{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Load necessary packages, get the data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "cervical_cancer_data = pd.read_csv(\"http://archive.ics.uci.edu/ml/machine-learning-databases/00383/risk_factors_cervical_cancer.csv\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Take a quick peek" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AgeNumber of sexual partnersFirst sexual intercourseNum of pregnanciesSmokesSmokes (years)Smokes (packs/year)Hormonal ContraceptivesHormonal Contraceptives (years)IUD...STDs: Time since first diagnosisSTDs: Time since last diagnosisDx:CancerDx:CINDx:HPVDxHinselmannSchillerCitologyBiopsy
0184.015.01.00.00.00.00.00.00.0...??00000000
1151.014.01.00.00.00.00.00.00.0...??00000000
2341.0?1.00.00.00.00.00.00.0...??00000000
3525.016.04.01.037.037.01.03.00.0...??10100000
4463.021.04.00.00.00.01.015.00.0...??00000000
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5 rows × 36 columns

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" ], "text/plain": [ " Age Number of sexual partners First sexual intercourse Num of pregnancies \\\n", "0 18 4.0 15.0 1.0 \n", "1 15 1.0 14.0 1.0 \n", "2 34 1.0 ? 1.0 \n", "3 52 5.0 16.0 4.0 \n", "4 46 3.0 21.0 4.0 \n", "\n", " Smokes Smokes (years) Smokes (packs/year) Hormonal Contraceptives \\\n", "0 0.0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 0.0 \n", "3 1.0 37.0 37.0 1.0 \n", "4 0.0 0.0 0.0 1.0 \n", "\n", " Hormonal Contraceptives (years) IUD ... \\\n", "0 0.0 0.0 ... \n", "1 0.0 0.0 ... \n", "2 0.0 0.0 ... \n", "3 3.0 0.0 ... \n", "4 15.0 0.0 ... \n", "\n", " STDs: Time since first diagnosis STDs: Time since last diagnosis Dx:Cancer \\\n", "0 ? ? 0 \n", "1 ? ? 0 \n", "2 ? ? 0 \n", "3 ? ? 1 \n", "4 ? ? 0 \n", "\n", " Dx:CIN Dx:HPV Dx Hinselmann Schiller Citology Biopsy \n", "0 0 0 0 0 0 0 0 \n", "1 0 0 0 0 0 0 0 \n", "2 0 0 0 0 0 0 0 \n", "3 0 1 0 0 0 0 0 \n", "4 0 0 0 0 0 0 0 \n", "\n", "[5 rows x 36 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get a glimpse of the column types" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Age int64\n", "Number of sexual partners object\n", "First sexual intercourse object\n", "Num of pregnancies object\n", "Smokes object\n", "Smokes (years) object\n", "Smokes (packs/year) object\n", "Hormonal Contraceptives object\n", "Hormonal Contraceptives (years) object\n", "IUD object\n", "IUD (years) object\n", "STDs object\n", "STDs (number) object\n", "STDs:condylomatosis object\n", "STDs:cervical condylomatosis object\n", "STDs:vaginal condylomatosis object\n", "STDs:vulvo-perineal condylomatosis object\n", "STDs:syphilis object\n", "STDs:pelvic inflammatory disease object\n", "STDs:genital herpes object\n", "STDs:molluscum contagiosum object\n", "STDs:AIDS object\n", "STDs:HIV object\n", "STDs:Hepatitis B object\n", "STDs:HPV object\n", "STDs: Number of diagnosis int64\n", "STDs: Time since first diagnosis object\n", "STDs: Time since last diagnosis object\n", "Dx:Cancer int64\n", "Dx:CIN int64\n", "Dx:HPV int64\n", "Dx int64\n", "Hinselmann int64\n", "Schiller int64\n", "Citology int64\n", "Biopsy int64\n", "dtype: object" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.dtypes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Read data in again, making question marks into \"NaN\" " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "cervical_cancer_data = pd.read_csv(\"http://archive.ics.uci.edu/ml/machine-learning-databases/00383/risk_factors_cervical_cancer.csv\",\n", " na_values=\"?\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Take a peek now!" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AgeNumber of sexual partnersFirst sexual intercourseNum of pregnanciesSmokesSmokes (years)Smokes (packs/year)Hormonal ContraceptivesHormonal Contraceptives (years)IUD...STDs: Time since first diagnosisSTDs: Time since last diagnosisDx:CancerDx:CINDx:HPVDxHinselmannSchillerCitologyBiopsy
0184.015.01.00.00.00.00.00.00.0...NaNNaN00000000
1151.014.01.00.00.00.00.00.00.0...NaNNaN00000000
2341.0NaN1.00.00.00.00.00.00.0...NaNNaN00000000
3525.016.04.01.037.037.01.03.00.0...NaNNaN10100000
4463.021.04.00.00.00.01.015.00.0...NaNNaN00000000
