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UmarZein/eda2.ipynb

Created October 25, 2023 10:30
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eda2.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "12657923-2416-479c-9ad7-d64542c4de65",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "ef857ff1-74fc-44dc-b126-bd6385181a43",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"df=pd.read_csv(\"train.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e9875bf6-8474-48ad-b4d8-6b5800446531",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PassengerId</th>\n",
" <th>Survived</th>\n",
" <th>Pclass</th>\n",
" <th>Name</th>\n",
" <th>Sex</th>\n",
" <th>Age</th>\n",
" <th>SibSp</th>\n",
" <th>Parch</th>\n",
" <th>Ticket</th>\n",
" <th>Fare</th>\n",
" <th>Cabin</th>\n",
" <th>Embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Braund, Mr. Owen Harris</td>\n",
" <td>male</td>\n",
" <td>22.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>A/5 21171</td>\n",
" <td>7.2500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
" <td>female</td>\n",
" <td>38.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>PC 17599</td>\n",
" <td>71.2833</td>\n",
" <td>C85</td>\n",
" <td>C</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>Heikkinen, Miss. Laina</td>\n",
" <td>female</td>\n",
" <td>26.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>STON/O2. 3101282</td>\n",
" <td>7.9250</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
" <td>female</td>\n",
" <td>35.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>113803</td>\n",
" <td>53.1000</td>\n",
" <td>C123</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Allen, Mr. William Henry</td>\n",
" <td>male</td>\n",
" <td>35.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>373450</td>\n",
" <td>8.0500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>886</th>\n",
" <td>887</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>Montvila, Rev. Juozas</td>\n",
" <td>male</td>\n",
" <td>27.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>211536</td>\n",
" <td>13.0000</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>887</th>\n",
" <td>888</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Graham, Miss. Margaret Edith</td>\n",
" <td>female</td>\n",
" <td>19.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>112053</td>\n",
" <td>30.0000</td>\n",
" <td>B42</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>888</th>\n",
" <td>889</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
" <td>female</td>\n",
" <td>NaN</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>W./C. 6607</td>\n",
" <td>23.4500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>890</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Behr, Mr. Karl Howell</td>\n",
