data-science-best-practices-using-pandas-titanic.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/faressayah/data-science-best-practices-using-pandas-titanic?scriptVersionId=117856353\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown","outputs":[],"execution_count":0},{"cell_type":"markdown","id":"306fb4f7","metadata":{"papermill":{"duration":0.01292,"end_time":"2023-01-31T18:26:48.42985","exception":false,"start_time":"2023-01-31T18:26:48.41693","status":"completed"},"tags":[]},"source":["# Kaggle Titanic Challenge\n","****"]},{"cell_type":"code","execution_count":1,"id":"52526b8c","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:48.456252Z","iopub.status.busy":"2023-01-31T18:26:48.455561Z","iopub.status.idle":"2023-01-31T18:26:48.523694Z","shell.execute_reply":"2023-01-31T18:26:48.522471Z"},"papermill":{"duration":0.08601,"end_time":"2023-01-31T18:26:48.527981","exception":false,"start_time":"2023-01-31T18:26:48.441971","status":"completed"},"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","  </tbody>\n","</table>\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","                                                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","   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  "]},"execution_count":1,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","titanic_df = pd.read_csv('/kaggle/input/titanic/train.csv')\n","titanic_df.head()"]},{"cell_type":"markdown","id":"9831fcb0","metadata":{"papermill":{"duration":0.01125,"end_time":"2023-01-31T18:26:48.550907","exception":false,"start_time":"2023-01-31T18:26:48.539657","status":"completed"},"tags":[]},"source":["### Variable Notes\n","   - **PassengerId** Unique ID of the passenger\n","\n","   - **Survived** Survived (1) or died (0)\n","\n","   - **Pclass** Passenger's class (1st, 2nd, or 3rd)\n","\n","   - **Name** Passenger's name\n","\n","   - **Sex** Passenger's sex\n","\n","   - **Age** Passenger's age\n","\n","   - **SibSp** Number of siblings/spouses aboard the Titanic\n","\n","   - **Parch** Number of parents/children aboard the Titanic\n","\n","   - **Ticket** Ticket number\n","\n","   - **Fare** Fare paid for ticket\n","\n","   - **Cabin** Cabin number\n","\n","   - **Embarked** Where the passenger got on the ship (C - Cherbourg, S - Southampton, Q = Queenstown)"]},{"cell_type":"code","execution_count":2,"id":"1995f8ae","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:48.578544Z","iopub.status.busy":"2023-01-31T18:26:48.577715Z","iopub.status.idle":"2023-01-31T18:26:48.611512Z","shell.execute_reply":"2023-01-31T18:26:48.610233Z"},"papermill":{"duration":0.050214,"end_time":"2023-01-31T18:26:48.614299","exception":false,"start_time":"2023-01-31T18:26:48.564085","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["DataFrame shape : (891, 12)\n","=================================\n","<class 'pandas.core.frame.DataFrame'>\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","DataFrame info : None\n","=================================\n","DataFrame columns : Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n","       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'],\n","      dtype='object')\n","=================================\n","The type of each column : 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\n","=================================\n","How much missing value in every column : PassengerId      0\n","Survived         0\n","Pclass           0\n","Name             0\n","Sex              0\n","Age            177\n","SibSp            0\n","Parch            0\n","Ticket           0\n","Fare             0\n","Cabin          687\n","Embarked         2\n","dtype: int64\n","=================================\n"]}],"source":["# Exploring the data using pandas methods : 'shape', 'info', 'describe', 'dtype', 'mean()', ...\n","print(f\"DataFrame shape : {titanic_df.shape}\\n=================================\")\n","print(f\"DataFrame info : {titanic_df.info()}\\n=================================\")\n","print(f\"DataFrame columns : {titanic_df.columns}\\n=================================\")\n","print(f\"The type of each column : {titanic_df.dtypes}\\n=================================\")\n","print(f\"How much missing value in every column : {titanic_df.isna().sum()}\\n=================================\")"]},{"cell_type":"markdown","id":"e66f9fe5","metadata":{"papermill":{"duration":0.011478,"end_time":"2023-01-31T18:26:48.637693","exception":false,"start_time":"2023-01-31T18:26:48.626215","status":"completed"},"tags":[]},"source":["All good data analysis projects begin with trying to answer questions. Now that we know what column category data we have let's think of some questions or insights we would like to obtain from the data. So here's a list of questions we'll try to answer using our data analysis skills!