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5 rows × 36 columns

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" ], "text/plain": [ " Age Number of sexual partners First sexual intercourse \\\n", "0 18 4.0 15.0 \n", "1 15 1.0 14.0 \n", "2 34 1.0 NaN \n", "3 52 5.0 16.0 \n", "4 46 3.0 21.0 \n", "\n", " Num of pregnancies Smokes Smokes (years) Smokes (packs/year) \\\n", "0 1.0 0.0 0.0 0.0 \n", "1 1.0 0.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "3 4.0 1.0 37.0 37.0 \n", "4 4.0 0.0 0.0 0.0 \n", "\n", " Hormonal Contraceptives Hormonal Contraceptives (years) IUD ... \\\n", "0 0.0 0.0 0.0 ... \n", "1 0.0 0.0 0.0 ... \n", "2 0.0 0.0 0.0 ... \n", "3 1.0 3.0 0.0 ... \n", "4 1.0 15.0 0.0 ... \n", "\n", " STDs: Time since first diagnosis STDs: Time since last diagnosis \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "\n", " Dx:Cancer Dx:CIN Dx:HPV Dx Hinselmann Schiller Citology Biopsy \n", "0 0 0 0 0 0 0 0 0 \n", "1 0 0 0 0 0 0 0 0 \n", "2 0 0 0 0 0 0 0 0 \n", "3 1 0 1 0 0 0 0 0 \n", "4 0 0 0 0 0 0 0 0 \n", "\n", "[5 rows x 36 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get summary statistics" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AgeNumber of sexual partnersFirst sexual intercourseNum of pregnanciesSmokesSmokes (years)Smokes (packs/year)Hormonal ContraceptivesHormonal Contraceptives (years)IUD...STDs: Time since first diagnosisSTDs: Time since last diagnosisDx:CancerDx:CINDx:HPVDxHinselmannSchillerCitologyBiopsy
count858.000000832.000000851.000000802.000000845.000000845.000000845.000000750.000000750.000000741.000000...71.00000071.000000858.000000858.000000858.000000858.000000858.000000858.000000858.000000858.000000
mean26.8205132.52764416.9953002.2755610.1455621.2197210.4531440.6413332.2564190.112011...6.1408455.8169010.0209790.0104900.0209790.0279720.0407930.0862470.0512820.064103
std8.4979481.6677602.8033551.4474140.3528764.0890172.2266100.4799293.7642540.315593...5.8950245.7552710.1433980.1019390.1433980.1649890.1979250.2808920.2207010.245078
min13.0000001.00000010.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000...1.0000001.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
25%20.0000002.00000015.0000001.0000000.0000000.0000000.0000000.0000000.0000000.000000...2.0000002.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
50%25.0000002.00000017.0000002.0000000.0000000.0000000.0000001.0000000.5000000.000000...4.0000003.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
75%32.0000003.00000018.0000003.0000000.0000000.0000000.0000001.0000003.0000000.000000...8.0000007.5000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
max84.00000028.00000032.00000011.0000001.00000037.00000037.0000001.00000030.0000001.000000...22.00000022.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
\n", "

8 rows × 36 columns

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" ], "text/plain": [ " Age Number of sexual partners First sexual intercourse \\\n", "count 858.000000 832.000000 851.000000 \n", "mean 26.820513 2.527644 16.995300 \n", "std 8.497948 1.667760 2.803355 \n", "min 13.000000 1.000000 10.000000 \n", "25% 20.000000 2.000000 15.000000 \n", "50% 25.000000 2.000000 17.000000 \n", "75% 32.000000 3.000000 18.000000 \n", "max 84.000000 28.000000 32.000000 \n", "\n", " Num of pregnancies Smokes Smokes (years) Smokes (packs/year) \\\n", "count 802.000000 845.000000 845.000000 845.000000 \n", "mean 2.275561 0.145562 1.219721 0.453144 \n", "std 1.447414 0.352876 4.089017 2.226610 \n", "min 0.000000 0.000000 0.000000 0.000000 \n", "25% 1.000000 0.000000 0.000000 0.000000 \n", "50% 2.000000 0.000000 0.000000 0.000000 \n", "75% 3.000000 0.000000 0.000000 0.000000 \n", "max 11.000000 1.000000 37.000000 37.000000 \n", "\n", " Hormonal Contraceptives Hormonal Contraceptives (years) IUD \\\n", "count 750.000000 750.000000 741.000000 \n", "mean 0.641333 2.256419 0.112011 \n", "std 0.479929 3.764254 0.315593 \n", "min 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 \n", "50% 1.000000 0.500000 0.000000 \n", "75% 1.000000 3.000000 0.000000 \n", "max 1.000000 30.000000 1.000000 \n", "\n", " ... STDs: Time since first diagnosis \\\n", "count ... 