" <td>male</td>\n",
" <td>26.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>111369</td>\n",
" <td>30.0000</td>\n",
" <td>C148</td>\n",
" <td>C</td>\n",
" </tr>\n",
" <tr>\n",
" <th>890</th>\n",
" <td>891</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Dooley, Mr. Patrick</td>\n",
" <td>male</td>\n",
" <td>32.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>370376</td>\n",
" <td>7.7500</td>\n",
" <td>NaN</td>\n",
" <td>Q</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>891 rows × 12 columns</p>\n",
"</div>"
],
"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 NaN 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 Cabin Embarked \n",
"0 0 A/5 21171 7.2500 NaN S \n",
"1 0 PC 17599 71.2833 C85 C \n",
"2 0 STON/O2. 3101282 7.9250 NaN S \n",
"3 0 113803 53.1000 C123 S \n",
"4 0 373450 8.0500 NaN S \n",
".. ... ... ... ... ... \n",
"886 0 211536 13.0000 NaN S \n",
"887 0 112053 30.0000 B42 S \n",
"888 2 W./C. 6607 23.4500 NaN S \n",
"889 0 111369 30.0000 C148 C \n",
"890 0 370376 7.7500 NaN Q \n",
"\n",
"[891 rows x 12 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "raw",
"id": "94624906-038c-4d3e-91c6-f4f92ba77cb4",
"metadata": {},
"source": [
"categorical = nominal / ordinal\n",
"numeric = interval / ratio"
]
},
{
"cell_type": "markdown",
"id": "367c2cd5-2755-4193-af1a-e1330d5785bf",
"metadata": {
"tags": []
},
"source": [
"\n",
"- numeric-numeric = scatter plot\n",
"\n",
"- categorical-numeric = boxplot\n",
"\n",
"- numeric-categorical = boxplot\n",
"\n",
"- categorical-categorical = heatmap / barchart\n",
"\n",
"- numerical = histogram\n",
"\n",
"- categorical = bar chart / pie chart"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "6cc6f538-c927-4f08-81d4-80aec3fc56f6",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"x=data['Age']#numeric\n",
"y=data['Fare']#numeric"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "e84bf97f-8b27-4cb8-8528-e4b9d885e7cc",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='Age', ylabel='Fare'>"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=df,x='Age',y='Fare',hue='Pclass')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "bc086072-b119-40b8-9cec-c8779de7b5b1",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"x=data['Sex']\n",
"y=data['Age']"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "6d319ec8-24fc-493e-b4ba-c887ce28a338",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='Sex', ylabel='Age'>"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.boxplot(data=data,x='Sex',y='Age',hue='Pclass')"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "92c6ab4a-590b-4976-be4d-7c2173011ae2",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"x=data['Pclass']\n",
