to 19 years x Main \n", - "2 35 to 44 years m4 Merced \n", - "3 10 to 19 years x Main \n", - "4 10 to 19 years b2 Bayview \n", + "0 NaN b2 Bayview \n", + "1 NaN e9 Excelsior \n", + "2 45 to 54 years n4 Noe Valley \n", + "3 NaN o2 Ocean View \n", + "4 NaN o7 Ortega \n", "\n", " Circulation Active Month Circulation Active Year Notice Preference Code \\\n", - "0 NaN NaN z \n", - "1 NaN NaN z \n", - "2 NaN NaN z \n", - "3 NaN NaN z \n", - "4 NaN NaN z \n", + "0 Mar 2023.0 z \n", + "1 Jun 2023.0 z \n", + "2 Jan 2023.0 z \n", + "3 Jul 2023.0 z \n", + "4 Jul 2023.0 z \n", "\n", " Notice Preference Definition Provided Email Address \\\n", "0 Email True \n", @@ -1158,22 +1159,22 @@ "3 Email True \n", "4 Email True \n", "\n", - " Year Patron Registered Within San Francisco County \\\n", - "0 2022 True \n", - "1 2022 True \n", - "2 2019 True \n", - "3 2021 True \n", - "4 2013 True \n", + " Year Patron Registered Within San Francisco County \\\n", + "0 2003 False \n", + "1 2003 False \n", + "2 2011 False \n", + "3 2003 False \n", + "4 2003 False \n", "\n", " Membership Duration Years Average Checkouts per Year \n", - "0 NaN NaN \n", - "1 NaN NaN \n", - "2 NaN NaN \n", - "3 NaN NaN \n", - "4 NaN NaN " + "0 21.0 2.523810 \n", + "1 21.0 22.857143 \n", + "2 13.0 5.384615 \n", + "3 21.0 187.333333 \n", + "4 21.0 53.238095 " ] }, - "execution_count": 22, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1184,12 +1185,12 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ "
" ] @@ -1241,7 +1242,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -1253,7 +1254,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -1261,11 +1262,11 @@ "output_type": "stream", "text": [ "Im Mittel werden in den Altersgruppen wie folgt Verlängerungen getätigt:\n", - "0 bis 9-jährige: 20.315836426333597\n", - "10 bis 19-jährige: 22.88212931062654\n", + "0 bis 9-jährige: 20.67787896079863\n", + "10 bis 19-jährige: 22.311279378051168\n", "...\n", - "65 bis 74-jährige: 22.535718393031114\n", - "ab 75-jährige: 25.460337634193355\n" + "65 bis 74-jährige: 22.143589378726553\n", + "ab 75-jährige: 25.564645418763174\n" ] } ], @@ -1319,7 +1320,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -1328,22 +1329,22 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 27, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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DV9hnZWMAAAAAAEBZl2QBAAAAAIC1hcAcAAAAAAAiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCT1DMxHjRqVWbNmLXfb22+/nWHDhn2sSQEAAAAAQEOrV2B+3nnnZerUqcvdNn78+AwdOvRjTQoAAAAAABpao1XtePzxx2fixIlJkqIocvLJJ6dx48Z1+s2YMSNbbbXVmpshAAAAAAA0gNUKzH/7298mSX73u9+lbdu22XTTTWv1qaysTPPmzXPIIYes2VkCAAAAAMAnbJUD85122ik77bRT6euTTjopX/rSlz6RSQEAAAAAQENb5cD8wy6//PI1PQ8AAAAAACiregXmM2fOzKWXXprHHnssCxYsSFEUtbZXVFRk3Lhxa2SCAAAAAADQEOoVmF988cV5/PHHc8ABB6RVq1aprKxc0/MCAAAAAIAGVa/A/C9/+UvOP//8HHrooWt6PgAAAAAAUBb1ujW8cePGHvgJAAAAAMCnSr0C8969e+f+++9f03MBAAAAAICyqdeSLG3bts3VV1+dqVOnpmPHjmnSpEmt7RUVFTn55JPXyAQBAAAAAKAh1Csw/8lPfpIkGTNmTMaMGVNnu8AcAAAAAIB1Tb0C8wkTJqzpeQAAAOuwysqKVFZWlHsa1FNNTZGamqLc0wAAKLt6BeYAAADLVFZWpMUmG6SyqqrcU6GeapYuzazZC4TmAMBnXr0C8/POO2+lfS6//PL6DA0AAKxjKisrUllVlQdHDM/M6W+Wezqspk033zL7H/q9VFZWCMwBgM+8egXmo0ePrtM2f/78zJ49O5tssknat2//sScGAACsW2ZOfzPT35ha7mkAAEC91Ssw//Of/7zc9pdffjkDBgzIwQcf/HHmBAAAAAAADa5yTQ627bbb5uSTT8511123JocFAAAAAIBP3BoNzJNko402yuuvv76mhwUAAAAAgE9UvZZkeeONN+q0LV26NNOmTcvVV1+d7bbb7mNPDAAAAAAAGlK9AvNevXqloqKiTntRFNlggw1y7bXXfuyJAQAAAABAQ6pXYH7ZZZfVCcwrKiqy0UYbpXv37tloo43WyOQAAAAAAKCh1CswP+SQQ9b0PAAAAAAAoKzqFZgnycyZM3Prrbdm9OjRmTt3blq0aJEuXbrk6KOPTsuWLdfkHAEAAAAA4BNXWZ+dpk2blj59+uS2227L+uuvn7Zt26ZRo0a59dZbc/DBB+ett95a0/MEAAAAAIBPVL3uML/yyivTqFGjPPjgg/nSl75Uap86dWr69++fIUOG5IorrlhjkwQAAAAAgE9ave4wf/LJJ3PqqafWCsuT5Etf+lJOPvnkPPHEE2tkcgAAAAAA0FDqFZgvXbo0LVq0WO62TTfdNPPmzftYkwIAAAAAgIZWr8C8devW+f3vf7/cbaNGjUp1dfXHmhQAAAAAADS0eq1hftJJJ+V73/teZs+ena9//ev53Oc+l3feeSd/+MMf8te//jVDhw5d0/MEAAAAAIBPVL0C89133z0///nP8/Of/zxPPfVUqX2zzTbL5Zdfnt69e6+xCQIAAAAAQEOoV2CeJK+//npat26d22+/PXPmzMmECRNyzTXXZPbs2WtwegAAAAAA0DDqFZjffPPNue6663LkkUdmu+22S5J8/vOfz6uvvpqrrroqG2ywQQ499NA1OlEAAAAAAPgk1Sswv/vuu3P66afn2GOPLbW1atUq5557bjbddNP86le/EpgDAAAAALBOqazPTm+99VZ23HHH5W5r3759XnvttY81KQAAAAAAaGj1Csy/9KUv5a9//etyt40ePTqtWrX6WJMCAAAAAICGVq8lWQ4//PBcdtllWbJkSfbZZ5+0bNkyM2fOzCOPPJJf/epXOeuss9b0PAEAAAAA4BNVr8D8iCOOyLRp03LrrbfmtttuK7VXVVXlqKOOytFHH72GpgcAAAAAAA2jXoF5kpx55pn5/ve/n2effTazZ89O8+bN06FDh7Ro0WJNzg8AAAAAABpEvdYwX6ZZs2bp0aNHvv71r2fPPfesV1g+e/bsXHTRRfnqV7+anXbaKYcffnjGjh1b2j5+/Pj069cvnTp1Ss+ePTN8+PBa+9fU1GTo0KHp