71.000000 \n", "mean ... 6.140845 \n", "std ... 5.895024 \n", "min ... 1.000000 \n", "25% ... 2.000000 \n", "50% ... 4.000000 \n", "75% ... 8.000000 \n", "max ... 22.000000 \n", "\n", " STDs: Time since last diagnosis Dx:Cancer Dx:CIN Dx:HPV \\\n", "count 71.000000 858.000000 858.000000 858.000000 \n", "mean 5.816901 0.020979 0.010490 0.020979 \n", "std 5.755271 0.143398 0.101939 0.143398 \n", "min 1.000000 0.000000 0.000000 0.000000 \n", "25% 2.000000 0.000000 0.000000 0.000000 \n", "50% 3.000000 0.000000 0.000000 0.000000 \n", "75% 7.500000 0.000000 0.000000 0.000000 \n", "max 22.000000 1.000000 1.000000 1.000000 \n", "\n", " Dx Hinselmann Schiller Citology Biopsy \n", "count 858.000000 858.000000 858.000000 858.000000 858.000000 \n", "mean 0.027972 0.040793 0.086247 0.051282 0.064103 \n", "std 0.164989 0.197925 0.280892 0.220701 0.245078 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "50% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "75% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "max 1.000000 1.000000 1.000000 1.000000 1.000000 \n", "\n", "[8 rows x 36 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Do we like our column names?" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Age', 'Number of sexual partners', 'First sexual intercourse',\n", " 'Num of pregnancies', 'Smokes', 'Smokes (years)', 'Smokes (packs/year)',\n", " 'Hormonal Contraceptives', 'Hormonal Contraceptives (years)', 'IUD',\n", " 'IUD (years)', 'STDs', 'STDs (number)', 'STDs:condylomatosis',\n", " 'STDs:cervical condylomatosis', 'STDs:vaginal condylomatosis',\n", " 'STDs:vulvo-perineal condylomatosis', 'STDs:syphilis',\n", " 'STDs:pelvic inflammatory disease', 'STDs:genital herpes',\n", " 'STDs:molluscum contagiosum', 'STDs:AIDS', 'STDs:HIV',\n", " 'STDs:Hepatitis B', 'STDs:HPV', 'STDs: Number of diagnosis',\n", " 'STDs: Time since first diagnosis', 'STDs: Time since last diagnosis',\n", " 'Dx:Cancer', 'Dx:CIN', 'Dx:HPV', 'Dx', 'Hinselmann', 'Schiller',\n", " 'Citology', 'Biopsy'],\n", " dtype='object')" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### These column names won't work well for other researchers using other packages.\n", "\n", "We'll make them lowercase and change any spaces or punctuation to underscore. We'll need the regular expressions, or \"re\" library to do this." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "cervical_cancer_data.columns = cervical_cancer_data.columns.str.lower()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['age', 'number of sexual partners', 'first sexual intercourse',\n", " 'num of pregnancies', 'smokes', 'smokes (years)', 'smokes (packs/year)',\n", " 'hormonal contraceptives', 'hormonal contraceptives (years)', 'iud',\n", " 'iud (years)', 'stds', 'stds (number)', 'stds:condylomatosis',\n", " 'stds:cervical condylomatosis', 'stds:vaginal condylomatosis',\n", " 'stds:vulvo-perineal condylomatosis', 'stds:syphilis',\n", " 'stds:pelvic inflammatory disease', 'stds:genital herpes',\n", " 'stds:molluscum contagiosum', 'stds:aids', 'stds:hiv',\n", " 'stds:hepatitis b', 'stds:hpv', 'stds: number of diagnosis',\n", " 'stds: time since first diagnosis', 'stds: time since last diagnosis',\n", " 'dx:cancer', 'dx:cin', 'dx:hpv', 'dx', 'hinselmann', 'schiller',\n", " 'citology', 'biopsy'],\n", " dtype='object')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.columns" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "import re" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['age', 'number_of_sexual_partners', 'first_sexual_intercourse',\n", " 'num_of_pregnancies', 'smokes', 'smokes_years_', 'smokes_packs_year_',\n", " 'hormonal_contraceptives', 'hormonal_contraceptives_years_', 'iud',\n", " 'iud_years_', 'stds', 'stds_number_', 'stds_condylomatosis',\n", " 'stds_cervical_condylomatosis', 'stds_vaginal_condylomatosis',\n", " 'stds_vulvo_perineal_condylomatosis', 'stds_syphilis',\n", " 'stds_pelvic_inflammatory_disease', 'stds_genital_herpes',\n", " 'stds_molluscum_contagiosum', 'stds_aids', 'stds_hiv',\n", " 'stds_hepatitis_b', 'stds_hpv', 'stds_number_of_diagnosis',\n", " 'stds_time_since_first_diagnosis', 'stds_time_since_last_diagnosis',\n", " 'dx_cancer', 