\n","\n","First some basic questions:\n","\n","    1.) Who were the passengers on the Titanic? (Ages, Gender, Class,..etc)\n","    2.) What deck were the passengers on and how does that relate to their class?\n","    3.) Where did the passengers come from?\n","    4.) Who was alone and who was with family?\n","    \n","Then we'll dig deeper, with a broader question:\n","\n","    5.) What factors helped someone survive the sinking?"]},{"cell_type":"markdown","id":"616c81f0","metadata":{"papermill":{"duration":0.012677,"end_time":"2023-01-31T18:26:48.662101","exception":false,"start_time":"2023-01-31T18:26:48.649424","status":"completed"},"tags":[]},"source":["# 1. Who were the passengers on the titanic?"]},{"cell_type":"code","execution_count":3,"id":"f51d77fe","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:48.689423Z","iopub.status.busy":"2023-01-31T18:26:48.688671Z","iopub.status.idle":"2023-01-31T18:26:50.001403Z","shell.execute_reply":"2023-01-31T18:26:49.999845Z"},"papermill":{"duration":1.330643,"end_time":"2023-01-31T18:26:50.004672","exception":false,"start_time":"2023-01-31T18:26:48.674029","status":"completed"},"tags":[]},"outputs":[],"source":["import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","%matplotlib inline\n","sns.set(style=\"ticks\")\n","plt.style.use(\"fivethirtyeight\")"]},{"cell_type":"code","execution_count":4,"id":"31780ce6","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:50.031743Z","iopub.status.busy":"2023-01-31T18:26:50.030887Z","iopub.status.idle":"2023-01-31T18:26:50.347536Z","shell.execute_reply":"2023-01-31T18:26:50.3463Z"},"papermill":{"duration":0.332888,"end_time":"2023-01-31T18:26:50.350419","exception":false,"start_time":"2023-01-31T18:26:50.017531","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b7a6e450>"]},"execution_count":4,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's first check gender\n","# 'catplot()': Figure-level interface for drawing categorical plots onto a FacetGrid.\n","sns.catplot(x='Sex', data=titanic_df, kind='count')"]},{"cell_type":"code","execution_count":5,"id":"e4f8eaf9","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:50.378161Z","iopub.status.busy":"2023-01-31T18:26:50.377727Z","iopub.status.idle":"2023-01-31T18:26:50.737974Z","shell.execute_reply":"2023-01-31T18:26:50.736695Z"},"papermill":{"duration":0.377346,"end_time":"2023-01-31T18:26:50.740596","exception":false,"start_time":"2023-01-31T18:26:50.36325","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b5790d10>"]},"execution_count":5,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 437.975x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Now let separate the gender by classes passing 'Sex' to the 'hue' parameter\n","sns.catplot(x='Pclass', data=titanic_df, hue='Sex', kind='count')"]},{"cell_type":"markdown","id":"c1af56d6","metadata":{"papermill":{"duration":0.012171,"end_time":"2023-01-31T18:26:50.765592","exception":false,"start_time":"2023-01-31T18:26:50.753421","status":"completed"},"tags":[]},"source":["Wow, quite a few more males in the 3rd class than females, an interesting find. However, it might be useful to know the split between males, females, and children. How can we go about this?"]},{"cell_type":"code","execution_count":6,"id":"e3817934","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:50.792495Z","iopub.status.busy":"2023-01-31T18:26:50.792085Z","iopub.status.idle":"2023-01-31T18:26:50.799402Z","shell.execute_reply":"2023-01-31T18:26:50.798129Z"},"papermill":{"duration":0.023491,"end_time":"2023-01-31T18:26:50.801622","exception":false,"start_time":"2023-01-31T18:26:50.778131","status":"completed"},"tags":[]},"outputs":[],"source":["# Create a new column 'Person' in which every person under 16 is child.\n","\n","titanic_df['Person'] = titanic_df.Sex\n","titanic_df.loc[titanic_df['Age'] < 16, 'Person'] = 'Child'"]},{"cell_type":"code","execution_count":7,"id":"de5ab240","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:50.829379Z","iopub.status.busy":"2023-01-31T18:26:50.828602Z","iopub.status.idle":"2023-01-31T18:26:50.837484Z","shell.execute_reply":"2023-01-31T18:26:50.83582Z"},"papermill":{"duration":0.025963,"end_time":"2023-01-31T18:26:50.84038","exception":false,"start_time":"2023-01-31T18:26:50.814417","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Person categories : ['male' 'female' 'Child']\n","=================================\n","Distribution of person : male      537\n","female    271\n","Child      83\n","Name: Person, dtype: int64\n","=================================\n","Mean age : 29.69911764705882\n","=================================\n"]}],"source":["# Checking the distribution\n","print(f\"Person categories : {titanic_df.Person.unique()}\\n=================================\")\n","print(f\"Distribution of person : {titanic_df.Person.value_counts()}\\n=================================\")\n","print(f\"Mean age : {titanic_df.Age.mean()}\\n=================================\")"]},{"cell_type":"markdown","id":"45dec2c2","metadata":{"papermill":{"duration":0.012279,"end_time":"2023-01-31T18:26:50.865313","exception":false,"start_time":"2023-01-31T18:26:50.853034","status":"completed"},"tags":[]},"source":["Excellent! Now we have seperated the passengers between female, male, and child. This will be important later on beacuse of the famous **\"Women and children first policy\"**!"]