0aNHOnbsmP79+2fKlCm1+qxsDAAAAAAA+FiB+Zpwxhln5LnnnsvgwYNzzz33ZMcdd8z3vve9TJo0KbNmzcoxxxyTL3/5yxk5cmQGDBiQa665JiNHjiztf/311+euu+7KT3/604wYMSIVFRU57rjjsnjx4iRZpTEAAAAAAKDeS7KsCVOmTMlTTz2V3/zmN9lpp52SJBdccEGeeOKJ3H///WnSpEkaN26ciy++OI0aNcp2222XKVOmZNiwYenbt28WL16cW265JQMHDsyee+6ZJBkyZEh69OiRhx9+OAcccEDuvvvujxwDAAAAAACSMt9h3qJFi9x0001p165dqa2ioiJFUWTOnDkZO3ZsunbtmkaN/i/X7969eyZPnpwZM2ZkwoQJee+999K9e/fS9ubNm6dt27YZM2ZMkqx0DAAAAAAASMp8h3nz5s1Ld4Yv88c//jGvvvpq9thjjwwZMiTV1dW1tm+++eZJkjfeeCPTpk1Lkmy55ZZ1+rz55ptJkmnTpn3kGC1btqz3/Bs1KvuKNnxKVVWprU8Dx5G1kbpc9zXUMVQrnw7qhdXhOAIAlDkw/2//+Mc/cv7552fvvfdOr169cvnll6dx48a1+qy//vpJkkWLFmXBggVJstw+c+bMSZIsXLjwI8eor8rKirRosWG99wc+/Zo336DcUwA+hZxbWB3qhdWhXgAA1qLA/JFHHslZZ52Vjh07ZvDgwUmSJk2alB7eucyykLtp06Zp0qRJkmTx4sWlvy/rs8EGG6zSGPVVU1Nk7tz59d4fPkpVVaVfWD4F5s5dkKVLa8o9DajF+WXd11DnFrXy6aBeWB2uXQCAT7NVvfl5rQjM77jjjlx66aXp3bt3Bg0aVLojvFWrVpk+fXqtvsu+3mKLLbJkyZJS21ZbbVWrT5s2bVZpjI9jyRIXk8CKLV1a4zwBrHHOLawO9cLqUC8AAGV+6GeS/PrXv84ll1ySI444IldffXWt5VO6du2af/zjH1m6dGmp7emnn84222yTli1bpk2bNtloo40yevTo0va5c+dm3Lhx6dKlyyqNAQAAAAAASZkD88mTJ+eyyy5L7969c/zxx2fGjBl5++238/bbb+fdd99N3759M2/evFxwwQWZOHFi7r333tx+++05/vjjk3ywdnm/fv0yaNCgPProo5kwYUJOP/30tGrVKr17906SlY4BAAAAAABJmZdk+dOf/pT3338/Dz/8cB5++OFa2/r06ZMrrrgiN998cy699NL06dMnm222Wc4+++z06dOn1O/UU0/NkiVLcuGFF2bhwoXp2rVrhg8fXrpTvWXLlisdAwAAAAAAyhqYn3DCCTnhhBM+sk+HDh0yYsSIFW6vqqrKwIEDM3DgwHqPAQAAAAAAZV/DHAAAAAAA1gYCcwAAAAAAiMAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSJI3KPYHPmsrKilRWVpR7GtRDTU2Rmpqi3NMAAAAAAD4hAvMGVFlZkU02aZqqKjf2r4uWLq3J7NnzheYAAAAA8CklMG9AlZUVqaqqzC9+81Renz6n3NNhNXxh841z8uG7p7KyQmAOAAAAAJ9SAvMyeH36nLzy+qxyTwMAAAAAgA9Zq9YGuf766/Pd7363Vtv48ePTr1+/dOrUKT179szw4cNrba+pqcnQoUPTo0ePdOzYMf3798+UKVNWawwAAAAAAFhrAvPbbrstQ4cOrdU2a9asHHPMMfnyl7+ckSNHZsCAAbnmmmsycuTIUp/rr78+d911V376059mxIgRqaioyHHHHZfFixev8hgAAAAAAFD2JVneeuutXHDBBfnHP/6RbbbZpta2u+++O40bN87FF1+cRo0aZbvttsuUKVMybNiw9O3bN4sXL84tt9ySgQMHZs8990ySDBkyJD169MjDDz+cAw44YKVjAAAAAABAshbcYf7CCy9k4403zn333ZeOHTvW2jZ27Nh07do1jRr9X67fvXv3TJ48OTNmzMiECRPy3nvvpXv37qXtzZs3T9u2bTNmzJhVGgMAAAAAAJK14A7zXr16pVevXsvdNm3atFRXV9dq23zzzZMkb7zxRqZNm5Yk2XLLLev0efPNN1dpjJYtW9Z77o0ard7/N1RVlf3/J/iYGuoYqpVPB8eRtZG6XPf5WcTqUC+sDscRAGAtCMw/ysKFC9O4ceNabeuvv36SZNGiRVmwYEGSLLfPnDlzVmmM+qqsrEiLFhvWe3/WTc2bb1DuKbAOUS/AJ8G5hdWhXlgd6gUAYC0PzJs0aVJ6eOcyy0Lupk2bpkmTJkmSxYsXl/6+rM8GG2ywSmPUV01Nkblz56/WPlVVlS5C13Fz5y7I0qU1n/jrqJVPh4aqF1gdzi/rPj+LWB3qhdXh2gUA+DRb1Zuf1+rAvFWrVpk+fXqttmVfb7HFFlmyZEmpbauttqrVp02bNqs0xsexZImLyc+apUtrHHdWmXoBPgnOLawO9cLqUC8AAGt5YN61a9fcddddWbp0aaqqqpIkTz/9dLbZZpu0bNkyzZo1y0YbbZTRo0eXAvO5c+dm3Lhx6dev3yqNAfBpUFlZkcrKinJPg3qqqSlSU1OUexoAAADwmbdWB+Z9+/bNzTffnAsuuCDHHntsnn/++dx+++358Y9/nOSDtcv79euXQYMGZdNNN80XvvCFXHnllWnVqlV69+69SmMArOsqKyuySYsNUlVZVe6pUE9La5Zm9qwFQnMAAAAos7U6MG/ZsmVuvvnmXHrppenTp08222yznH322enTp0+pz6mnnpolS5bkwgsvzMKFC9O1a9cMHz689KDPVRkDYF1WWVmRqsqq3Pj4r/LGnLfKPR1W0+c33iLH73lkKisrBOYAAABQZmtVYH7FFVfUaevQoUNGjBixwn2qqqoycODADBw4cIV9VjYGwKfBG3PeypQZr5V7GgAAAGVhqcp1l2UqWZusVYE5AAAAAKyuysqKtGjRNJWVleWeCvVQU1OTWbPmC81ZKwjMAQAAAFinfXB3eWUm/HNk5r/7Trmnw2po2uxzadO5r2UqWWsIzAEAAAD4VJj/7juZN/fNck8DWIf5nAoAAAAAAERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASZJG5Z4AAAAAnx2VlRWprKwo9zSop5qaIjU1RbmnAQCfGIE5AAAADaKysiItWjRNZaUPO6+rampqMmvWfKE5AJ9aAnMAAAAaxAd3l1dmysPjsmjW/HJPh9W0foum2bp321RWVgjMAfjUEpgDAADQoBbNmp8F78wr9zQAAOrwOTgAAAAAAIjAHAAAAAAAkgjMAQAAAAAgicAcAAAAAACSCMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIEnSqNwTAAAAAFieysqKVFZWlHsa1FNNTZGamqLc0wBYLQJzAAAAYK1TWVmRFi2aprLSh+PXVTU1NZk1a77QHFinCMwBAACAtc4Hd5dX5oEHHsjMmTPLPR1W06abbpoDDjgglZUVAnNgnSIwBwAAANZaM2fOzPTp08s9DQA+I3yuCQAAAAAAIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASCIwBwAAAACAJAJzAAAAAABIIjAHAAAAAIAkAnMAAAAAAEgiMAcAAAAAgCQCcwAAAAAASJI0KvcEAAAAAAAaSmVlRSorK8o9DeqppqZITU3xiY0vMAcAAAAAPhMqKyuySYumqaq08Ma6amlNTWbPmv+JheYCcwAAAADgM6GysiJVlZW5Y8z4vPXu/HJPh9W0RbOm6dd1h1RWVgjMAQAAAADWhLfenZ/X58wr9zRYC/nsAQAAAAAARGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJBOYAAAAAAJBEYA4AAAAAAEkE5gAAAAAAkERgDgAAAAAASQTmAAAAAACQRGAOAAAAAABJPkOBeU1NTYYOHZoePXqkY8eO6d+/f6ZMmVLuaQEAAAAAsJb4zATm119/fe6666789Kc/zYgRI1JRUZHjjjsuixcvLvfUAAAAAABYC3wmAvPFixfnlltuyYABA7LnnnumTZs2GTJkSN566608/PDD5Z4eAAAAAABrgc9EYD5hwoS899576d69e6mtefPmadu2bcaMGVPGmQEAAAAAsLaoKIqiKPckPmkPPfRQBgwYkOeeey5NmjQptf/gBz/IwoULc+ONN672mEVRpKZm9d66ioqksrIyc+YtzNKlNav9mpRPVVVlNt6oSWpqatIQ/2KW1cr7781NUbP0k39B1qiKyqqst2HzBq+XuQvezRL1ss5pVFmV5hs0a/B6WTR3bool6mVdUtGoKus3b/hzy3uuW9ZJVVWV2bAM1y7z583N0qXOLeuaqqqqNN2oYc4vpevc+YtTrObvU5RfRWVF1mvauOHPLfPnO7esg6qqqtK0adMGr5fFi97ze/Q6pqKyKo3X37DBa+XdhYuz9NMfi37qVFVUpFmT+v0sqqpatXvHG9VjXuucBQsWJEkaN25cq3399dfPnDlz6jVmRUVFqqoq6rXvxhs1WXkn1kqVlQ37oYz1NmzeoK/HmtXQ9dJ8g2YN+nqsWQ1dL+s3d35ZVzV0rWzoumWd1tD10nQj55Z1WUPWy3pNG6+8E2utBj+3NG3aoK/HmtXQ9dJ4/Q0b9PVYcxq6Vpo18bNoXfZJ1stnYkmWZXeV//cDPhctWpQNNtigHFMCAAAAAGAt85kIzLfccsskyfTp02u1T58+Pa1atSrHlAAAAAAAWMt8JgLzNm3aZKONNsro0aNLbXPnzs24cePSpUuXMs4MAAAAAIC1xWdiDfPGjRunX79+GTRoUDbddNN84QtfyJVXXplWrVqld+/e5Z4eAAAAAABrgc9EYJ4kp556apYsWZILL7wwCxcuTNeuXTN8+PA6DwIFAAAAAOCzqaIoiqLckwAAAAAAgHL7TKxhDgAAAAAAKyMwBwAAAACACMwBAAAAACCJwBwAAAAAAJIIzAEAAAAAIInAHAAAAAAAkgjM10k1NTUZOnRoevTokY4dO6Z///6ZMmXKR+7zj3/8I2PHjv1Yr/vCCy/kyCOPzE477ZSePXvm2muvzdKlSz/WmKw5119/fb773e/WaR8/fnz69euXTp06pWfPnhk+fPhHjjN//vzceeeda2xev//979OrV6867eqpYc2ePTsXXXRRvvrVr2annXbK4YcfXuecUI5aWbhwYa666qr06tUrnTt3ziGHHJJHH310hf1vuOGGtG7d+mO9Jiu3KvVy3nnnpXXr1rX+fPWrX13hmGuiXubPn59LLrkke+yxRzp27JgjjjgizzzzzAr7q5eGMWPGjAwcODDdu3dP586d8/3vfz8TJ06s1acc9fJhM2fOzB577JFrr712hX3US8OaPHlyOnfunHvvvbdWezlq5f3330+7du3qvO6QIUOW21+tNIzXX3+9zjFp3bp1fvvb35b6rK314jq34Y0aNSr7779/2rdvnwMOOCB//OMfa20v1+9Ejz/+eA455JC0b98+++yzz0eO6dzScFZWLw19bnnttdeWe75r3bp12rRps9x91MvqGT169Arf47333rvUb3WP/Wdd69at61zLfWoUrHOuvfbaYtdddy0ee+yxYvz48UX//v2L3r17F4sWLVrhPtXV1cXIkSPr/Zqvvvpq0bFjx+Kkk04qJkyYUIwePbr42te+VlxwwQX1HpM159Zbby1at25d9OvXr1b7zJkzi27duhUXXHBBMXHixOKee+4p2rdvX9xzzz0rHOvaa68t9tprrzUyrwceeKDYcccd64ynnhreMcccUxx00EHFmDFjikmTJhWXXHJJ0aFDh2LixIlFUZSvVi644IKiZ8+exRNPPFG88sorxS9/+cuiTZs2xd/+9rc6fZ977rmibdu2RXV19cd6TVZuZfVSFEXRp0+fYvDgwcX06dNLf2bMmLHCMddEvZx22mnF1772tWLMmDHFK6+8Uvz4xz8uOnbsWEybNq1OX/XScL71rW8Vhx56aPH8888XEydOLAYMGFDsvvvuxfz580t9ylEvH3bSSScV1dXVxdChQ5e7Xb00rMWLFxeHHHLIcq9Py1ErEyZMKKqrq4vx48fXet158+bV6atWGs6jjz5atG/fvnjrrbdqHZcFCxaU+qyN9eI6t+GNGjWq2GGHHYrbbruteOWVV4rrrruuaNOmTfHMM88URVG+69zRo0cXO+ywQ3HVVVcVU6ZMKe66665ihx12KB544IE6fZ1bGs7K6qUoGv7csmTJklqvNX369OKFF14oOnfuXAwePLhOf/Wy+hYtWlTnPX7yySeLtm3bFnfffXep3+oe+8+6j5s1rs3cYb6OWbx4cW655ZYMGDAge+65Z9q0aZMhQ4bkrbfeysMPP/yJve4dd9yRTTbZJEOGDEnr1q2zyy675NJLL80999yTN9544xN7XT7aW2+9lWOPPTbXXHNNttlmmzrb77777jRu3DgXX3xxtttuu/Tt2zdHH310hg0btsIxi6L42POaN29ezjrrrAwcODDbbbddne3qqWFNmTIlTz31VH70ox+lS5cu2XbbbXPBBRdkiy22yP3335+kPLWyYMGCjBo1KmeccUZ69OiRrbfeOscff3y6deuWkSNH1uo7f/78DBw4MF26dPlYr8nKrUq9LF26NBMnTkz79u2z2Wablf5suummKxz349bLkiVL0qRJk9K8tt5665x++ulZsGBBnbvM1UvDmTVrVr74xS/mkksuSfv27bPddtvlpJNOyttvv52XXnopSXnq5cNGjBiRyZMnZ7PNNlvudvXS8K699tpsuOGGddrLVSsvvvhimjVrljZt2tR63f+eo1ppWC+++GK22WabbL755rWOS5MmTZKsvfXiOrdhFUWRa665JkcddVSOOuqobL311jn55JOz22675e9//3uS8v1OdO2112afffbJGWecka222iqHHnpoDj744Dqf2nNuaTirUi/lOLdUVVXVeq3NNtssV111Vaqrq/ODH/ygVl/1Uj+NGzeu9f5usskmufzyy7PvvvvmW9/6VpL6HXs+vQTm65gJEybkvffeS/fu3UttzZs3T9u2bTNmzJjl7rPsYzrnnXdezj333CTJm2++mbPOOiu77757OnXqlO9973v5z3/+s8LXnTx5cjp06JDGjRuX2tq2bZuiKJb7uhMmTEjr1q3rbDv99NNzyimnJEnefffd/PCHP0z37t2z884758gjj8y//vWvUt+iKHLzzTdnv/32S7t27bLzzjvn+OOPz9SpU2t9b0OGDMlee+2V3XffPS+//HKef/75fOc730nnzp3TtWvXDBgw4FN7cfrCCy9k4403zn333ZeOHTvW2T527Nh07do1jRo1KrV17949kydPzowZM+r0v/baa3PdddeVPgL72muvJfngI2sHHXRQOnTokF69euWXv/xlampqVjiv1157LXPmzMk999yTffbZp8529dSwWrRokZtuuint2rUrtVVUVKQoisyZMydJeWqloqIiv/zlL9OjR48625bNa5lLL7001dXV+cY3vvGR36ta+fhWpV5eeeWVLFq0aLn/IbY8a6JeGjVqlMsvvzy77rprkmTu3Lm5/vrrs+GGG6ZTp061+qqXhtOiRYsMHjw422+/fZLknXfeyfDhw9OqVat85StfSVKeellm8uTJGTRoUK688spaP3M+TL00rDFjxmTEiBH52c9+VmdbuWrlP//5T6leP4paaVgrOy5ra724zm1YL7/8cl5//fV8/etfr9U+fPjwHH/88UnKc527YMGCjB07ts68Lrvsslx00UW12pxbGs6q1Es5r1uWeeSRR/L000/n4osvTmVl7dhOvawZd955Z958882cd955pbbVPfaPPPJI2rRpk9dff71W+7e//e1cfvnlST64yfH0009Ply5d0q1bt5xwwgl55ZVXSn0XL16cq666Kvvss0/atWuXbt265YwzzsisWbOS/N9yPddff31233339OrVK3Pnzi0t99SxY8fsuuuuOffcc+v8Dv1hL730Uk466aR069Yt7dq1S+/evXP77beXtl977bX57ne/m2HDhuWrX/1q2rdvnyOPPDIvv/xyqc+0adNy4oknpnPnzunZs2ceeOCBlb5HkyZNygknnJBu3bpl5513zqmnnlqqhXvvvTft27fP3Llza+3zta99LVdfffUqvX/nnntuTjnllPTv3z877bRTbrzxxpXOaZU13M3srAl/+tOfiurq6lofRSyKojj11FOL73//+8vdZ/r06UV1dXVx2223FXPnzi3efffdYs899yz69etXPPfcc8X48eOLU045pejSpUvx+uuvL3eM888/v/jmN79Zq+2ll14qqquri+HDhy93n4MPPrg4//zzS1/PnTu3aN++ffHoo48WNTU1xaGHHlr069evePbZZ4uJEycWV111VbHjjjsWL7zwQlEUHywz0qVLl+LRRx8tXnvtteJvf/tb0bt37+Kkk04qjVldXV1069ateP7554t//vOfxdKlS4vu3bsXgwcPLl599dXi3//+d3HIIYcURx111Erf23XdOeecU2dJlgMPPLD4+c9/Xqtt2XF7/vnn64wxb9684oorrii++tWvFtOnTy+WLFlS3HrrrUW7du2KO+64o5g8eXJx3333FV26dCkuv/zyVZrX0KFD63w8TT2V34MPPlhUV1cXjz76aFEUa0etFEVRPPvss0Xr1q2LX/3qV6W2hx56qNh9992LmTNnFiNHjlzpRw/Vypr33/Xy4IMPFq1bty5+9KMfFXvttVex9957Fz/5yU+KuXPnLnf/NV0vN9xwQ1FdXV20bt26zsep1Uv5XHjhhUV1dXXRrl274i9/+UupvVz1snjx4qJPnz7FDTfcUBRFUey11151lmRRLw1