'dx_cin', 'dx_hpv', 'dx', 'hinselmann', 'schiller',\n", " 'citology', 'biopsy'],\n", " dtype='object')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.columns = [re.sub('[^a-z]+', '_', col) for col in cervical_cancer_data.columns]\n", "cervical_cancer_data.columns" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['age', 'number_of_sexual_partners', 'first_sexual_intercourse',\n", " 'num_of_pregnancies', 'smokes', 'smokes_years', 'smokes_packs_year',\n", " 'hormonal_contraceptives', 'hormonal_contraceptives_years', 'iud',\n", " 'iud_years', 'stds', 'stds_number', 'stds_condylomatosis',\n", " 'stds_cervical_condylomatosis', 'stds_vaginal_condylomatosis',\n", " 'stds_vulvo_perineal_condylomatosis', 'stds_syphilis',\n", " 'stds_pelvic_inflammatory_disease', 'stds_genital_herpes',\n", " 'stds_molluscum_contagiosum', 'stds_aids', 'stds_hiv',\n", " 'stds_hepatitis_b', 'stds_hpv', 'stds_number_of_diagnosis',\n", " 'stds_time_since_first_diagnosis', 'stds_time_since_last_diagnosis',\n", " 'dx_cancer', 'dx_cin', 'dx_hpv', 'dx', 'hinselmann', 'schiller',\n", " 'citology', 'biopsy'],\n", " dtype='object')" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.columns = [re.sub('_$', '', col) for col in cervical_cancer_data.columns]\n", "cervical_cancer_data.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Make 0/1 Columns into Booleans" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 False\n", "1 False\n", "2 False\n", "3 True\n", "4 False\n", "5 False\n", "6 True\n", "7 False\n", "8 False\n", "9 True\n", "10 False\n", "11 False\n", "12 False\n", "13 False\n", "14 False\n", "15 False\n", "16 False\n", "17 False\n", "18 False\n", "19 False\n", "20 False\n", "21 False\n", "22 False\n", "23 False\n", "24 False\n", "25 False\n", "26 False\n", "27 False\n", "28 True\n", "29 False\n", " ... \n", "828 False\n", "829 False\n", "830 False\n", "831 False\n", "832 False\n", "833 False\n", "834 True\n", "835 False\n", "836 False\n", "837 True\n", "838 False\n", "839 False\n", "840 False\n", "841 False\n", "842 True\n", "843 False\n", "844 True\n", "845 False\n", "846 False\n", "847 False\n", "848 False\n", "849 True\n", "850 False\n", "851 False\n", "852 False\n", "853 False\n", "854 False\n", "855 False\n", "856 False\n", "857 False\n", "Name: smokes, Length: 858, dtype: bool" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data['smokes'].astype(\"bool\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "boolean_cols = [\"smokes\", \"hormonal_contraceptives\", \"iud\", \"stds\", \n", " \"stds_condylomatosis\", \"stds_cervical_condylomatosis\", \n", " \"stds_vaginal_condylomatosis\", \n", " \"stds_vulvo_perineal_condylomatosis\", \n", " \"stds_syphilis\", \"stds_pelvic_inflammatory_disease\", \n", " \"stds_genital_herpes\", \"stds_molluscum_contagiosum\", \n", " \"stds_aids\", \"stds_hiv\", \"stds_hepatitis_b\", \"stds_hpv\",\n", " \"dx_cancer\", \"dx_cin\", \"dx_hpv\", \"dx\", \"hinselmann\",\n", " \"schiller\", \"citology\", \"biopsy\"]" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "for x in boolean_cols:\n", " cervical_cancer_data[x] = cervical_cancer_data[x].astype(\"bool\") " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "age int64\n", "number_of_sexual_partners float64\n", "first_sexual_intercourse float64\n", "num_of_pregnancies float64\n", "smokes bool\n", "smokes_years float64\n", "smokes_packs_year float64\n", "hormonal_contraceptives bool\n", "hormonal_contraceptives_years float64\n", "iud bool\n", "iud_years float64\n", "stds bool\n", "stds_number float64\n", "stds_condylomatosis bool\n", "stds_cervical_condylomatosis bool\n", "stds_vaginal_condylomatosis bool\n", "stds_vulvo_perineal_condylomatosis bool\n", "stds_syphilis bool\n", "stds_pelvic_inflammatory_disease bool\n", "stds_genital_herpes bool\n", "stds_molluscum_contagiosum bool\n", "stds_aids bool\n", "stds_hiv bool\n", "stds_hepatitis_b bool\n", "stds_hpv bool\n", "stds_number_of_diagnosis int64\n", "stds_time_since_first_diagnosis float64\n", "stds_time_since_last_diagnosis float64\n", "dx_cancer bool\n", "dx_cin bool\n", "dx_hpv bool\n", "dx bool\n", "hinselmann bool\n", "schiller bool\n", "citology bool\n", "biopsy bool\n", "dtype: object" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.dtypes" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "from matplotlib import pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(cervical_cancer_data['age'])\n", "plt.xlabel(\"Age\")\n", "plt.ylabel(\"Count\")\n", "plt.title(\"Histogram of Age\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/paytonk/anaconda3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile\n", " interpolation=interpolation)\n", "/Users/paytonk/anaconda3/lib/python3.6/site-packages/matplotlib/cbook/__init__.py:1872: RuntimeWarning: invalid value encountered in less_equal\n", " wiskhi = np.compress(x <= hival, x)\n", "/Users/paytonk/anaconda3/lib/python3.6/site-packages/matplotlib/cbook/__init__.py:1879: RuntimeWarning: invalid value encountered in greater_equal\n", " wisklo = np.compress(x >= loval, x)\n", "/Users/paytonk/anaconda3/lib/python3.6/site-packages/matplotlib/cbook/__init__.py:1887: RuntimeWarning: invalid value encountered in less\n", " np.compress(x < stats['whislo'], x),\n", "/Users/paytonk/anaconda3/lib/python3.6/site-packages/matplotlib/cbook/__init__.py:1888: RuntimeWarning: invalid value encountered in greater\n", " np.compress(x > stats['whishi'], x)\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.boxplot(cervical_cancer_data['number_of_sexual_partners'])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.boxplot(cervical_cancer_data['number_of_sexual_partners'][~np.isnan(cervical_cancer_data['number_of_sexual_partners'])])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(cervical_cancer_data['smokes_years'], cervical_cancer_data['stds_number'])\n", "plt.xlabel(\"Smoking Years\")\n", "plt.ylabel(\"Number of STIs\")\n", "plt.title(\"Sexually Transmitted Infections as a Function of Smoking Years\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Let's plot a correlation heatmap!" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "corr = cervical_cancer_data.corr()\n", "plt.matshow(corr)\n", "plt.xticks(range(len(corr.columns)), corr.columns, rotation='vertical')\n", "plt.yticks(range(len(corr.columns)), corr.columns)\n", "plt.rcParams[\"figure.figsize\"] =(15,10)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Ugh, that's not great. Let's try a different tack, using a table with a gradient background:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/paytonk/anaconda3/lib/python3.6/site-packages/matplotlib/colors.py:504: RuntimeWarning: invalid value encountered in less\n", " xa[xa < 0] = -1\n" ] }, { "data": { "text/html": [ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 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agenumber_of_sexual_partnersfirst_sexual_intercoursenum_of_pregnanciessmokessmokes_yearssmokes_packs_yearhormonal_contraceptiveshormonal_contraceptives_yearsiudiud_yearsstdsstds_numberstds_condylomatosisstds_cervical_condylomatosisstds_vaginal_condylomatosisstds_vulvo_perineal_condylomatosisstds_syphilisstds_pelvic_inflammatory_diseasestds_genital_herpesstds_molluscum_contagiosumstds_aidsstds_hivstds_hepatitis_bstds_hpvstds_number_of_diagnosisstds_time_since_first_diagnosisstds_time_since_last_diagnosisdx_cancerdx_cindx_hpvdxhinselmannschillercitologybiopsy
age10.0856340.3700170.5488560.04524440.2186190.1319460.02920130.2897830.1077250.216101-0.0849161-0.0161856-0.119277-0.128618-0.124629-0.118207-0.113142-0.125518-0.13094-0.12802-0.128618-0.118233-0.13094-0.121616-0.001605940.4059290.4851210.110340.06144340.1017220.0926351-0.003966850.103283-0.01686210.0559555
number_of_sexual_partners0.0856341-0.1501690.07908070.2438390.1869320.1820670.005847690.01956930.02379990.004453860.03707020.04144170.018885-0.00245086-0.01164270.01996960.009398280.000914447-0.005919260.000914447-0.002450860.00629981-0.00364136-0.0002861530.05189960.05182510.07799190.02231640.01569350.02727290.022992-0.0398474-0.008966950.0218576-0.00144245
first_sexual_intercourse0.370017-0.1501691-0.0607327-0.119815-0.0588344-0.0567552-0.009269380.00830776-0.0704175-0.0265033-0.07364420.00674514-0.0578771-0.0902938-0.0737004-0.0558185-0.123784-0.089917-0.0873664-0.0911923-0.0902938-0.0878793-0.0886417-0.0844655-0.0133320.06377450.08936970.0672885-0.03262780.04396960.0357546-0.01654870.00349475-0.01097320.00726437
