diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..c059800 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,23 @@ +# Nasz obraz będzie dzidziczył z obrazu Ubuntu w wersji latest +FROM ubuntu:latest + +# Instalujemy niezbędne zależności. Zwróć uwagę na flagę "-y" (assume yes) +RUN apt update && apt install -y git +RUN apt install -y python3-pip +RUN apt install -y curl +RUN pip3 install --user wget +RUN pip3 install --user kaggle +RUN pip3 install --user seaborn +RUN pip3 install --user sklearn +RUN pip3 install --user pandas +RUN pip3 install --user matplotlib + +# Stwórzmy w kontenerze (jeśli nie istnieje) katalog /app i przejdźmy do niego (wszystkie kolejne polecenia RUN, CMD, ENTRYPOINT, COPY i ADD będą w nim wykonywane) +WORKDIR /app + +# Skopiujmy nasz skrypt do katalogu /app w kontenerze +COPY ./test.sh ./ +COPY ./Python_file.py ./ + +# Domyślne polecenie, które zostanie uruchomione w kontenerze po jego starcie +CMD ./test.sh \ No newline at end of file diff --git a/Jenkinsfile b/Jenkinsfile index 39da665..9ee5562 100644 --- a/Jenkinsfile +++ b/Jenkinsfile @@ -1,5 +1,7 @@ pipeline { - agent any + agent { + dockerfile true + } //Definijuemy parametry, które będzie można podać podczas wywoływania zadania parameters { string ( @@ -9,6 +11,12 @@ pipeline { trim: false ) } + stages { + stage('Test') { + steps { + sh 'cat /etc/issue' + } + } stages { // 4. Repozytorium [2 pkt] stage('checkout: Check out from version control') { diff --git a/Zajęcia4/Dockerfile b/Zajęcia4/Dockerfile index 4c1f891..c059800 100644 --- a/Zajęcia4/Dockerfile +++ b/Zajęcia4/Dockerfile @@ -5,6 +5,7 @@ FROM ubuntu:latest RUN apt update && apt install -y git RUN apt install -y python3-pip RUN apt install -y curl +RUN pip3 install --user wget RUN pip3 install --user kaggle RUN pip3 install --user seaborn RUN pip3 install --user sklearn @@ -16,4 +17,7 @@ WORKDIR /app # Skopiujmy nasz skrypt do katalogu /app w kontenerze COPY ./test.sh ./ -COPY ./IUM_1_434788.ipynb ./ \ No newline at end of file +COPY ./Python_file.py ./ + +# Domyślne polecenie, które zostanie uruchomione w kontenerze po jego starcie +CMD ./test.sh \ No newline at end of file diff --git a/Zajęcia4/IUM_1_434788.ipynb b/Zajęcia4/IUM_1_434788.ipynb deleted file mode 100644 index 31e0c66..0000000 --- a/Zajęcia4/IUM_1_434788.ipynb +++ /dev/null @@ -1,3306 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "IUM_1_434788.ipynb", - "provenance": [], - "collapsed_sections": [], - "toc_visible": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - } - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "shaFKPEixPn4" - }, - "source": [ - "# 1. Pobranie zbioru danych z Repozytorium" - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "-03GDjWtxD7W", - "outputId": "3cefd33d-3ef4-4c16-963e-ffa6e9e781de" - }, - "source": [ - "!curl -OL https://git.wmi.amu.edu.pl/s434788/ium_434788/raw/branch/master/winequality-red.csv" - ], - "execution_count": 1, - "outputs": [ - { - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 98k 0 98k 0 0 74502 0 --:--:-- 0:00:01 --:--:-- 74502\n" - ], - "name": "stdout" - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 419 - }, - "id": "sAUNi0ylxWUm", - "outputId": "fe879388-072d-4845-f3b5-f06a4fca5f1e" - }, - "source": [ - "import pandas as pd\n", - "wine=pd.read_csv('winequality-red.csv')\n", - "wine" - ], - "execution_count": 2, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
07.40.7000.001.90.07611.034.00.997803.510.569.45
17.80.8800.002.60.09825.067.00.996803.200.689.85
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.......................................