rzpw5Rc+ePYv77ruvKIq6H+MtV60cd9xxRd++fYv+/fsXu+66a9GnT59i1KhRtfqolYa3//77F0cddVRx+OGHF7vuumtx2GGHFU888URp+9paL65zG9YjjzxSVFdXF2PGjCn69+9fdO/evfjmN79ZumYpivJc544fP7507TRgwICie/fuxUEHHVRr6YeicG5paKtSL+W+zi2KD2r27LPPrtOuXtaMhQsXFt26dSuuueaaWu2re+zff//9Yrfddit+8YtflNpefvnl0rJd7733XtG7d+9iwIABxfjx44v//Oc/xbnnnlt07dq1tKTkJZdcUvTs2bP429/+Vrz22mvF//7v/xa77LJLcemllxZFURRTp04tqquri6997WvFSy+9VDz//PPFjBkzSvX12muvFWPHji169epV61h/2Pz584vdd9+9OPPMM4uJEycWr7zySnHVVVcV1dXVxbhx44qi+CC32XHHHYvjjjuuGD9+fDF27Nhi7733Lo488sjS93rAAQcUhx56aPHvf/+7eOaZZ4pvfOMbH7kky2uvvVbsvPPOpe//ueeeK77zne8Ue+21V/Huu+8W7733XtGpU6da58Vnn322qK6uLiZPnrxK798555xTVFdXF8OGDStefvnl4o033ljp8V9VAvN1zKhRo4rq6upi6dKltdoHDhz4kSegDxfxnXfeWXTo0KHWOkwLFy4s9thjjzoXEsuMGTOmaN26dXHjjTcWCxcuLN56663iyCOPLNq2bVv6RfS//b//9/+KnXfeuVi4cGFRFEUxYsSIYrfddivef//94q9//WtRXV1dZy2oI444ojjnnHOKovhg3cJHHnmk1vbBgwcXe++9d63v67LLLit9PXv27KJ169bFHXfcUdTU1BRF8cE6gv/85z9X+N58WiwvMN9nn32Kq6++ulbbq6++WrpIWJ4PB9w1NTXFbrvtVlxxxRW1+vzqV78qdtxxxxX+4FjReMuop/IaO3Zs0alTp+LEE08sta0NtTJp0qRi9913L/r27Vt6JsO0adOKbt26FY8//nhRFMUqXRiqlTVrefVyzTXXFDvssENx0003Ff/5z3+Khx56qNh7772Lfv361fn5tMyarJdXXnmlGDduXDF48OCiTZs2xZ///OeiKNRLub300kvFv/71r+L8888vOnToUPz73/8uiqJ89TJo0KDisMMOK5YsWVIURd3AXL00vNNPP7047bTTSl//9y9Z5aqVnj17Fvvss0/x+OOPF+PGjSuuv/76Yocddih++9vfFkWhVsph0aJFRdu2bYu+ffsWo0ePLv71r38Vl156adG6devir3/9a1EUa2+9uM5tWMt+P+7Vq1dx7733FuPGjSuGDBlSq1bKcZ07ZsyYorq6uth9992L22+/vRg3blxx6623FjvuuKNzSxmtSr2U+zr3ySefLFq3bl3r2UFFoV7WpBEjRhSdOnUqZs6cWau9Psf+iiuuKPbdd9/S14MHDy769OlTFEVR3H333UWXLl2KxYsXl7YvXbq01jXpqFGjitGjR9ca84wzzigF1csC89tvv720fdy4cUV1dXXpd6CiKIoXX3yxGD9+/HLnOGPGjOLGG28s3n333VLbokWLiurq6uJ3v/tdURQf1HDr1q2LWbNmlfrcdtttxY477lgURVE88cQTRXV1dTFlypQ681hRYP7zn/+86NGjR63nLb7zzjtFhw4dijvvvLMoiqI499xza+VYP/nJT4rDDjtsld+/c845p+jatetyX//jarTye9BZmyxbs2/x4sWlvyfJokWLssEGG6zSGC+++GK+/OUv11qHaf3110+HDh1WuCxLly5dctlll+VnP/tZhgwZkg033DCnnnpqJk2alGbNmi13n69//ev52c9+lkcffTT7779/fve73+Wggw5Ko0aN8sILLyRJracRL/u+Fi1alCTp1atXnnvuuQwdOjRTpkzJpEmT8tJLL2WLLbaotc/WW29d+vvGG2+cY489Npdcckmuu+667LbbbvnqV7+ar33ta6v03nzaNGnSJIsXL67Vtuz9bdq06Ur3nzlzZt55553svPPOtdq7du2a999/Py+//PJyl4JZGfVUPo888kjOOuusdOzYMYMHDy61l7tWnnnmmZx00knZbLPNctNNN6Vx48YpiiLnnntu9ttvv9V6MrlaWXNWVC8DBgzI0UcfnebNmydJqqurs9lmm+XQQw/Nv/71r5WeFz5uvSx773fYYYe88MILufXWW9OzZ0/1UmbLlii45JJL8uyzz+aOO+7I5ZdfXpZ6+fvf/57f/OY3+d3vfpeqqqo6Yzq/NLxRo0Zl7Nix+cMf/rDCPuU6t/zP//xPampqStfSO+ywQ958880MHz48ffv2VStl0Lhx44wZMyaNGjUqLW3Srl27TJo0KcOHD8+uu+66VtbLN7/5Tde5DWy99dZLknzve99Lnz59knxwTMaNG5dbb701u+66a1muc5fV7Te+8Y0ceeSRpXlNmTIlt956q3NLmaxKvZT7OnfUqFHp0qVLrWVBXLesWaNGjcq+++6bFi1a1Gqvz7Hv27dvbrnlljz33HPp0KFD7rvvvhx77LFJknHjxmXevHnZZZddau2zaNGiTJo0KckH54inn346gwcPziuvvJJJkybl5ZdfrrNG/Yff4x122CEHHnhgTjjhhGy55ZbZbbfd0rNnz/Tq1Wu53++mm26a73znO3nwwQczYcKETJkyJePHj0+SWssEfe5zn8smm2xS+rpZs2Z5//33k3yQI2688cbZaqutas3jo3LIF198Me3atau1RFnLli2zzTbblLLHPn365Mgjj8y0adPyuc99Lg8++GBOP/30VX7//vu9WZME5uuYLbfcMkkyffr0WoU6ffr0tGnTZpXGKIoiFRUVddqXLl1aa123/3bIIYekT58+mT59elq0aJElS5bksssuW2Fxbrzxxtlnn31y3333pX379vnnP/+Zn/zkJ0k++Ee50UYb5d57762z37J/TMOGDcu1116bQw45JLvssku++93v5tFHH62zTtKH/+MgSc4666x85zvfyeOPP15a9+vGG2/MqFGjVrh+6adVq1atMn369Fpty77+7x9yy1Os4OElS5cuTZKPrJeVUU8N74477sill16a3r17Z9CgQbXmX85aefjhh3PmmWemffv2ueGGG0oXKG+88Ub++te/5plnnsmoUaOSfPDgxyTp3Llzjj/++Jxwwgl1xlMra8ZH1UtFRUXpOC1TXV2d5IO17Vb2i0R96mXevHl58skns9tuu9V67e233z5//vOf1UuZzJgxI08//XT222+/UjBdWVmZ7bbbrnQOKUe9/O53v8v8+fNz0EEHldoWLFiQG2+8Mbfcckvuv/9+9dLARo4cmRkzZqRnz5612n/0ox9l+PDheeCBB8pSK8kHN478t9atW+cPf/iDc0sZLS/IrK6uzpNPPpmkPOeW5KPrZRnXuQ2nVatWSf7v2C/zla98JY899lipT0Nf5y4bd3nzuvfee51bymRV6qVc55bkgxp47LHHSoHhMuplzZk5c2b++c9/ltas/7D6HPuvfOUr6dixY+67774sXLgw77zzTg444IAkH7zH22yzTW644YY6+y37GXfxxRfnwQcfzMEHH5yePXvmxBNPzPDhw/PWW2/V6v/f7/FVV12Vk08+OU888UT++te/5owzzshOO+2UX/3qV3Ve65133sm3v/3ttGjRInvvvXd23XXXtG/fPnvuuWetfis7Nsur7Y+q54/KHpf951XXrl3zxS9+Mffff3+22267zJ8/P/vtt1+SVXv/krrvzZrioZ/rmDZt2mSjjTbK6NGjS21z587NuHHjVvkpydXV1XUecLJo0aL8+9//XuEDbP70pz/l5JNPTkVFRbbYYos0btw4f/rTn9K0adN07tx5ha/Vt2/fPPXUU/n973+f9u3blx4KVl1dnXnz5mXx4sXZeuutS3+GDRuWRx99NElyww035JRTTsnFF1+cQw89NJ06dcorr7zykU+gfvnll/OjH/0oLVu2zOGHH56hQ4fm5ptvzqRJkzJhwoRVen8+Tbp27Zp//OMfpR/OSfL0009nm222ScuWLZe7z4dPaC1btkzLli3zj3/8o1afsWPHZr311qv1nzarQz01vF//+te55JJLcsQRR+Tqq6+u88OwXLXy5z//Oaeddlp69uyZW2+9tdYFyhZbbJGHHnoo9913X0aNGpVRo0bl1FNPTfLBXQGHHXbYCr9ftfLxrKxezjzzzHzve9+r1bbsAUEr+jnycetlyZIlOf300/PQQw/Van/++efzla98Rb2UyfTp03PmmWfm73//e6nt/fffz7hx40p3RpWjXs4666z88Y9/LNXCqFGjsvnmm+ewww7LqFGj1EsZDBo0KA8++GCtY5Ikp556am666aYk5amV2bNnp0uXLvn9739f53W33357tVImEyZMSOfOnTN27Nha7R/+fWVtrJfEdW5Da9u2bTbccMM899xztdpffPHF0jEsx3XuFltska222mqF83JuKY9VqZdynFuWmThxYubOnZvu3bvXalcva84zzzyTioqKOnctJ/U79skH7/FDDz2Uhx56KHvvvXfpLu3q6uq88cYbadasWen9/cIXvpCrrroqY8aMyaxZs/Kb3/wmF198cc4///wccsgh2WGHHfLyyy9/5Hv87LPP5rLLLsu2226bo48+OjfddFMuu+yyjB49erkPMv7DH/6Q2bNn56677spJJ52U3r17lx4Q+lGv82Ft27bN3Llz89JLL5XaJk+enHfffXeF+1RXV+f555+v9Qmfd955J1OmTCn9nlBRUZGDDz44f/rTn/LAAw9kn332KX0aa2Xv3ydNYL6Oady4cfr165dBgwbl0UcfzYQJE3L66aenVatW6d279wr3a9q0aSZNmpRZs2bl61//epo3b57TTjstzz//fCZMmJCBAwdm/vz5OfTQQ5e7//bbb58nnngi119/fV577bX86U9/yiWXXJKTTjopG2644Qpfd7fddsvnPve5DBs2LIccckipvUePHtlhhx1y2mmn5emnn86UKVPys5/9LCNHjiz9w9lyyy3z1FNPZeLEiXn55ZczZMiQPPTQQ3U+Tvdhm2yySe6///5cdNFFmTRpUiZPnpyRI0dm4403zrbbbruyt/dTp2/fvpk3b14uuOCCTJw4Mffee29uv/325f5v6jJNmzbNnDlzMnny5CxZsiT9+/fPHXfckTvvvDNTpkzJH/7wh1x33XU59NBDV/ix0pVRTw1r8uTJueyyy9K7d+8cf/zxmTFjRt5+++28/fbbpR9w5aiVOXPm5JxzzsmOO+6YCy64IHPmzCnNa/bs2WnUqFGti7ett9669EvN1ltvXevjYv9NrdTfqtTLgQcemKeeeio33HBDXn311Tz++OM5//zzc+CBB67wqfIft1422WSTfOtb38qQIUPy+OOP5+WXX85ll12W5557LieeeKJ6KZM2bdpkjz32yI9//OOMHTs2L774Ys4555zMnTs3Rx99dJLy1EvLli3r1EOjRo2y8cYbl/6uXhrWFltsUec9Tz44Vl/4wheSlO/csttuu2Xw4MH5y1/+kldeeSU33XRT7rvvvgwYMECtlEl1dXW233770rll0qRJufzyy/Pss8+W7qJcG+slcZ3b0Jo0aZJjjz02v/jFL3L//ffn1VdfzQ033JCnnnoqxxxzTJLy/U50yimnZMSIEbnzzjszderUjBgxIiNHjsz3vvc955YyWZV6Kce5ZZkJEyakcePG2WabbWq1q5c1Z8KECfnSl7603KVE6nPsk+SAAw7Iu+++m3vuuafWe3zQQQdl4403zimnnJJnn302kyZNynnnnZfHH38822+/fZo1a5ZmzZrl0UcfzZQpU/Kf//wnP/zhD/PCCy985Hu80UYb5de//nWuvPLK0n4PPPBAvvzlL9dZZib54JMVCxYsyB//+Me88cYbefLJJ3PGGWckyUe+zod169YtHTt2zNlnn51nn302//rXv3LuueemsnLFsfLhhx+eefPm5ayzzsqECRPy/PPP5wc/+EFatGhRugs/+WBZlhdeeCGPPvpoaamkVXn/PnGfyMrofKKWLFlS/PznPy+6d+9edOrUqTjuuOOKqVOnfuQ+Q4cOLTp06FCccMIJRVF88MC0E088sejcuXPRuXPn4thjjy0mTJjwkWM89thjxde//vWiQ4cOxb777lvccccdqzTfwYMHF+3bty/mzJlTq33GjBnFueeeW3Tr1q3o0KFD0adPn+Lhhx8ubf/3v/9dfPvb3y46dOhQ7LrrrsUJJ5xQ/OY3vylat25d+n6X94CBZ555pjjiiCOKnXbaqejYsWNx1FFHlR489mm2vId+FkVRPPfcc8W3v/3tol27dsVee+1V/L//9/8+cpypU6cWX/va14p27doVzz77bFEURXH77bcXvXv3Lnbcccdi7733Lm688cbSQ9RWZnkP/SwK9dSQbrjhhqK6unq5f5Y90KUoGr5W7rvvvhXOa3m1XBSr9nCbZdRK/axqvfzP//xPcfDBBxcdOnQodt999+KKK64oPVBoedbEuWXRokXF4MGDi549exbt2rUrDj300BU+rKso1EtDmTt3bvGjH/2o2H333YsOHToU/fv3L1588cVafcpRL//tvx/6+d/US8Nb3vdajlp57733iiuuuKLYc889i3bt2hXf+MY3ah23/6ZWGsaMGTOK8847r9h9992L9u3bL/ecv7bWi+vchnfLLbcUvXr1KnbcccfioIMOqnNMyvU70ahRo4r99tuv2HHHHYt99923uPvuu1fY17ml4aysXsp13XLTTTcVu++++yp9D+qlfn70ox8V3/72t1e4fXWP/TJnnnlm0aNHjzrH+NVXXy1OOeWUYueddy46depUHH744bV+lj355JPFgQceWLRv377YY489ijPPPLP45S9/WXTq1Kl47733Sg/9/Nvf/lZr3D//+c/FIYccUnTq1KnYaaedipNOOqnWAzk/rKamprjyyiuL3XbbrejQoUOx3377FbfccktxxBFHFOeee25RFMvPbf67xmbOnFmcccYZRefOnYtdd921uO2224rddttthQ/9LIqi+Ne//lUcddRRRYcOHYouXboUP/jBD4rXX3+9Tr+jjjqq6NGjR52Hq67s/VtRDrYmVBTFKt5/D/V03nnn5f3338+gQYPKPRU+BdQTq0qtsDrUC6tDvbCq1AqrQ72wqtQKq0O9fPKOPPLIdO7cuc7686y7PPSTT8yyj+7cf//9ufPOO8s9HdZx6olVpVZYHeqF1aFeWFVqhdWhXlhVaoXVoV4+eY888kjGjx+ff/7zn/nZz35W7umwBgnM+cSMHDkyjz32WAYMGJAOHTqUezqs49QTq0qtsDrUC6tDvbCq1AqrQ72wqtQKq0O9fPKGDRu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"text/plain": [ "
" ] @@ -1366,7 +1367,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -1418,29 +1419,29 @@ " \n", " \n", " Mission\n", - " 0.056841\n", - " 0.171199\n", - " 0.050172\n", - " 0.227154\n", - " 0.225018\n", - " 0.122017\n", - " 0.041523\n", - " 0.034855\n", - " 0.048348\n", - " 0.022872\n", + " 0.054378\n", + " 0.173489\n", + " 0.05183\n", + " 0.218813\n", + " 0.229385\n", + " 0.123936\n", + " 0.040607\n", + " 0.034698\n", + " 0.049119\n", + " 0.023746\n", " \n", " \n", " All\n", - " 0.056841\n", - " 0.171199\n", - " 0.050172\n", - " 0.227154\n", - " 0.225018\n", - " 0.122017\n", - " 0.041523\n", - " 0.034855\n", - " 0.048348\n", - " 0.022872\n", + " 0.054378\n", + " 0.173489\n", + " 0.05183\n", + " 0.218813\n", + " 0.229385\n", + " 0.123936\n", + " 0.040607\n", + " 0.034698\n", + " 0.049119\n", + " 0.023746\n", " \n", " \n", "\n", @@ -1449,26 +1450,26 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Home Library Definition \n", - "Mission 0.056841 0.171199 0.050172 \n", - "All 0.056841 0.171199 0.050172 \n", + "Mission 0.054378 0.173489 0.05183 \n", + "All 0.054378 0.173489 0.05183 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Home Library Definition \n", - "Mission 0.227154 0.225018 0.122017 \n", - "All 0.227154 0.225018 0.122017 \n", + "Mission 0.218813 0.229385 0.123936 \n", + "All 0.218813 0.229385 0.123936 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Home Library Definition \n", - "Mission 0.041523 0.034855 0.048348 \n", - "All 0.041523 0.034855 0.048348 \n", + "Mission 0.040607 0.034698 0.049119 \n", + "All 0.040607 0.034698 0.049119 \n", "\n", "Age Range 75 years and over \n", "Home Library Definition \n", - "Mission 0.022872 \n", - "All 0.022872 " + "Mission 0.023746 \n", + "All 0.023746 " ] }, - "execution_count": 28, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1487,7 +1488,7 @@ "source": [ "###### Antwort auf Frage 6\n", "Die Verteilung der Altersgruppen im Mission District ist wie folgt:\n", - "- ca. 6% der Nutzer sind zwischen 0 und 9 Jahren,\n", + "- ca. 5% der Nutzer sind zwischen 0 und 9 Jahren,\n", "- ca. 17% der Nutzer sind zwischen 10 und 19 Jahren,\n", " \n", "...