num_of_pregnancies0.5488560.0790807-0.060732710.07084350.1803310.1009040.1229980.224790.0958640.154987-0.02340490.0017439-0.086466-0.0782136-0.0771182-0.0860852-0.0108958-0.0838803-0.0812367-0.0733058-0.0782136-0.0672378-0.0812367-0.08160380.03415330.2167640.2762490.03514910.01098510.0467880.02133580.04043870.0920173-0.03003620.0464159
smokes0.04524440.243839-0.1198150.070843510.7231280.493361-0.002485360.04009290.00225203-0.02900390.1075660.1327310.06219050.02294830.03567330.06369510.05922430.02131780.02131780.02131780.02294830.05011780.03101590.02936010.1172770.09835110.0427880.00327007-0.04468570.0255377-0.05427110.03956160.05991270.0003709760.0297328
smokes_years0.2186190.186932-0.05883440.1803310.72312810.724116-0.01472140.05097920.01338710.04021970.0614240.09877160.0226652-0.004987220.01880670.02367010.00182157-0.00604593-0.00604593-0.00604593-0.004987220.03301290.005461040.002600270.08464670.1591060.1643450.0562341-0.03096830.0588473-0.0499260.07225130.0958904-0.006827070.0620442
smokes_packs_year0.1319460.182067-0.05675520.1009040.4933610.72411610.001247470.0412776-0.0001061120.01658390.01115440.0326579-0.00638392-0.01354-0.00466788-0.00575894-0.0137368-0.0142198-0.0142198-0.0142198-0.013540.0102463-0.00284111-0.01463530.03335660.1950850.1996110.111572-0.02112840.113516-0.03406260.02704350.01819120.004665530.0248819
hormonal_contraceptives0.02920130.00584769-0.009269380.122998-0.00248536-0.01472140.0012474710.4485740.194324-0.03478140.163352-0.02797330.1970630.2446910.2276290.1955040.2262740.246090.246090.2384550.2446910.1975980.2384550.247484-0.06219860.05880560.1153530.0112779-0.004397260.0288078-0.007244990.01236-0.0340024-0.0251159-0.0180153
hormonal_contraceptives_years0.2897830.01956930.008307760.224790.04009290.05097920.04127760.44857410.1085850.0004828030.0340383-0.007054830.05033870.1015330.0650260.05256250.06539860.09243180.09095760.09022050.1015330.03246010.09022050.113962-0.03845870.3178070.3612430.05471180.003273170.0632286-0.01344610.03894480.07924730.07626320.0793876
iud0.1077250.0237999-0.07041750.0958640.002252030.0133871-0.0001061120.1943240.10858510.7464780.5178790.0875680.5622680.6436760.6340.5581710.5925480.6391060.6391060.6391060.6436760.608280.6391060.634591-0.01351560.1425170.1765520.0347030.07852290.01546840.107085-0.0161445-0.0122685-0.0281993-0.00923433
iud_years0.2161010.00445386-0.02650330.154987-0.02900390.04021970.0165839-0.03478140.0004828030.74647810.0142140.01566640.022031-0.0195317-0.0209720.0208465-0.0355788-0.0218519-0.0218519-0.0218519-0.01953170.00975568-0.0218519-0.02395380.007902520.1072810.1304410.09811270.01800070.03364690.1119930.007994020.07941530.00271470.0332753
stds-0.08491610.0370702-0.0736442-0.02340490.1075660.0614240.01115440.1633520.03403830.5178790.01421410.9186090.8773870.7146910.7301190.8738210.7829430.7185630.7185630.7185630.7146910.7829430.7185630.7224250.553297nannan-0.03685680.00194911-0.0368568-0.0369711-0.02161670.00132040.00726220.0255648
stds_number-0.01618560.04144170.006745140.00174390.1327310.09877160.0326579-0.0279733-0.007054830.0875680.01566640.91860910.899521nan0.3348490.8906990.306830.0534620.0534620.053462nan0.3842310.1183930.07565710.897233-0.0654583-0.179025-0.0182556-0.00952577-0.0182556-0.02834060.06534910.1207250.06000950.0983473
stds_condylomatosis-0.1192770.018885-0.0578771-0.0864660.06219050.0226652-0.006383920.1970630.05033870.5622680.0220310.8773870.89952110.8145680.8321510.9959370.7518840.8096310.8096310.8096310.8145680.7694430.8096310.8047580.315185-0.129216-0.182258-0.0671068-0.0170003-0.0671068-0.0591078-0.0323222-0.02028430.00500721-0.00692478
stds_cervical_condylomatosis-0.128618-0.00245086-0.0902938-0.07821360.0229483-0.00498722-0.013540.2446910.1015330.643676-0.01953170.714691nan0.81456810.978870.8178910.9128270.9946110.9946110.99461110.9128270.9946110.989294-0.107953nannan-0.054663-0.00353958-0.054663-0.0417782-0.0770072-0.102056-0.0384481-0.0686891
stds_vaginal_condylomatosis-0.124629-0.0116427-0.0737004-0.07711820.03567330.0188067-0.004667880.2276290.0650260.634-0.0209720.7301190.3348490.8321510.9788710.8262830.8925830.9735380.9735380.9735380.978870.8925830.9735380.968277-0.0639846-0.141545-0.131131-0.055843-0.00492466-0.055843-0.0434887-0.0786695-0.104734-0.0410914-0.0712605