"y=data['Sex']"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "5d21a473-ff26-48df-a5af-799b41c1f656",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"contingency=pd.crosstab(x,y)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "a1816719-357b-4fbc-b900-e7a879adbc04",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>Sex</th>\n",
" <th>female</th>\n",
" <th>male</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Pclass</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>94</td>\n",
" <td>122</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>76</td>\n",
" <td>108</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>144</td>\n",
" <td>347</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Sex female male\n",
"Pclass \n",
"1 94 122\n",
"2 76 108\n",
"3 144 347"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"contingency"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "15438544-6331-4d41-9baa-678e104b446b",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Sex', ylabel='Pclass'>"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(contingency,annot=True)"
]
},
{
"cell_type": "code",
"execution_count": 95,
"id": "3e30c62d-c1dc-4e98-a518-ed048f38368f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='Pclass', ylabel='Survived'>"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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Wm81mu6Z7qGeKiork7e2twsJCeXl5GV1Og1fXd+6sr6p7R1FcO0Z+J6d+7quCEldJkq+1TK/cWWBYLRLfy+o4f/68MjIyFBwcLHd3d6PLabSu9nuozt9vTksBAABTIdwAAABTIdwAAABTYUIxADhJC2tZpe8B1C3CDQA4yfSuZ4wuAbXUyK6xqXec9fPntBQAoNG7fHfeXz8FG3Xv8t2OXV1da7UdRm4AAI2eq6urfHx8lJubK0lq3ry5LBaLwVU1LuXl5crLy1Pz5s1rfUdjwg0AAJICAgIkyR5wUPdcXFwUFBRU62BJuAEAQJceFNm6dWv5+fnpwoULRpfTKLm5uTnl7sWEGwAAfsXV1bXWcz5gLCYUAwAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUzE83CxevFjBwcFyd3dXWFiYkpOTr9p/3bp16ty5s5o3b67WrVtr1KhRKigoqKNqAQBAfWdouNm0aZMmT56sGTNm6ODBg+rZs6cGDBigzMzMSvvv3btXjz/+uKKjo/XNN99oy5YtOnDggMaMGVPHlQMAgPrK0HCzYMECRUdHa8yYMerYsaPi4+MVGBiohISESvt//vnnat++vSZOnKjg4GD16NFDTz31lFJSUq64j5KSEhUVFTm8AACAeRkWbkpLS5WamqqoqCiH9qioKO3bt6/SdSIjI/Xjjz8qMTFRNptNOTk5evvttzVw4MAr7icuLk7e3t72V2BgoFOPAwAA1C+GhZv8/HyVlZXJ39/fod3f31/Z2dmVrhMZGal169Zp+PDhcnNzU0BAgHx8fPTaa69dcT+xsbEqLCy0v06cOOHU4wAAAPWL4ROKLRaLw7LNZqvQdtmRI0c0ceJEzZw5U6mpqdq+fbsyMjI0duzYK27farXKy8vL4QUAAMyriVE7btmypVxdXSuM0uTm5lYYzbksLi5O3bt31zPPPCNJ6tSpk6677jr17NlTL7zwglq3bn3N6wYAAPWbYSM3bm5uCgsLU1JSkkN7UlKSIiMjK13n559/louLY8murq6SLo34AAAAGHpaKiYmRm+++aZWrlypo0ePasqUKcrMzLSfZoqNjdXjjz9u7z9o0CC9++67SkhI0PHjx/XZZ59p4sSJuv3229WmTRujDgMAANQjhp2WkqThw4eroKBAc+bMUVZWlkJDQ5WYmKh27dpJkrKyshzueTNy5EidPXtWr7/+uv7617/Kx8dH/fr100svvWTUIQAAgHrGYmtk53OKiork7e2twsJCJhc7QeacW40uoV4ImnnY6BLwb3wn/4PvJcykOn+/Db9aCgAAwJkINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQMDzeLFy9WcHCw3N3dFRYWpuTk5Kv2Lykp0YwZM9SuXTtZrVbdeOONWrlyZR1VCwAA6rsmRu5806ZNmjx5shYvXqzu3btr6dKlGjBggI4cOaKgoKBK1xk2bJhycnK0YsUK3XTTTcrNzdXFixfruHIAAFBfGRpuFixYoOjoaI0ZM0aSFB8frx07dighIUFxcXEV+m/fvl179uzR8ePH1aJFC0lS+/bt67JkAABQz1U53Dz00ENV3ui77777m31KS0uVmpqqadOmObRHRUVp3759la7z/vvvKzw8XPPnz9dbb72l6667Tg888IDmzp2rZs2aVbpOSUmJSkpK7MtFRUVVPg4AANDwVDnceHt729/bbDZt3bpV3t7eCg8PlySlpqbqzJkzVQ5B+fn5Kisrk7+/v0O7v7+/srOzK13n+PHj2rt3r9zd3bV161bl5+dr3LhxOn369BXn3cTFxWn27NlVqgkAADR8VQ43q1atsr9/9tlnNWzYMC1ZskSurq6SpLKyMo0bN05eXl7VKsBisTgs22y2Cm2XlZeXy2KxaN26dfawtWDBAg0dOlRvvPFGpaM3sbGxiomJsS8XFRUpMDCwWjUCAICGo0ZXS61cuVJTp061BxtJcnV1VUxMTJWvXGrZsqVcXV0rjNLk5uZWGM25rHXr1rrhhhscRpE6duwom82mH3/8sdJ1rFarvLy8HF4AAMC8ahRuLl68qKNHj1ZoP3r0qMrLy6u0DTc3N4WFhSkpKcmhPSkpSZGRkZWu0717d506dUrnzp2zt3377bdycXFR27Ztq3EEAADArGp0tdSoUaM0evRofffdd7rzzjslSZ9//rnmzZunUaNGVXk7MTExeuyxxxQeHq6IiAgtW7ZMmZmZGjt2rKRLp5ROnjyptWvXSpJGjBihuXPnatSoUZo9e7by8/P1zDPPaPTo0VecUAwAABqXGoWbV155RQEBAXr11VeVlZUl6dIpo7/97W/661//WuXtDB8+XAUFBZozZ46ysrIUGhqqxMREtWvXTpKUlZWlzMxMe38PDw8lJSVpwoQJCg8Pl6+vr4YNG6YXXnihJocBAABMyGKz2Wy12cDlS6sbylyWoqIieXt7q7CwsMHUXJ9lzrnV6BLqhaCZh40uAf/Gd/I/+F5CkiZNmqS8vDxJUqtWrbRw4UKDK6qZ6vz9rvHjFy5evKj//d//1YYNG+xXN/3f+TAAAMBYeXl5ysnJUU5Ojj3kmF2NTkv98MMPuvfee5WZmamSkhL1799fnp6emj9/vs6fP68lS5Y4u04AAIAqqdHIzaRJkxQeHq6ffvrJYSLvgw8+qI8//thpxQEAAFRXjUZu9u7dq88++0xubm4O7e3atdPJkyedUhgAAEBN1Gjkpry8XGVlZRXaf/zxR3l6eta6KAAAgJqqUbjp37+/4uPj7csWi0Xnzp3T888/r/vuu89ZtQEAAFRbjU5Lvfrqq+rbt69uueUWnT9/XiNGjNC//vUvtWzZUhs2bHB2jQAAAFVWo3DTpk0bpaWlacOGDfrqq69UXl6u6OhoPfLII9wpGAAAGKpG4ebnn39W8+bNNXr0aI0ePdrZNQEAANRYjebc+Pn56dFHH9WOHTuq/KBMAACAulCjcLN27VqVlJTowQcfVJs2bTRp0iQdOHDA2bUBAABUW43CzUMPPaQtW7YoJydHcXFxOnr0qCIjI3XzzTdrzpw5zq4RAACgymr8bClJ8vT01KhRo7Rz5059/fXXuu666zR79mxn1QYAAFBttQo358+f1+bNmzV48GB169ZNBQUFmjp1qrNqAwAAqLYaXS21c+dOrVu3Ttu2bZOrq6uGDh2qHTt2qHfv3s6uDwAAoFpqFG4GDx6sgQMHas2aNRo4cKCaNm3q7LoAAABqpEbhJjs7W15eXs6uBQAAoNaqHG6KioocAk1RUdEV+xJ8AACAUaocbq6//nplZWXJz89PPj4+slgsFfrYbDZZLJZKnxgOAABQF6ocbnbt2qUWLVrY31cWbgAAAIxW5XDz6yuh+vTpcy1qAQAAqLUa3ecmJCREf//733Xs2DFn1wMAAFArNQo3Tz/9tLZv366OHTsqLCxM8fHxysrKcnZtAAAA1VajcBMTE6MDBw7o//2//6f7779fCQkJCgoKUlRUlNauXevsGgEAAKqsVo9fuPnmmzV79mwdO3ZMycnJysvL06hRo5xVGwAAQLXV6CZ+v/bll19q/fr12rRpkwoLCzV06FBn1AUAAFAjNQo33377rdatW6f169fr+++/V9++fTVv3jw99NBD8vT0dHaNAAAAVVajcPP73/9e4eHhGj9+vP70pz8pICDA2XUBAADUSLXDTVlZmZYsWaKhQ4fab+oHAACuLHPOrYbt++IZX0mu/35/ytBagmYerpP9VHtCsaurqyZOnKjCwsJrUQ8AAECt1OhqqVtvvVXHjx93di0AAAC1VqNw89///d+aOnWq/vnPfyorK0tFRUUOLwAAAKPUaELxvffeK0l64IEHHB6gyVPBAQCA0WoUbj755BNn1wEAAOAUNQo3v35COAAAQH1So3Dz6aefXvXzXr161agYAACA2qpRuOnTp0+Ftl/PvWHODQAAMEqNrpb66aefHF65ubnavn27brvtNu3cudPZNQIAAFRZjUZuvL29K7T1799fVqtVU6ZMUWpqaq0LAwAAqIkajdxcSatWrXTs2DFnbhIAAKBaajRyc+jQIYdlm82mrKwszZs3T507d3ZKYQAAADVRo3DTpUsXWSwW2Ww2h/Y777xTK1eudEphAAAANVGjcJORkeGw7OLiolatWsnd3d0pRQEAANRUtcLNF198odOnT2vAgAH2trVr1+r5559XcXGxBg8erNdee01Wq9XpheI/Jk2apLy8PEmX5jktXLjQ4IoAAKg/qjWheNasWQ7zbQ4fPqzo6GjdfffdmjZtmj744APFxcU5vUg4ysvLU05OjnJycuwhBwAAXFKtcJOWlqa77rrLvrxx40bdcccdWr58uWJiYrRo0SJt3rzZ6UUCAABUVbXCzU8//SR/f3/78p49e+xPCJek2267TSdOnHBedQAAANVUrXDj7+9vn0xcWlqqr776ShEREfbPz549q6ZNmzq3QgAAgGqoVri59957NW3aNCUnJys2NlbNmzdXz5497Z8fOnRIN954o9OLBAAAqKpqXS31wgsv6KGHHlLv3r3l4eGhNWvWyM3Nzf75ypUrFRUV5fQiAQAAqqpa4aZVq1ZKTk5WYWGhPDw85Orq6vD5li1b5OHh4dQCAQAAqsNpD86UpBYtWtSqGAAAgNpy6oMzAQAAjEa4AQAApkK4AQAApkK4AQAAplKjCcUAAKBhaGEtq/S9mRFuAAAwseldzxhdQp3jtBQAADAVw8PN4sWLFRwcLHd3d4WFhSk5OblK63322Wdq0qSJunTpcm0LBAAADYqh4WbTpk2aPHmyZsyYoYMHD6pnz54aMGCAMjMzr7peYWGhHn/8cd111111VCkAAGgoDA03CxYsUHR0tMaMGaOOHTsqPj5egYGBSkhIuOp6Tz31lEaMGOHwRHIAAADJwHBTWlqq1NTUCg/ajIqK0r59+6643qpVq5Senq7nn3++SvspKSlRUVGRwwsAAJiXYeEmPz9fZWVl8vf3d2j39/dXdnZ2pev861//0rRp07Ru3To1aVK1C73i4uLk7e1tfwUGBta6dgAAUH8ZPqHYYrE4LNtstgptklRWVqYRI0Zo9uzZuvnmm6u8/djYWBUWFtpfJ06cqHXNAACg/jLsPjctW7aUq6trhVGa3NzcCqM5knT27FmlpKTo4MGDevrppyVJ5eXlstlsatKkiXbu3Kl+/fpVWM9qtcpqtV6bgwAAAPWOYSM3bm5uCgsLU1JSkkN7UlKSIiMjK/T38vLS4cOHlZaWZn+NHTtWHTp0UFpamu644466Kh0AANRjht6hOCYmRo899pjCw8MVERGhZcuWKTMzU2PHjpV06ZTSyZMntXbtWrm4uCg0NNRhfT8/P7m7u1doBwAAjZeh4Wb48OEqKCjQnDlzlJWVpdDQUCUmJqpdu3aSpKysrN+85w0AAMCvGf5sqXHjxmncuHGVfrZ69eqrrjtr1izNmjXL+UUBAIAGy/CrpQAAAJyJcAMAAEyFcAMAAEyFcAMAAEzF8AnFDVXYM2sN27fXT+fsqTTrp3OG1rLV07BdAwBQKUZuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqTQxugBUX3nT6yp9DwAACDcN0rkOA4wuAQCAeovTUgAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFSaGF0AgIZv0qRJysvLkyS1atVKCxcuNLgiAI0Z4QZAreXl5SknJ8foMgBAEqelAACAyRBuAACAqRBuAACAqRBuAACAqRgebhYvXqzg4GC5u7srLCxMycnJV+z77rvvqn///mrVqpW8vLwUERGhHTt21GG1AACgvjM03GzatEmTJ0/WjBkzdPDgQfXs2VMDBgxQZmZmpf0//fRT9e/fX4mJiUpNTVXfvn01aNAgHTx4sI4rBwAA9ZWhl4IvWLBA0dHRGjNmjCQpPj5eO3bsUEJCguLi4ir0j4+Pd1h+8cUX9d577+mDDz5Q165dK91HSUmJSkpK7MtFRUXOOwAAAFDvGDZyU1paqtTUVEVFRTm0R0VFad++fVXaRnl5uc6ePasWLVpcsU9cXJy8vb3tr8DAwFrVDQAA6jfDwk1+fr7Kysrk7+/v0O7v76/s7OwqbeMf//iHiouLNWzYsCv2iY2NVWFhof114sSJWtUNAADqN8PvUGyxWByWbTZbhbbKbNiwQbNmzdJ7770nPz+/K/azWq2yWq21rhMAADQMhoWbli1bytXVtcIoTW5uboXRnP9r06ZNio6O1pYtW3T33XdfyzIBAEADY9hpKTc3N4WFhSkpKcmhPSkpSZGRkVdcb8OGDRo5cqTWr1+vgQMHXusyAQBAA2PoaamYmBg99thjCg8PV0REhJYtW6bMzEyNHTtW0qX5MidPntTatWslXQo2jz/+uBYuXKg777zTPurTrFkzeXt7G3YcAACg/jA03AwfPlwFBQWaM2eOsrKyFBoaqsTERLVr106SlJWV5XDPm6VLl+rixYsaP368xo8fb29/4okntHr16rouHwAA1EOGTygeN26cxo0bV+ln/zew7N69+9oXBAAAGjTDH78AAADgTIaP3AAAcC1MmjRJeXl5kqRWrVpp4cKFBleEukK4AQCYUl5ennJycowuAwbgtBQAADAVwg0AADAVwg0AADAVwg0AADAVJhQDJhH2zFrD9u310zn7v5SyfjpnaC1bPQ3bNYB6gpEbAABgKoQbAABgKoQbAABgKoQbAABgKoQbAABgKoQbAABgKoQbAABgKtznBgBwzXD/pUu4/1LdYuQGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCk8FBwCYUnnT6yp9D/Mj3AAATOlchwFGlwCDEG4A1Br/QgZQnxBuANQa/0IGUJ8woRgAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJgK4QYAAJiK4eFm8eLFCg4Olru7u8LCwpScnHzV/nv27FFYWJjc3d0VEhKiJUuW