\n", @@ -1516,7 +1517,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -1570,45 +1571,45 @@ " \n", " \n", " Email\n", - " 29979\n", - " 55109\n", - " 21740\n", - " 88098\n", - " 76322\n", - " 45360\n", - " 17403\n", - " 15438\n", - " 26988\n", - " 14340\n", - " 390777\n", + " 28740\n", + " 54936\n", + " 22701\n", + " 88200\n", + " 77618\n", + " 45165\n", + " 17336\n", + " 15539\n", + " 27170\n", + " 15069\n", + " 392474\n", " \n", " \n", - " Print\n", - " 1276\n", - " 665\n", - " 338\n", - " 1210\n", - " 1064\n", - " 683\n", - " 328\n", - " 346\n", - " 703\n", - " 579\n", - " 7192\n", + " None\n", + " 3952\n", + " 11921\n", + " 2680\n", + " 4469\n", + " 4101\n", + " 3154\n", + " 1740\n", + " 2115\n", + " 4544\n", + " 4228\n", + " 42904\n", " \n", " \n", " All\n", - " 31255\n", - " 55774\n", - " 22078\n", - " 89308\n", - " 77386\n", - " 46043\n", - " 17731\n", - " 15784\n", - " 27691\n", - " 14919\n", - " 397969\n", + " 32692\n", + " 66857\n", + " 25381\n", + " 92669\n", + " 81719\n", + " 48319\n", + " 19076\n", + " 17654\n", + " 31714\n", + " 19297\n", + " 435378\n", " \n", " \n", "\n", @@ -1617,30 +1618,30 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Notice Preference Definition \n", - "Email 29979 55109 21740 \n", - "Print 1276 665 338 \n", - "All 31255 55774 22078 \n", + "Email 28740 54936 22701 \n", + "None 3952 11921 2680 \n", + "All 32692 66857 25381 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Notice Preference Definition \n", - "Email 88098 76322 45360 \n", - "Print 1210 1064 683 \n", - "All 89308 77386 46043 \n", + "Email 88200 77618 45165 \n", + "None 4469 4101 3154 \n", + "All 92669 81719 48319 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Notice Preference Definition \n", - "Email 17403 15438 26988 \n", - "Print 328 346 703 \n", - "All 17731 15784 27691 \n", + "Email 17336 15539 27170 \n", + "None 1740 2115 4544 \n", + "All 19076 17654 31714 \n", "\n", "Age Range 75 years and over All \n", "Notice Preference Definition \n", - "Email 14340 390777 \n", - "Print 579 7192 \n", - "All 14919 397969 " + "Email 15069 392474 \n", + "None 4228 42904 \n", + "All 19297 435378 " ] }, - "execution_count": 29, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1658,7 +1659,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -1710,42 +1711,42 @@ " \n", " \n", " Email\n", - " 0.076716\n", - " 0.141024\n", - " 0.055633\n", - " 0.225443\n", - " 0.195308\n", - " 0.116076\n", - " 0.044534\n", - " 0.039506\n", - " 0.069062\n", - " 0.036696\n", + " 0.073228\n", + " 0.139974\n", + " 0.057841\n", + " 0.224728\n", + " 0.197766\n", + " 0.115078\n", + " 0.044171\n", + " 0.039592\n", + " 0.069228\n", + " 0.038395\n", " \n", " \n", - " Print\n", - " 0.177419\n", - " 0.092464\n", - " 0.046997\n", - " 0.168242\n", - " 0.147942\n", - " 0.094967\n", - " 0.045606\n", - " 0.048109\n", - " 0.097747\n", - " 0.080506\n", + " None\n", + " 0.092113\n", + " 0.277853\n", + " 0.062465\n", + " 0.104163\n", + " 0.095585\n", + " 0.073513\n", + " 0.040556\n", + " 0.049296\n", + " 0.105911\n", + " 0.098546\n", " \n", " \n", " All\n", - " 0.078536\n", - " 0.140147\n", - " 0.055477\n", - " 0.224409\n", - " 0.194452\n", - " 0.115695\n", - " 0.044554\n", - " 0.039661\n", - " 0.069581\n", - " 0.037488\n", + " 0.075089\n", + " 0.153561\n", + " 0.058296\n", + " 0.212847\n", + " 0.187697\n", + " 0.110982\n", + " 0.043815\n", + " 0.040549\n", + " 0.072842\n", + " 0.044322\n", " \n", " \n", "\n", @@ -1754,30 +1755,30 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Notice Preference Definition \n", - "Email 0.076716 0.141024 0.055633 \n", - "Print 0.177419 0.092464 0.046997 \n", - "All 0.078536 0.140147 0.055477 \n", + "Email 0.073228 0.139974 0.057841 \n", + "None 0.092113 0.277853 0.062465 \n", + "All 0.075089 0.153561 0.058296 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Notice