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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid ... sulphates alcohol quality\n", - "0 7.4 0.700 0.00 ... 0.56 9.4 5\n", - "1 7.8 0.880 0.00 ... 0.68 9.8 5\n", - "2 7.8 0.760 0.04 ... 0.65 9.8 5\n", - "3 11.2 0.280 0.56 ... 0.58 9.8 6\n", - "4 7.4 0.700 0.00 ... 0.56 9.4 5\n", - "... ... ... ... ... ... ... ...\n", - "1594 6.2 0.600 0.08 ... 0.58 10.5 5\n", - "1595 5.9 0.550 0.10 ... 0.76 11.2 6\n", - "1596 6.3 0.510 0.13 ... 0.75 11.0 6\n", - "1597 5.9 0.645 0.12 ... 0.71 10.2 5\n", - "1598 6.0 0.310 0.47 ... 0.66 11.0 6\n", - "\n", - "[1599 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 2 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4H-i6DJlxduP" - }, - "source": [ - "# 2. Podział na zbiory test/train przy pomocy SciKit + (poprawka z 26.03.2021 przy pomocy basha)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Rf49qKC-eqEU" - }, - "source": [ - "## 2.1 SciKit" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nZO_naLatT0o" - }, - "source": [ - "Próbowałem również podzielić na podzbiory Train:Dev:Test 6:2:2 Przy pomocy basha ale uznałem, że wygodniejsze jest korzystanie z \"train_test_split()\". Docelowo podział będzie dokonywany na 4 zmienne ` X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)`, jednak chciałem zachować konwencje z przykładu, z ćwiczeń." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ebHl5Aw1uuK1" - }, - "source": [ - "https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "X88VMhb0x3gJ" - }, - "source": [ - "from sklearn.model_selection import train_test_split\n", - "\n", - "wine_train, wine_test = train_test_split(wine, test_size=360,train_size=959, random_state=1)" - ], - "execution_count": 3, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "OzjEfgNOyAWs", - "outputId": "7e7bb70f-2b1e-422c-9500-d411884d8d5a" - }, - "source": [ - "wine_test[\"quality\"].value_counts()" - ], - "execution_count": 4, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "5 155\n", - "6 149\n", - "7 37\n", - "4 16\n", - "8 2\n", - "3 1\n", - "Name: quality, dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 4 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "SpQZIuSxyAd0", - "outputId": "96505a9a-d2e7-44a1-b2cf-ee40d6d7d3d0" - }, - "source": [ - "wine_train[\"quality\"].value_counts()" - ], - "execution_count": 5, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "5 400\n", - "6 388\n", - "7 125\n", - "4 30\n", - "8 11\n", - "3 5\n", - "Name: quality, dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 5 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YK0491tAeupD" - }, - "source": [ - "## 2.2 Bash" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "1idNUz-9eyfJ" - }, - "source": [ - "!head -n 1 winequality-red.csv > header.csv\n", - "!tail -n +2 winequality-red.csv | shuf > data.shuffled\n", - "\n", - "!head -n 266 data.shuffled > wine.data.test\n", - "!head -n 532 data.shuffled | tail -n 266 > wine.data.dev\n", - "!tail -n +333 data.shuffled > wine.data.train\n", - "\n", - "!cat header.csv wine.data.test > test.csv\n", - "!cat header.csv wine.data.dev > dev.csv\n", - "!cat header.csv wine.data.train > train.csv" - ], - "execution_count": 6, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "-C4RRDH2fFEp", - "outputId": "93944a72-838c-4e2b-a907-de4b0902fcb1" - }, - "source": [ - "!wc -l test.csv\n", - "!wc -l dev.csv\n", - "!wc -l train.csv" - ], - "execution_count": 7, - "outputs": [ - { - "output_type": "stream", - "text": [ - "267 test.csv\n", - "267 dev.csv\n", - "1268 