stds_vulvo_perineal_condylomatosis-0.1182070.0199696-0.0558185-0.08608520.06369510.0236701-0.005758940.1955040.05256250.5581710.02084650.8738210.8906990.9959370.8178910.82628310.755150.8129480.8129480.8129480.8178910.7727560.8129480.8080680.306715-0.108776-0.162766-0.0668341-0.016728-0.0668341-0.058742-0.0317722-0.01939060.00573778-0.00613588
stds_syphilis-0.1131420.00939828-0.123784-0.01089580.05922430.00182157-0.01373680.2262740.06539860.592548-0.03557880.7829430.306830.7518840.9128270.8925830.7551510.9076660.9076660.9076660.9128270.8386590.9076660.9025720.0687268-0.0655049-0.0498327-0.0598833-0.00947388-0.0598833-0.0492257-0.0675478-0.0901384-0.0498744-0.0799043
stds_pelvic_inflammatory_disease-0.1255180.000914447-0.089917-0.08388030.0213178-0.00604593-0.01421980.246090.09243180.639106-0.02185190.7185630.0534620.8096310.9946110.9735380.8129480.90766610.9892360.9892360.9946110.9076660.9892360.983934-0.0968240.09922160.108406-0.0549592-0.00388986-0.0549592-0.0422092-0.0774244-0.102729-0.0391152-0.0693367
stds_genital_herpes-0.13094-0.00591926-0.0873664-0.08123670.0213178-0.00604593-0.01421980.246090.09095760.639106-0.02185190.7185630.0534620.8096310.9946110.9735380.8129480.9076660.98923610.9892360.9946110.9076660.9892360.983934-0.096824-0.104974-0.100747-0.0549592-0.00388986-0.0549592-0.0422092-0.0774244-0.102729-0.0391152-0.0548761
stds_molluscum_contagiosum-0.128020.000914447-0.0911923-0.07330580.0213178-0.00604593-0.01421980.2384550.09022050.639106-0.02185190.7185630.0534620.8096310.9946110.9735380.8129480.9076660.9892360.98923610.9946110.9076660.9892360.983934-0.096824-0.104974-0.100747-0.0549592-0.00388986-0.0549592-0.0422092-0.0774244-0.102729-0.0391152-0.0693367
stds_aids-0.128618-0.00245086-0.0902938-0.07821360.0229483-0.00498722-0.013540.2446910.1015330.643676-0.01953170.714691nan0.81456810.978870.8178910.9128270.9946110.9946110.99461110.9128270.9946110.989294-0.107953nannan-0.054663-0.00353958-0.054663-0.0417782-0.0770072-0.102056-0.0384481-0.0686891
stds_hiv-0.1182330.00629981-0.0878793-0.06723780.05011780.03301290.01024630.1975980.03246010.608280.009755680.7829430.3842310.7694430.9128270.8925830.7727560.8386590.9076660.9076660.9076660.91282710.9177730.9025720.1237240.1961630.103655-0.05988330.0231711-0.0598833-0.0290559-0.0339209-0.0427495-0.00463948-0.0120118
stds_hepatitis_b-0.13094-0.00364136-0.0886417-0.08123670.03101590.00546104-0.002841110.2384550.09022050.639106-0.02185190.7185630.1183930.8096310.9946110.9735380.8129480.9076660.9892360.9892360.9892360.9946110.91777310.983934-0.0968240.3034170.31756-0.0549592-0.00388986-0.0549592-0.0422092-0.0774244-0.102729-0.0391152-0.0693367
stds_hpv-0.121616-0.000286153-0.0844655-0.08160380.02936010.00260027-0.01463530.2474840.1139620.634591-0.02395380.7224250.07565710.8047580.9892940.9682770.8080680.9025720.9839340.9839340.9839340.9892940.9025720.9839341-0.09745450.2013190.212983-0.00602465-0.00423743-0.00602465-0.0212441-0.0778406-0.1034-0.0397781-0.0699811
stds_number_of_diagnosis-0.001605940.0518996-0.0133320.03415330.1172770.08464670.0333566-0.0621986-0.0384587-0.01351560.007902520.5532970.8972330.315185-0.107953-0.06398460.3067150.0687268-0.096824-0.096824-0.096824-0.1079530.123724-0.096824-0.097454510.0458703-0.157872-0.01542290.00806961-0.0154229-0.002288580.0767870.1308730.05511450.0974489
stds_time_since_first_diagnosis0.4059290.05182510.06377450.2167640.09835110.1591060.1950850.05880560.3178070.1425170.107281nan-0.0654583-0.129216nan-0.141545-0.108776-0.06550490.0992216-0.104974-0.104974nan0.1961630.3034170.2013190.045870310.9309070.2013190.18090.2013190.272221-0.119477-0.01797290.0162567-0.070153
stds_time_since_last_diagnosis0.4851210.07799190.08936970.2762490.0427880.1643450.1996110.1153530.3612430.1765520.130441nan-0.179025-0.182258nan-0.131131-0.162766-0.04983270.108406-0.100747-0.100747nan0.1036550.317560.212983-0.1578720.93090710.2129830.1920680.2129830.288482-0.126042-0.002704680.035399-0.0475845