Preference Definition \n", - "Email 0.225443 0.195308 0.116076 \n", - "Print 0.168242 0.147942 0.094967 \n", - "All 0.224409 0.194452 0.115695 \n", + "Email 0.224728 0.197766 0.115078 \n", + "None 0.104163 0.095585 0.073513 \n", + "All 0.212847 0.187697 0.110982 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Notice Preference Definition \n", - "Email 0.044534 0.039506 0.069062 \n", - "Print 0.045606 0.048109 0.097747 \n", - "All 0.044554 0.039661 0.069581 \n", + "Email 0.044171 0.039592 0.069228 \n", + "None 0.040556 0.049296 0.105911 \n", + "All 0.043815 0.040549 0.072842 \n", "\n", "Age Range 75 years and over \n", "Notice Preference Definition \n", - "Email 0.036696 \n", - "Print 0.080506 \n", - "All 0.037488 " + "Email 0.038395 \n", + "None 0.098546 \n", + "All 0.044322 " ] }, - "execution_count": 30, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1796,12 +1797,12 @@ "metadata": {}, "source": [ "Hier sehen wir, dass jede Zeile in der Summe 1 ergibt. D.h. wir können die Tabelle prozentual nach Zeilen interpretieren.\n", - "Also z.B. erste Zeile: Von allen Nutzern, die per Mail informiert werden möchten, befinden sich ca. 13% (0.128020 von 1) in der Altersgruppe 45 bis 54 Jahre.\n" + "Also z.B. erste Zeile: Von allen Nutzern, die per Mail informiert werden möchten, befinden sich ca. 12% (0.115078 von 1) in der Altersgruppe 45 bis 54 Jahre.\n" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -1855,31 +1856,31 @@ " \n", " \n", " Email\n", - " 0.959175\n", - " 0.988077\n", - " 0.984691\n", - " 0.986451\n", - " 0.986251\n", - " 0.985166\n", - " 0.981501\n", - " 0.978079\n", - " 0.974613\n", - " 0.96119\n", - " 0.981928\n", + " 0.879114\n", + " 0.821694\n", + " 0.894409\n", + " 0.951775\n", + " 0.949816\n", + " 0.934725\n", + " 0.908786\n", + " 0.880197\n", + " 0.856719\n", + " 0.780899\n", + " 0.901456\n", " \n", " \n", - " Print\n", - " 0.040825\n", - " 0.011923\n", - " 0.015309\n", - " 0.013549\n", - " 0.013749\n", - " 0.014834\n", - " 0.018499\n", - " 0.021921\n", - " 0.025387\n", - " 0.03881\n", - " 0.018072\n", + " None\n", + " 0.120886\n", + " 0.178306\n", + " 0.105591\n", + " 0.048225\n", + " 0.050184\n", + " 0.065275\n", + " 0.091214\n", + " 0.119803\n", + " 0.143281\n", + " 0.219101\n", + " 0.098544\n", " \n", " \n", "\n", @@ -1888,26 +1889,26 @@ "text/plain": [ "Age Range 0 to 9 years 10 to 19 years 20 to 24 years \\\n", "Notice Preference Definition \n", - "Email 0.959175 0.988077 0.984691 \n", - "Print 0.040825 0.011923 0.015309 \n", + "Email 0.879114 0.821694 0.894409 \n", + "None 0.120886 0.178306 0.105591 \n", "\n", "Age Range 25 to 34 years 35 to 44 years 45 to 54 years \\\n", "Notice Preference Definition \n", - "Email 0.986451 0.986251 0.985166 \n", - "Print 0.013549 0.013749 0.014834 \n", + "Email 0.951775 0.949816 0.934725 \n", + "None 0.048225 0.050184 0.065275 \n", "\n", "Age Range 55 to 59 years 60 to 64 years 65 to 74 years \\\n", "Notice Preference Definition \n", - "Email 0.981501 0.978079 0.974613 \n", - "Print 0.018499 0.021921 0.025387 \n", + "Email 0.908786 0.880197 0.856719 \n", + "None 0.091214 0.119803 0.143281 \n", "\n", "Age Range 75 years and over All \n", "Notice Preference Definition \n", - "Email 0.96119 0.981928 \n", - "Print 0.03881 0.018072 " + "Email 0.780899 0.901456 \n", + "None 0.219101 0.098544 " ] }, - "execution_count": 31, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1926,7 +1927,7 @@ "metadata": {}, "source": [ "Hier sehen wir, dass jede Spalte in der Summe 1 ergibt. D.h. wir können die Tabelle prozentual nach Spalten interpretieren.\n", - "Also z.B. erste Spalte: Von allen Nutzern, die zwischen 0 und 9 Jahren sind, möchten sich ca. 4% (0.040825 von 1) per Post informieren lassen.\n" + "Also z.B. erste Spalte: Von allen Nutzern, die zwischen 0 und 9 Jahren sind, möchten sich ca. 12% (0.120886 von 1) nicht informieren lassen.