train.csv\n" - ], - "name": "stdout" - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "wLlI-k_jfb70" - }, - "source": [ - "wine_test_bash=pd.read_csv('test.csv')\n", - "wine_dev_bash=pd.read_csv('dev.csv')\n", - "wine_train_bash=pd.read_csv('train.csv')" - ], - "execution_count": 8, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wAq8KmNdyNOm" - }, - "source": [ - "# 3. Statystyki dla zbiorów" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "Wcq9YSTfXbs1" - }, - "source": [ - "from matplotlib import pyplot as plt\n", - "import seaborn as sns" - ], - "execution_count": 9, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EjDFpgdPy_of" - }, - "source": [ - "## 3.1. Zbiór Train (bash)" - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 419 - }, - "id": "SscUak3AydG0", - "outputId": "5f0bd8df-1753-4211-e3a6-8ce2685146f9" - }, - "source": [ - "wine_train_bash" - ], - "execution_count": 10, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
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48.30.5600.222.40.08210.086.00.998303.370.629.55
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
count1267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.0000001267.000000
mean8.3441990.5258880.2738912.5740330.08741915.88989746.1460140.9967993.3100160.65573010.3967255.632991
std1.7892530.1778040.1961411.4534630.04675410.60367432.7348180.0018930.1540470.1662061.0423530.806931
min4.7000000.1200000.0000000.9000000.0120001.0000006.0000000.9900702.7400000.3700008.4000003.000000
25%7.1000000.3900000.0900001.9000000.0710007.00000022.0000000.9956603.2100000.5500009.5000005.000000
50%7.9000000.5200000.2600002.2000000.08000013.00000037.0000000.9968003.3100000.62000010.2000006.000000
75%9.3000000.6400000.4300002.6000000.09000022.00000062.0000000.9978703.4000000.73000011.0000006.000000
max15.9000001.5800001.00000015.5000000.61100072.000000278.0000001.0036904.0100002.00000014.9000008.000000
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" - ], - "text/plain": [ - " fixed acidity volatile acidity ... alcohol quality\n", - "count 1267.000000 1267.000000 ... 1267.000000 1267.000000\n", - "mean 8.344199 0.525888 ... 10.396725 5.632991\n", - "std 1.789253 0.177804 ... 1.042353 0.806931\n", - "min 4.700000 0.120000 ... 8.400000 3.000000\n", - "25% 7.100000 0.390000 ... 9.500000 5.000000\n", - "50% 7.900000 0.520000 ... 10.200000 6.000000\n", - "75% 9.300000 0.640000 ... 11.000000 6.000000\n", - "max 15.900000 1.580000 ... 14.900000 8.000000\n", - "\n", - "[8 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 12 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JWXJ2CZQuylE" - }, - "source": [ - "Testowy Wykres (quality, volatile acidity)" - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 408 - }, - "id": "HbsfwCL7XpNe", - "outputId": "249d8110-1b17-41ad-e1b1-18b0aa12ff06" - }, - "source": [ - "fig = plt.figure(figsize = (10,6))\n", - "sns.barplot(x = 'quality', y = 'volatile acidity', data = wine_train_bash)" - ], - "execution_count": 13, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 13 - }, - { - "output_type": "display_data", - "data": { - "image/png": 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\n", 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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
count266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000
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75%9.1000000.6300000.4000002.5000000.09200021.00000062.7500000.9976003.4000000.75000011.4000006.000000
max13.3000001.3300000.7400008.8000000.46700051.000000289.0000001.0026003.9000001.98000014.0000008.000000
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plt.figure(figsize = (10,6))\n", - "sns.barplot(x = 'quality', y = 'volatile acidity', data = wine_test_bash)" - ], - "execution_count": 17, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 17 - }, - { - "output_type": "display_data", - "data": { - "image/png": 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1599 rows × 12 columns

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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid ... sulphates alcohol quality\n", - "0 7.4 0.700 0.00 ... 0.56 9.4 5\n", - "1 7.8 0.880 0.00 ... 0.68 9.8 5\n", - "2 7.8 0.760 0.04 ... 0.65 9.8 5\n", - "3 11.2 0.280 0.56 ... 0.58 9.8 6\n", - "4 7.4 0.700 0.00 ... 0.56 9.4 5\n", - "... ... ... ... ... ... ... ...\n", - "1594 6.2 0.600 0.08 ... 0.58 10.5 5\n", - "1595 5.9 0.550 0.10 ... 0.76 11.2 6\n", - "1596 6.3 0.510 0.13 ... 0.75 11.0 6\n", - "1597 5.9 0.645 0.12 ... 0.71 10.2 5\n", - "1598 6.0 0.310 0.47 ... 0.66 11.0 6\n", - "\n", - "[1599 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 18 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Ua_ctPpVzeKJ", - "outputId": "da95e47b-9e44-42e0-efc0-66631dba99f1" - }, - "source": [ - "wine[\"quality\"].value_counts()" - ], - "execution_count": 19, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "5 681\n", - "6 638\n", - "7 199\n", - "4 53\n", - "8 18\n", - "3 10\n", - "Name: quality, dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 19 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 297 - }, - "id": "-06v1i7XzeOz", - "outputId": "b0da7e9b-98aa-4af6-8131-359a54c2ac69" - }, - "source": [ - "wine.describe(include='all')" - ], - "execution_count": 20, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
count1599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.0000001599.000000
mean8.3196370.5278210.2709762.5388060.08746715.87492246.4677920.9967473.3111130.65814910.4229835.636023
std1.7410960.1790600.1948011.4099280.04706510.46015732.8953240.0018870.1543860.1695071.0656680.807569
min4.6000000.1200000.0000000.9000000.0120001.0000006.0000000.9900702.7400000.3300008.4000003.000000
25%7.1000000.3900000.0900001.9000000.0700007.00000022.0000000.9956003.2100000.5500009.5000005.000000
50%7.9000000.5200000.2600002.2000000.07900014.00000038.0000000.9967503.3100000.62000010.2000006.000000
75%9.2000000.6400000.4200002.6000000.09000021.00000062.0000000.9978353.4000000.73000011.1000006.000000
max15.9000001.5800001.00000015.5000000.61100072.000000289.0000001.0036904.0100002.00000014.9000008.000000
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" - ], - "text/plain": [ - " fixed acidity volatile acidity ... alcohol quality\n", - "count 1599.000000 1599.000000 ... 1599.000000 1599.000000\n", - "mean 8.319637 0.527821 ... 10.422983 5.636023\n", - "std 1.741096 0.179060 ... 1.065668 0.807569\n", - "min 4.600000 0.120000 ... 8.400000 3.000000\n", - "25% 7.100000 0.390000 ... 9.500000 5.000000\n", - "50% 7.900000 0.520000 ... 10.200000 6.000000\n", - "75% 9.200000 0.640000 ... 11.100000 6.000000\n", - "max 15.900000 1.580000 ... 14.900000 8.000000\n", - "\n", - "[8 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 20 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "t8Y53QPyu_fO" - }, - "source": [ - "Testowy Wykres (quality, volatile acidity)" - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 405 - }, - "id": "hEe3BYcJaKnF", - "outputId": "cd03275d-d09e-4517-ef76-22b40d9ffa9e" - }, - "source": [ - "fig = plt.figure(figsize = (10,6))\n", - "sns.barplot(x = 'quality', y = 'volatile acidity', data = wine)" - ], - "execution_count": 21, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 21 - }, - { - "output_type": "display_data", - "data": { - "image/png": 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266 rows × 12 columns

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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid ... sulphates alcohol quality\n", - "0 8.0 0.705 0.05 ... 0.95 10.5 6\n", - "1 7.6 0.665 0.10 ... 0.51 9.3 5\n", - "2 7.8 0.550 0.35 ... 0.56 9.2 5\n", - "3 13.0 0.320 0.65 ... 0.61 10.6 5\n", - "4 8.8 0.610 0.30 ... 0.51 9.3 4\n", - ".. ... ... ... ... ... ... ...\n", - "261 13.8 0.490 0.67 ... 0.93 12.0 6\n", - "262 7.1 0.750 0.01 ... 0.40 12.8 6\n", - "263 9.9 0.350 0.41 ... 0.50 9.5 5\n", - "264 6.5 0.520 0.11 ... 0.52 9.3 5\n", - "265 6.8 0.670 0.00 ... 0.74 9.7 5\n", - "\n", - "[266 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 22 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "lhRktuxPgOsC", - "outputId": "612e6163-0b66-4495-fdc1-2a0813efe37e" - }, - "source": [ - "wine_dev_bash[\"quality\"].value_counts()" - ], - "execution_count": 23, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "5 115\n", - "6 113\n", - "7 24\n", - "4 9\n", - "8 3\n", - "3 2\n", - "Name: quality, dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 23 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 297 - }, - "id": "FmOQIZMSgOnK", - "outputId": "a7f4b4e8-36a0-4a07-cce4-98caa71ff7d0" - }, - "source": [ - "wine_dev_bash.describe(include='all')" - ], - "execution_count": 24, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
count266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000266.000000
mean8.2736840.5400750.2530082.5233080.08862015.39849643.9736840.9967493.3178950.64977410.4533215.590226
std1.7205920.1938560.1903301.3804980.05582510.00221930.5187120.0019300.1520030.1769301.0580100.777841
min4.9000000.1200000.0000001.3000000.0120001.0000008.0000000.9906402.8700000.3300008.5000003.000000
25%7.1000000.3962500.0800001.9000000.0682508.00000020.0000000.9955253.2100000.5425009.5000005.000000
50%7.9000000.5200000.2400002.2000000.07900013.00000037.0000000.9967203.3200000.62000010.2000006.000000
75%9.2000000.6487500.3900002.6000000.09000020.00000060.0000000.9978773.4300000.72000011.2000006.000000
max15.6000001.5800000.76000013.8000000.61100066.000000141.0000001.0031503.7200001.95000014.0000008.000000
\n", - "
" - ], - "text/plain": [ - " fixed acidity volatile acidity ... alcohol quality\n", - "count 266.000000 266.000000 ... 266.000000 266.000000\n", - "mean 8.273684 0.540075 ... 10.453321 5.590226\n", - "std 1.720592 0.193856 ... 1.058010 0.777841\n", - "min 4.900000 0.120000 ... 8.500000 3.000000\n", - "25% 7.100000 0.396250 ... 9.500000 5.000000\n", - "50% 7.900000 0.520000 ... 10.200000 6.000000\n", - "75% 9.200000 0.648750 ... 11.200000 6.000000\n", - "max 15.600000 1.580000 ... 14.000000 8.000000\n", - "\n", - "[8 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 24 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 405 - }, - "id": "j3Z6noeZgOjC", - "outputId": "de24703b-50d4-4059-d5e6-ddc0c0f3356c" - }, - "source": [ - "fig = plt.figure(figsize = (10,6))\n", - "sns.barplot(x = 'quality', y = 'volatile acidity', data = wine_dev_bash)" - ], - "execution_count": 25, - "outputs": [ 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\n", 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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
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.......................................
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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid ... sulphates alcohol quality\n", - "0 7.4 0.700 0.00 ... 0.56 9.4 8.0\n", - "1 7.8 0.880 0.00 ... 0.68 9.8 8.0\n", - "2 7.8 0.760 0.04 ... 0.65 9.8 8.0\n", - "3 11.2 0.280 0.56 ... 0.58 9.8 12.0\n", - "4 7.4 0.700 0.00 ... 0.56 9.4 8.0\n", - "... ... ... ... ... ... ... ...\n", - "1594 6.2 0.600 0.08 ... 0.58 10.5 8.0\n", - "1595 5.9 0.550 0.10 ... 0.76 11.2 12.0\n", - "1596 6.3 0.510 0.13 ... 0.75 11.0 12.0\n", - "1597 5.9 0.645 0.12 ... 0.71 10.2 8.0\n", - "1598 6.0 0.310 0.47 ... 0.66 11.0 12.0\n", - "\n", - "[1599 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 27 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "I1AwZoyN4RHs", - "outputId": "15a7bca4-8bbe-4749-80b8-5eede667aa07" - }, - "source": [ - "wine[\"quality\"].value_counts()" - ], - "execution_count": 28, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "8.0 681\n", - "12.0 638\n", - "16.0 199\n", - "4.0 53\n", - "20.0 18\n", - "0.0 10\n", - "Name: quality, dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 28 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XBU3z_of414w" - }, - "source": [ - "# 5. Usuwanie artefaktów" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "KCstRwQp5-X1" - }, - "source": [ - "### Całe szczęscie nie ma w moim zbiorze ani pustych linijek, ani przykładów z niepoprawnymi wartościami" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "EJqksTP545UV" - }, - "source": [ - "# Znajdźmy pustą linijkę:\n", - "! grep -P \"^$\" -n winequality-red.csv" - ], - "execution_count": 29, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8DuoPn3Fa0kP" - }, - "source": [ - "Szukanie wartości \"NA\": https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html" - ] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "REYF2AWjz_lr", - "outputId": "01c5cd70-a37e-433f-bde3-d0c855c96c2e" - }, - "source": [ - "wine.isnull().sum()" - ], - "execution_count": 30, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "fixed acidity 0\n", - "volatile acidity 0\n", - "citric acid 0\n", - "residual sugar 0\n", - "chlorides 0\n", - "free sulfur dioxide 0\n", - "total sulfur dioxide 0\n", - "density 0\n", - "pH 0\n", - "sulphates 0\n", - "alcohol 0\n", - "quality 0\n", - "dtype: int64" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 30 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "RbkqNj9_akcU" - }, - "source": [ - "wine.dropna(inplace=True) " - ], - "execution_count": 31, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 419 - }, - "id": "4WylJo9malyG", - "outputId": "95a9b3f4-a7f5-4f61-fdbe-918dbca2d72c" - }, - "source": [ - "wine" - ], - "execution_count": 32, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
07.40.7000.001.90.07611.034.00.997803.510.569.48.0
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.......................................
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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid ... sulphates alcohol quality\n", - "0 7.4 0.700 0.00 ... 0.56 9.4 8.0\n", - "1 7.8 0.880 0.00 ... 0.68 9.8 8.0\n", - "2 7.8 0.760 0.04 ... 0.65 9.8 8.0\n", - "3 11.2 0.280 0.56 ... 0.58 9.8 12.0\n", - "4 7.4 0.700 0.00 ... 0.56 9.4 8.0\n", - "... ... ... ... ... ... ... ...\n", - "1594 6.2 0.600 0.08 ... 0.58 10.5 8.0\n", - "1595 5.9 0.550 0.10 ... 0.76 11.2 12.0\n", - "1596 6.3 0.510 0.13 ... 0.75 11.0 12.0\n", - "1597 5.9 0.645 0.12 ... 0.71 10.2 8.0\n", - "1598 6.0 0.310 0.47 ... 0.66 11.0 12.0\n", - "\n", - "[1599 rows x 12 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 32 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "iqsJ9Bfngy-m" - }, - "source": [ - "" - ], - "execution_count": null, - "outputs": [] - } - ] -} \ No newline at end of file diff --git a/Zajęcia4/test.sh b/Zajęcia4/test.sh index cb12447..0efedce 100644 --- a/Zajęcia4/test.sh +++ b/Zajęcia4/test.sh @@ -1,19 +1,2 @@ -# 5. Zapisanie zbioru danych [4 pkt] (Pobranie pliku .csv) -curl -OL https://git.wmi.amu.edu.pl/s434788/ium_434788/raw/branch/master/winequality-red.csv - - -# 5. Zapisanie zbioru danych [4 pkt] (Podzielenie pliku csv na test/dev/train) -head -n 1 winequality-red.csv > header.csv -tail -n +2 winequality-red.csv | shuf > data.shuffled - -head -n 266 data.shuffled > wine.data.test -head -n 532 data.shuffled | tail -n 266 > wine.data.dev -tail -n +333 data.shuffled > wine.data.train - -cat header.csv wine.data.test > test.csv -cat header.csv wine.data.dev > dev.csv -cat header.csv wine.data.train > train.csv - -# 7. Parametry zadania [1 pkt] -head -n $1 data.shuffled > zadanie7.data -cat header.csv zadanie7.data > Final_file.csv \ No newline at end of file +#Uruchomienie skryptu i wyświetlenie 10 pierwszych wierszy wyjściowej tabeli +python3 Python_file.py \ No newline at end of file diff --git a/Zajęcia4/winequality-red.csv b/Zajęcia4/winequality-red.csv deleted file mode 100644 index 62e674c..0000000 --- a/Zajęcia4/winequality-red.csv +++ /dev/null @@ -1,1600 +0,0 @@ -fixed acidity,volatile acidity,citric acid,residual sugar,chlorides,free sulfur dioxide,total sulfur dioxide,density,pH,sulphates,alcohol,quality -7.4,0.7,0.0,1.9,0.076,11.0,34.0,0.9978,3.51,0.56,9.4,5 -7.8,0.88,0.0,2.6,0.098,25.0,67.0,0.9968,3.2,0.68,9.8,5 -7.8,0.76,0.04,2.3,0.092,15.0,54.0,0.997,3.26,0.65,9.8,5 -11.2,0.28,0.56,1.9,0.075,17.0,60.0,0.998,3.16,0.58,9.8,6 -7.4,0.7,0.0,1.9,0.076,11.0,34.0,0.9978,3.51,0.56,9.4,5 -7.4,0.66,0.0,1.8,0.075,13.0,40.0,0.9978,3.51,0.56,9.4,5 -7.9,0.6,0.06,1.6,0.069,15.0,59.0,0.9964,3.3,0.46,9.4,5 -7.3,0.65,0.0,1.2,0.065,15.0,21.0,0.9946,3.39,0.47,10.0,7 -7.8,0.58,0.02,2.0,0.073,9.0,18.0,0.9968,3.36,0.57,9.5,7 -7.5,0.5,0.36,6.1,0.071,17.0,102.0,0.9978,3.35,0.8,10.5,5 -6.7,0.58,0.08,1.8,0.09699999999999999,15.0,65.0,0.9959,3.28,0.54,9.2,5 -7.5,0.5,0.36,6.1,0.071,17.0,102.0,0.9978,3.35,0.8,10.5,5 -5.6,0.615,0.0,1.6,0.08900000000000001,16.0,59.0,0.9943,3.58,0.52,9.9,5 -7.8,0.61,0.29,1.6,0.114,9.0,29.0,0.9974,3.26,1.56,9.1,5 -8.9,0.62,0.18,3.8,0.17600000000000002,52.0,145.0,0.9986,3.16,0.88,9.2,5 -8.9,0.62,0.19,3.9,0.17,51.0,148.0,0.9986,3.17,0.93,9.2,5 -8.5,0.28,0.56,1.8,0.092,35.0,103.0,0.9969,3.3,0.75,10.5,7 -8.1,0.56,0.28,1.7,0.368,16.0,56.0,0.9968,3.11,1.28,9.3,5 -7.4,0.59,0.08,4.4,0.086,6.0,29.0,0.9974,3.38,0.5,9.0,4 -7.9,0.32,0.51,1.8,0.341,17.0,56.0,0.9969,3.04,1.08,9.2,6 -8.9,0.22,0.48,1.8,0.077,29.0,60.0,0.9968,3.39,0.53,9.4,6 -7.6,0.39,0.31,2.3,0.08199999999999999,23.0,71.0,0.9982,3.52,0.65,9.7,5 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