},{"cell_type":"code","execution_count":8,"id":"080e6c7e","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:50.892804Z","iopub.status.busy":"2023-01-31T18:26:50.892034Z","iopub.status.idle":"2023-01-31T18:26:51.263307Z","shell.execute_reply":"2023-01-31T18:26:51.261869Z"},"papermill":{"duration":0.387982,"end_time":"2023-01-31T18:26:51.265928","exception":false,"start_time":"2023-01-31T18:26:50.877946","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b56d0750>"]},"execution_count":8,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 437.975x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["sns.catplot(x='Pclass', data=titanic_df, hue='Person', kind='count')"]},{"cell_type":"markdown","id":"c2a66cac","metadata":{"papermill":{"duration":0.013679,"end_time":"2023-01-31T18:26:51.292715","exception":false,"start_time":"2023-01-31T18:26:51.279036","status":"completed"},"tags":[]},"source":["Interesting, quite a bit of children in 3rd class and not so many in 1st! How about we create a distribution of the ages to get a more precise picture of the who the passengers were."]},{"cell_type":"code","execution_count":9,"id":"d2d3aa3f","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:51.321455Z","iopub.status.busy":"2023-01-31T18:26:51.320214Z","iopub.status.idle":"2023-01-31T18:26:51.673454Z","shell.execute_reply":"2023-01-31T18:26:51.671986Z"},"papermill":{"duration":0.370591,"end_time":"2023-01-31T18:26:51.67653","exception":false,"start_time":"2023-01-31T18:26:51.305939","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:>"]},"execution_count":9,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# visualizing age distribution\n","titanic_df.Age.hist(bins=80)"]},{"cell_type":"code","execution_count":10,"id":"9cab326c","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:51.705626Z","iopub.status.busy":"2023-01-31T18:26:51.705211Z","iopub.status.idle":"2023-01-31T18:26:52.139173Z","shell.execute_reply":"2023-01-31T18:26:52.138209Z"},"papermill":{"duration":0.451189,"end_time":"2023-01-31T18:26:52.141533","exception":false,"start_time":"2023-01-31T18:26:51.690344","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b560ae10>"]},"execution_count":10,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 941.975x216 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Another way to visualize the data is to use FacetGrid to plot multiple kedplots on one plot\n","\n","fig = sns.FacetGrid(titanic_df, hue=\"Sex\", aspect=4)\n","fig.map(sns.kdeplot, 'Age', shade=True)\n","\n","oldest = titanic_df['Age'].max()\n","\n","fig.set(xlim=(0, oldest))\n","\n","fig.add_legend()"]},{"cell_type":"code","execution_count":11,"id":"d52f79f6","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:52.173211Z","iopub.status.busy":"2023-01-31T18:26:52.172491Z","iopub.status.idle":"2023-01-31T18:26:52.626296Z","shell.execute_reply":"2023-01-31T18:26:52.62502Z"},"papermill":{"duration":0.472406,"end_time":"2023-01-31T18:26:52.629117","exception":false,"start_time":"2023-01-31T18:26:52.156711","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b5614890>"]},"execution_count":11,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 941.975x216 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# We could have done the same thing for the 'person' column to include children:\n","\n","fig = sns.FacetGrid(titanic_df, hue=\"Person\",aspect=4)\n","fig.map(sns.kdeplot, 'Age', shade=True)\n","\n","oldest = titanic_df['Age'].max()\n","\n","fig.set(xlim=(0, oldest))\n","\n","fig.add_legend()"]},{"cell_type":"code","execution_count":12,"id":"4480ccbb","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:52.662142Z","iopub.status.busy":"2023-01-31T18:26:52.661683Z","iopub.status.idle":"2023-01-31T18:26:53.121453Z","shell.execute_reply":"2023-01-31T18:26:53.120074Z"},"papermill":{"duration":0.479358,"end_time":"2023-01-31T18:26:53.124233","exception":false,"start_time":"2023-01-31T18:26:52.644875","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b54675d0>"]},"execution_count":12,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 910.6x216 