1FGlAACgITA03GzatEmTJ0/WjBkzdPDgQfXs2VMDBgxQZmZmpf0zMjJ03333qWfPnjp48KCmT5+uiRMn6p133qnjygEAQH1laLhZsGCBoqOjNWbMGHXs2FHx8fEKDAxUQkJCpf2XLFmioKAgxcfHq2PHjhozZoxGjx6tV155pY4rBwAA9VUTo3ZcWlqq1NRUTZs2zaE9KipK+/btq3Sd/fv3KyoqyqHtnnvu0YoVK3ThwgU1bdq0wjolJSUqKSmxLxcWFkqSioqKalV/WckvtVrfLM42LTO6hHqhtt8nZ+A7eQnfyf/ge1l/8L28pDbfycvr2my23+xrWLjJz89XWVmZ/P39Hdr9/f2VnZ1d6TrZ2dmV9r948aLy8/PVunXrCuvExcVp9uzZFdoDAwNrUT0uCzW6gPoiztvoCvBvfCd/he9lvcH38t+c8J08e/asvL2vvh3Dws1lFovFYdlms1Vo+63+lbVfFhsbq5iYGPtyeXm5Tp8+LV9f36vuB7+tqKhIgYGBOnHihLy8vIwuB+A7iXqJ76Vz2Gw2nT17Vm3atPnNvoaFm5YtW8rV1bXCKE1ubm6F0ZnLAgICKu3fpEkT+fr6VrqO1WqV1Wp1aPPx8al54ajAy8uL/2BRr/CdRH3E97L2fmvE5jLDJhS7ubkpLCxMSUlJDu1JSUmKjIysdJ2IiIgK/Xfu3Knw8PBK59sAAIDGx9CrpWJiYvTmm29q5cqVOnr0qKZMmaLMzEyNHTtW0qVTSo8//ri9/9ixY/XDDz8oJiZGR48e1cqVK7VixQpNnTrVqEMAAAD1jKFzboYPH66CggLNmTNHWVlZCg0NVWJiotq1aydJysrKcrjnTXBwsBITEzVlyhS98cYbatOmjRYtWqQhQ4YYdQiNmtVq1fPPP1/htB9gFL6TqI/4XtY9i60q11QBAAA0EIY/fgEAAMCZCDcAAMBUCDcAAMBUCDcAAMBUCDeotk8//VSDBg1SmzZtZLFYtG3bNqNLQiMXFxen2267TZ6envLz89PgwYN17Ngxo8tCI5aQkKBOnTrZb9wXERGhjz76yOiyGg3CDaqtuLhYnTt31uuvv250KYAkac+ePRo/frw+//xzJSUl6eLFi4qKilJxcbHRpaGRatu2rebNm6eUlBSlpKSoX79++sMf/qBvvvnG6NIaBS4FR61YLBZt3bpVgwcPNroUwC4vL09+fn7as2ePevXqZXQ5gCSpRYsWevnllxUdHW10KaZn+IMzAcDZCgsLJV36YwIYraysTFu2bFFxcbEiIiKMLqdRINwAMBWbzaaYmBj16NFDoaGhRpeDRuzw4cOKiIjQ+fPn5eHhoa1bt+qWW24xuqxGgXADwFSefvppHTp0SHv37jW6FDRyHTp0UFpams6cOaN33nlHTzzxhPbs2UPAqQOEGwCmMWHCBL3//vv69NNP1bZtW6PLQSPn5uamm266SZIUHh6uAwcOaOHChVq6dKnBlZkf4QZAg2ez2TRhwgRt3bpVu3fvVnBwsNElARXYbDaVlJQYXUajQLhBtZ07d07fffedfTkjI0NpaWlq0aKFgoKCDKwMjdX48eO1fv16vffee/L09FR2drYkydvbW82aNTO4OjRG06dP14ABAxQYGKizZ89q48aN2r17t7Zv3250aY0Cl4Kj2nbv3q2+fftWaH/iiSe0evXqui8IjZ7FYqm0fdWqVRo5cmTdFgNIio6O1scff6ysrCx5e3urU6dOevbZZ9W/f3+jS2sUCDcAAMBUuEMxAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINAAAwFcINgAZr5MiRGjx4sNFlAKhnCDcADDVy5EhZLBZZLBY1bdpUISEhmjp1qoqLi40uDUADxYMzARju3nvv1apVq3ThwgUlJydrzJgxKi4uVkJCgtGlAWiAGLkBYDir1aqAgAAFBgZqxIgReuSRR7Rt2zZJ0jfffKOBAwfKy8tLnp6e6tmzp9LT0yvdzvbt29WjRw/5+PjI19dX999/v0Pf0tJSPf3002rdurXc3d3Vvn17xcXF2T+fNWuWgoKCZLVa1aZNG02cOPGaHjeAa4ORGwD1TrNmzXThwgWdPHlSvXr1Up8+fbRr1y55eXnps88+08WLFytdr7i4WDExMbr11ltVXFysmTNn6sEHH1RaWppcXFy0aNEivf/++9q8ebOCgoJ04sQJnThxQpL09ttv69VXX9XGjRv1X//1X8rOztbXX39dl4cNwEkINwDqlS+//FLr16/XXXfdpTfeeEPe3t7auHGjmjZtKkm6+eabr7jukCFDHJZXrFghPz8/HTlyRKGhocrMzNTvfvc79ejRQxaLRe3atbP3zczMVEBAgO6++241bdpUQUFBuv3226/NQQK4pjgtBcBw//znP+Xh4SF3d3dFRESoV69eeu2115SWlqaePXvag81vSU9P14gRIxQSEiIvLy8FBwdLuhRcpEuTl9PS0tShQwdNnDhRO3futK/7xz/+Ub/88otCQkL05JNPauvWrVccIQJQvxFuABiub9++SktL07Fjx3T+/Hm9++678vPzU7Nmzaq1nUGDBqmgoEDLly/XF198oS+++ELSpbk2ktStWzdlZGRo7ty5+uWXXzRs2DANHTpUkhQYGKhjx47pjTfeULNmzTRu3Dj16tVLFy5ccO7BArjmCDcADHfdddfppptuUrt27RxGaTp16qTk5OQqBYyCggIdPXpUzz33nO666y517NhRP/30U4V+Xl5eGj58uJYvX65NmzbpnXfe0enTpyVdmuvzwAMPaNGiRdq9e7f279+vw4cPO+9AAdQJ5twAqLeefvppvfbaa/rTn/6k2NhYeXt76/PPP9ftt9+uDh06OPS9/vrr5evrq2XLlql169bKzMzUtGnTHPq8+uqrat26tbp06SIXFxdt2bJFAQEB8vHx0erVq1VWVqY77rhDzZs311tvvaVmzZo5zMsB0DAwcgOg3vL19dWuXbt07tw59e7dW2FhYVq+fHmlc3BcXFy0ceNGpaamKjQ0VFOmTNHLL7/s0MfDw0MvvfSSwsPDddttt+n7779XYmKiXFxc5OPjo+XLl6t79+7q1KmTPv74Y33wwQfy9fWtq8MF4CQWm81mM7oIAAAAZ2HkBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmArhBgAAmMr/B8WLR4vWPyMyAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=df, x=\"Pclass\", y=\"Survived\", hue=\"Sex\")"
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "06a4a0e9-9ec1-43a5-a86b-2465b03efa3d",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"count 122.000000\n",
"mean 0.368852\n",
"std 0.484484\n",
"min 0.000000\n",
"25% 0.000000\n",
"50% 0.000000\n",
"75% 1.000000\n",
"max 1.000000\n",
"Name: Survived, dtype: float64"
]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.query(\"Pclass==1 and Sex=='male'\")['Survived'].describe()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "876bd23b-0e1b-4a6e-a753-042bf94f6e6e",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"x=data['Age']"
]
},
{
"cell_type": "code",
"execution_count": 93,
"id": "3dff739b-ca04-4d0c-b3d2-d8e91573e78f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
" if pd.api.types.is_categorical_dtype(vector):\n",
"/home/maru/anaconda3/lib/python3.9/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
" with pd.option_context('mode.use_inf_as_na', True):\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='Age', ylabel='Count'>"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=df,x='Age',row='')"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "1ed926cc-3e2a-4136-ba0a-a6b21643f95e",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"x=data['Pclass']"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "ee41da7d-41ee-4831-9847-fd44cc16c94b",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Pclass\n",
"3 491\n",
"1 216\n",
"2 184\n",
"Name: count, dtype: int64\n"
]
}
],
"source": [
"y=x.value_counts()\n",
"print(y)"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "f60b0036-b12c-4537-bd72-a852069fdff8",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: ylabel='count'>"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"y.plot.pie()"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "660b095c-6ca9-4538-b9b6-7ccbe7f4baa1",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"0 male\n",
"1 female\n",
"2 female\n",
"3 female\n",
"4 male\n",
" ... \n",
"886 male\n",
"887 female\n",
"888 female\n",
"889 male\n",
"890 male\n",
"Name: Sex, Length: 891, dtype: object"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x"
]
},
{
"cell_type": "code",
"execution_count": null,
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