\n" ] }, { diff --git a/content/descriptive_statistics/solutions.files/3.8.solutions_anscombe.ipynb b/content/descriptive_statistics/solutions.files/solutions_anscombe.ipynb similarity index 99% rename from content/descriptive_statistics/solutions.files/3.8.solutions_anscombe.ipynb rename to content/descriptive_statistics/solutions.files/solutions_anscombe.ipynb index 037cc705..2cec246f 100755 --- a/content/descriptive_statistics/solutions.files/3.8.solutions_anscombe.ipynb +++ b/content/descriptive_statistics/solutions.files/solutions_anscombe.ipynb @@ -447,7 +447,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -461,9 +461,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/content/descriptive_statistics/solutions.files/solutions_outlier.ipynb b/content/descriptive_statistics/solutions.files/solutions_outlier.ipynb index 17f03d5b..93ae9257 100644 --- a/content/descriptive_statistics/solutions.files/solutions_outlier.ipynb +++ b/content/descriptive_statistics/solutions.files/solutions_outlier.ipynb @@ -21,7 +21,9 @@ "import matplotlib.pyplot as plt\n", "\n", "sns.set()\n", - "df = pd.read_csv(\"../data/Library_Usage.csv\")" + "df = pd.read_csv(\"../data/Library_Usage.csv\",\n", + " low_memory=False\n", + ")" ] }, { @@ -33,24 +35,24 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 29, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -74,19 +76,19 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.90 424.0\n", - "0.95 816.0\n", - "0.99 2118.0\n", + "0.90 397.0\n", + "0.95 841.0\n", + "0.99 2428.0\n", "Name: Total Checkouts, dtype: float64" ] }, - "execution_count": 30, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -99,24 +101,24 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "99% der Beobachtungen haben weniger als 2118 Ausleihen. 95% weniger als 816 und 90% weniger als 424 Ausleihen. Den gleichen Trend, wenn auch nicht so stark, erhalten wir für die `Total Renewals`:" + "99% der Beobachtungen haben weniger als 2428 Ausleihen. 95% weniger als 841 und 90% weniger als 397 Ausleihen. Den gleichen Trend, wenn auch nicht so stark, erhalten wir für die `Total Renewals`:" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.90 130.0\n", - "0.95 285.0\n", - "0.99 982.0\n", + "0.90 167.00\n", + "0.95 368.00\n", + "0.99 1305.11\n", "Name: Total Renewals, dtype: float64" ] }, - "execution_count": 31, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -136,7 +138,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -154,16 +156,16 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.0057669418677145715" + "0.006644662953540077" ] }, - "execution_count": 44, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -181,14 +183,14 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "413195 423448\n" + "426106 436290\n" ] } ], @@ -206,24 +208,24 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 53, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -240,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -258,15 +260,18 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 10, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ 2. 113.] 111.0 279.5\n" - ] + "data": { + "text/plain": [ + "array([ 0., 78.])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -280,16 +285,16 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "111.0" + "78.0" ] }, - "execution_count": 66, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -301,16 +306,16 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "279.5" + "195.0" ] }, - "execution_count": 71, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -322,16 +327,16 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.1410940658593263" + "0.16023516468404042" ] }, - "execution_count": 72, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -350,24 +355,24 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 73, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" + "
" ] }, "metadata": {}, @@ -395,24 +400,24 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 88, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, @@ -437,24 +442,32 @@ }, { "cell_type": "code", - "execution_count": 110, + "execution_count": 19, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ania/anaconda3/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 110, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] }, "metadata": {}, @@ -467,24 +480,32 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 20, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ania/anaconda3/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 108, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, @@ -500,24 +521,32 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 21, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ania/anaconda3/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 109, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, @@ -527,11 +556,18 @@ "source": [ "sns.distplot(df['Total Checkouts Log'])" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -545,9 +581,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.9.13" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 }