dx_cancer0.110340.02231640.06728850.03514910.003270070.05623410.1115720.01127790.05471180.0347030.0981127-0.0368568-0.0182556-0.0671068-0.054663-0.055843-0.0668341-0.0598833-0.0549592-0.0549592-0.0549592-0.054663-0.0598833-0.0549592-0.00602465-0.01542290.2013190.2129831-0.01507180.8865080.6656470.1342640.1578120.1134460.160905
dx_cin0.06144340.0156935-0.03262780.0109851-0.0446857-0.0309683-0.0211284-0.004397260.003273170.07852290.01800070.00194911-0.00952577-0.0170003-0.00353958-0.00492466-0.016728-0.00947388-0.00388986-0.00388986-0.00388986-0.003539580.0231711-0.00388986-0.004237430.008069610.18090.192068-0.01507181-0.01507180.606939-0.02123250.00911911-0.02393770.113172
dx_hpv0.1017220.02727290.04396960.0467880.02553770.05884730.1135160.02880780.06322860.01546840.0336469-0.0368568-0.0182556-0.0671068-0.054663-0.055843-0.0668341-0.0598833-0.0549592-0.0549592-0.0549592-0.054663-0.0598833-0.0549592-0.00602465-0.01542290.2013190.2129830.886508-0.015071810.6163270.1342640.1578120.1134460.160905
dx0.09263510.0229920.03575460.0213358-0.0542711-0.049926-0.0340626-0.00724499-0.01344610.1070850.111993-0.0369711-0.0283406-0.0591078-0.0417782-0.0434887-0.058742-0.0492257-0.0422092-0.0422092-0.0422092-0.0417782-0.0290559-0.0422092-0.0212441-0.002288580.2722210.2884820.6656470.6069390.61632710.07221480.09895210.088740.157607
hinselmann-0.00396685-0.0398474-0.01654870.04043870.03956160.07225130.02704350.012360.0389448-0.01614450.00799402-0.02161670.0653491-0.0323222-0.0770072-0.0786695-0.0317722-0.0675478-0.0774244-0.0774244-0.0774244-0.0770072-0.0339209-0.0774244-0.07784060.076787-0.119477-0.1260420.134264-0.02123250.1342640.072214810.6502490.1924670.547417
schiller0.103283-0.008966950.003494750.09201730.05991270.09589040.0181912-0.03400240.0792473-0.01226850.07941530.00132040.120725-0.0202843-0.102056-0.104734-0.0193906-0.0901384-0.102729-0.102729-0.102729-0.102056-0.0427495-0.102729-0.10340.130873-0.0179729-0.002704680.1578120.009119110.1578120.09895210.65024910.3614860.733204
citology-0.01686210.0218576-0.0109732-0.03003620.000370976-0.006827070.00466553-0.02511590.0762632-0.02819930.00271470.00726220.06000950.00500721-0.0384481-0.04109140.00573778-0.0498744-0.0391152-0.0391152-0.0391152-0.0384481-0.00463948-0.0391152-0.03977810.05511450.01625670.0353990.113446-0.02393770.1134460.088740.1924670.36148610.327466
biopsy0.0559555-0.001442450.007264370.04641590.02973280.06204420.0248819-0.01801530.0793876-0.009234330.03327530.02556480.0983473-0.00692478-0.0686891-0.0712605-0.00613588-0.0799043-0.0693367-0.0548761-0.0693367-0.0686891-0.0120118-0.0693367-0.06998110.0974489-0.070153-0.04758450.1609050.1131720.1609050.1576070.5474170.7332040.3274661
" ], "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "corr = cervical_cancer_data.corr()\n", "corr.style.background_gradient()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stds_genital_herpesFalseTrue
dx_cancer
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" ], "text/plain": [ "stds_genital_herpes False True \n", "dx_cancer \n", "False 734 106\n", "True 18 0" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(cervical_cancer_data['dx_cancer'], cervical_cancer_data['stds_genital_herpes'])" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "age 0\n", "number_of_sexual_partners 26\n", "first_sexual_intercourse 7\n", "num_of_pregnancies 56\n", "smokes 0\n", "smokes_years 13\n", "smokes_packs_year 13\n", "hormonal_contraceptives 0\n", "hormonal_contraceptives_years 108\n", "iud 0\n", "iud_years 117\n", "stds 0\n", "stds_number 105\n", "stds_condylomatosis 0\n", "stds_cervical_condylomatosis 0\n", "stds_vaginal_condylomatosis 0\n", "stds_vulvo_perineal_condylomatosis 0\n", "stds_syphilis 0\n", "stds_pelvic_inflammatory_disease 0\n", "stds_genital_herpes 0\n", "stds_molluscum_contagiosum 0\n", "stds_aids 0\n", "stds_hiv 0\n", "stds_hepatitis_b 0\n", "stds_hpv 0\n", "stds_number_of_diagnosis 0\n", "stds_time_since_first_diagnosis 787\n", "stds_time_since_last_diagnosis 787\n", "dx_cancer 0\n", "dx_cin 0\n", "dx_hpv 0\n", "dx 0\n", "hinselmann 0\n", "schiller 0\n", "citology 0\n", "biopsy 0\n", "dtype: int64" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cervical_cancer_data.isna().sum()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }