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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
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2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
.......................................
88688702Montvila, Rev. Juozasmale27.00021153613.0000NaNS
88788811Graham, Miss. Margaret Edithfemale19.00011205330.0000B42S
88888903Johnston, Miss. Catherine Helen \"Carrie\"femaleNaN12W./C. 660723.4500NaNS
88989011Behr, Mr. Karl Howellmale26.00011136930.0000C148C
89089103Dooley, Mr. Patrickmale32.0003703767.7500NaNQ
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
88688702Montvila, Rev. Juozasmale27.00021153613.00NaNS
88788811Graham, Miss. Margaret Edithfemale19.00011205330.00B42S
88888903Johnston, Miss. Catherine Helen \"Carrie\"femaleNaN12W./C. 660723.45NaNS
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89089103Dooley, Mr. Patrickmale32.0003703767.75NaNQ
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PassengerIdSurvivedPclassAgeSibSpParchFare
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mean446.0000000.3838382.30864229.6991180.5230080.38159432.204208
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" ], "text/plain": [ " PassengerId Survived Pclass Age SibSp \\\n", "count 891.000000 891.000000 891.000000 714.000000 891.000000 \n", "mean 446.000000 0.383838 2.308642 29.699118 0.523008 \n", "std 257.353842 0.486592 0.836071 14.526497 1.102743 \n", "min 1.000000 0.000000 1.000000 0.420000 0.000000 \n", "25% 223.500000 0.000000 2.000000 20.125000 0.000000 \n", "50% 446.000000 0.000000 3.000000 28.000000 0.000000 \n", "75% 668.500000 1.000000 3.000000 38.000000 1.000000 \n", "max 891.000000 1.000000 3.000000 80.000000 8.000000 \n", "\n", " Parch Fare \n", "count 891.000000 891.000000 \n", "mean 0.381594 32.204208 \n", "std 0.806057 49.693429 \n", "min 0.000000 0.000000 \n", "25% 0.000000 7.910400 \n", "50% 0.000000 14.454200 \n", "75% 0.000000 31.000000 \n", "max 6.000000 512.329200 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.describe()" ] }, { "cell_type": "code", "execution_count": 8, "id": "e633b90d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 891 entries, 0 to 890\n", "Data columns (total 12 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 PassengerId 891 non-null int64 \n", " 1 Survived 891 non-null int64 \n", " 2 Pclass 891 non-null int64 \n", " 3 Name 891 non-null object \n", " 4 Sex 891 non-null object \n", " 5 Age 714 non-null float64\n", " 6 SibSp 891 non-null int64 \n", " 7 Parch 891 non-null int64 \n", " 8 Ticket 891 non-null object \n", " 9 Fare 891 non-null float64\n", " 10 Cabin 204 non-null object \n", " 11 Embarked 889 non-null object \n", "dtypes: float64(2), int64(5), object(5)\n", "memory usage: 83.7+ KB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 9, "id": "765b50c7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(891, 12)" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.shape" ] }, { "cell_type": "code", "execution_count": 10, "id": "515323e4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "177" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Age'].isnull().sum()" ] }, { "cell_type": "code", "execution_count": 11, "id": "a1cef447", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "687" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Cabin'].isnull().sum()" ] }, { "cell_type": "code", "execution_count": 12, "id": "4abd09a3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PassengerIdSurvivedPclassAgeSibSpParchFare
count891.000000891.000000891.000000714.000000891.000000891.000000891.000000
mean446.0000000.3838382.30864229.6991180.5230080.38159432.204208
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min1.0000000.0000001.0000000.4200000.0000000.0000000.000000
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" ], "text/plain": [ " PassengerId Survived Pclass Age SibSp \\\n", "count 891.000000 891.000000 891.000000 714.000000 891.000000 \n", "mean 446.000000 0.383838 2.308642 29.699118 0.523008 \n", "std 257.353842 0.486592 0.836071 14.526497 1.102743 \n", "min 1.000000 0.000000 1.000000 0.420000 0.000000 \n", "25% 223.500000 0.000000 2.000000 20.125000 0.000000 \n", "50% 446.000000 0.000000 3.000000 28.000000 0.000000 \n", "75% 668.500000 1.000000 3.000000 38.000000 1.000000 \n", "max 891.000000 1.000000 3.000000 80.000000 8.000000 \n", "\n", " Parch Fare \n", "count 891.000000 891.000000 \n", "mean 0.381594 32.204208 \n", "std 0.806057 49.693429 \n", "min 0.000000 0.000000 \n", "25% 0.000000 7.910400 \n", "50% 0.000000 14.454200 \n", "75% 0.000000 31.000000 \n", "max 6.000000 512.329200 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.describe()" ] }, { "cell_type": "code", "execution_count": 13, "id": "887204c0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 891 entries, 0 to 890\n", "Data columns (total 12 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 PassengerId 891 non-null int64 \n", " 1 Survived 891 non-null int64 \n", " 2 Pclass 891 non-null int64 \n", " 3 Name 891 non-null object \n", " 4 Sex 891 non-null object \n", " 5 Age 714 non-null float64\n", " 6 SibSp 891 non-null int64 \n", " 7 Parch 891 non-null int64 \n", " 8 Ticket 891 non-null object \n", " 9 Fare 891 non-null float64\n", " 10 Cabin 204 non-null object \n", " 11 Embarked 889 non-null object \n", "dtypes: float64(2), int64(5), object(5)\n", "memory usage: 83.7+ KB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 14, "id": "5376bb3f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "PassengerId int64\n", "Survived int64\n", "Pclass int64\n", "Name object\n", "Sex object\n", "Age float64\n", "SibSp int64\n", "Parch int64\n", "Ticket object\n", "Fare float64\n", "Cabin object\n", "Embarked object\n", "dtype: object" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.dtypes" ] }, { "cell_type": "code", "execution_count": 16, "id": "cd865b01", "metadata": {}, "outputs": [], "source": [ "def impute_age(cols):\n", " Age = cols[0]\n", " Pclass = cols[1]\n", " if pd.isnull(Age):\n", " if Pclass == 1:\n", " return 37\n", " elif Pclass == 2:\n", " return 29\n", " else:\n", " return 24\n", " \n", " else:\n", " return Age" ] }, { "cell_type": "code", "execution_count": 17, "id": "c78800c8", "metadata": {}, "outputs": [], "source": [ "df['Age']=df[['Age','Pclass']].apply(impute_age,axis=1)" ] }, { "cell_type": "code", "execution_count": 18, "id": "f9f2e2c9", "metadata": {}, "outputs": [], "source": [ "df.drop('Cabin',axis=1,inplace=True)" ] }, { "cell_type": "code", "execution_count": 22, "id": "85fbe6fd", "metadata": {}, "outputs": [], "source": [ "df.dropna(inplace=True)" ] }, { "cell_type": "code", "execution_count": 23, "id": "94bc3598", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500S
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250S
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000S
4503Allen, Mr. William Henrymale35.0003734508.0500S
....................................
88688702Montvila, Rev. Juozasmale27.00021153613.0000S
88788811Graham, Miss. Margaret Edithfemale19.00011205330.0000S
88888903Johnston, Miss. Catherine Helen \"Carrie\"female24.012W./C. 660723.4500S
88989011Behr, Mr. Karl Howellmale26.00011136930.0000C
89089103Dooley, Mr. Patrickmale32.0003703767.7500Q
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889 rows × 11 columns

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" ], "text/plain": [ " PassengerId Survived Pclass \\\n", "0 1 0 3 \n", "1 2 1 1 \n", "2 3 1 3 \n", "3 4 1 1 \n", "4 5 0 3 \n", ".. ... ... ... \n", "886 887 0 2 \n", "887 888 1 1 \n", "888 889 0 3 \n", "889 890 1 1 \n", "890 891 0 3 \n", "\n", " Name Sex Age SibSp \\\n", "0 Braund, Mr. Owen Harris male 22.0 1 \n", "1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n", "2 Heikkinen, Miss. Laina female 26.0 0 \n", "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", "4 Allen, Mr. William Henry male 35.0 0 \n", ".. ... ... ... ... \n", "886 Montvila, Rev. Juozas male 27.0 0 \n", "887 Graham, Miss. Margaret Edith female 19.0 0 \n", "888 Johnston, Miss. Catherine Helen \"Carrie\" female 24.0 1 \n", "889 Behr, Mr. Karl Howell male 26.0 0 \n", "890 Dooley, Mr. Patrick male 32.0 0 \n", "\n", " Parch Ticket Fare Embarked \n", "0 0 A/5 21171 7.2500 S \n", "1 0 PC 17599 71.2833 C \n", "2 0 STON/O2. 3101282 7.9250 S \n", "3 0 113803 53.1000 S \n", "4 0 373450 8.0500 S \n", ".. ... ... ... ... \n", "886 0 211536 13.0000 S \n", "887 0 112053 30.0000 S \n", "888 2 W./C. 6607 23.4500 S \n", "889 0 111369 30.0000 C \n", "890 0 370376 7.7500 Q \n", "\n", "[889 rows x 11 columns]" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": null, "id": "de7443e8", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 5 }