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's do the same for class by changing the hue argument:\n","\n","fig = sns.FacetGrid(titanic_df, hue=\"Pclass\",aspect=4)\n","fig.map(sns.kdeplot, 'Age', shade=True)\n","\n","oldest = titanic_df['Age'].max()\n","\n","fig.set(xlim=(0, oldest))\n","\n","fig.add_legend()"]},{"cell_type":"markdown","id":"22a9d197","metadata":{"papermill":{"duration":0.015578,"end_time":"2023-01-31T18:26:53.155069","exception":false,"start_time":"2023-01-31T18:26:53.139491","status":"completed"},"tags":[]},"source":["We've gotten a pretty good picture of who the passengers were based on Sex, Age, and Class. So let's move on to our 2nd question: What deck were the passengers on and how does that relate to their class?"]},{"cell_type":"markdown","id":"43a31bbe","metadata":{"papermill":{"duration":0.015972,"end_time":"2023-01-31T18:26:53.186397","exception":false,"start_time":"2023-01-31T18:26:53.170425","status":"completed"},"tags":[]},"source":["# 2. What deck were the passengers on and how does that relate to their class?"]},{"cell_type":"code","execution_count":13,"id":"fb61da65","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:53.220739Z","iopub.status.busy":"2023-01-31T18:26:53.220224Z","iopub.status.idle":"2023-01-31T18:26:53.240056Z","shell.execute_reply":"2023-01-31T18:26:53.238594Z"},"papermill":{"duration":0.040268,"end_time":"2023-01-31T18:26:53.242397","exception":false,"start_time":"2023-01-31T18:26:53.202129","status":"completed"},"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","      <th>Person</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","      <td>male</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","      <td>female</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","      <td>female</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","      <td>female</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","      <td>male</td>\n","    </tr>\n","  </tbody>\n","</table>\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","                                                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","   Parch            Ticket     Fare Cabin Embarked  Person  \n","0      0         A/5 21171   7.2500   NaN        S    male  \n","1      0          PC 17599  71.2833   C85        C  female  \n","2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n","3      0            113803  53.1000  C123        S  female  \n","4      0            373450   8.0500   NaN        S    male  "]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["# visualizing the dataset again\n","titanic_df.head()"]},{"cell_type":"markdown","id":"4cd6c0f9","metadata":{"papermill":{"duration":0.016084,"end_time":"2023-01-31T18:26:53.275179","exception":false,"start_time":"2023-01-31T18:26:53.259095","status":"completed"},"tags":[]},"source":["So we can see that the Cabin column has information on the deck, but it has several NaN values, so we'll have to drop them."]},{"cell_type":"code","execution_count":14,"id":"c064c2a3","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:53.308947Z","iopub.status.busy":"2023-01-31T18:26:53.307804Z","iopub.status.idle":"2023-01-31T18:26:53.317154Z","shell.execute_reply":"2023-01-31T18:26:53.316132Z"},"papermill":{"duration":0.028996,"end_time":"2023-01-31T18:26:53.319717","exception":false,"start_time":"2023-01-31T18:26:53.290721","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["1              C85\n","3             C123\n","6              E46\n","10              G6\n","11            C103\n","          ...     \n","871            D35\n","872    B51 B53 B55\n","879            C50\n","887            B42\n","889           C148\n","Name: Cabin, Length: 204, dtype: object"]},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":["# First we'll drop the NaN values and create a new object, deck\n","deck = titanic_df['Cabin'].dropna()\n","deck"]},{"cell_type":"markdown","id":"0594073b","metadata":{"papermill":{"duration":0.015879,"end_time":"2023-01-31T18:26:53.351172","exception":false,"start_time":"2023-01-31T18:26:53.335293","status":"completed"},"tags":[]},"source":["Notice we only need the first letter of the deck to classify its level (e.g. A, B, C, D, E, F, G)"]},{"cell_type":"code","execution_count":15,"id":"0246315d","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:53.38403Z","iopub.status.busy":"2023-01-31T18:26:53.383571Z","iopub.status.idle":"2023-01-31T18:26:53.689339Z","shell.execute_reply":"2023-01-31T18:26:53.68775Z"},"papermill":{"duration":0.326287,"end_time":"2023-01-31T18:26:53.692721","exception":false,"start_time":"2023-01-31T18:26:53.366434","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0eb53c8d0>"]},"execution_count":15,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAVgAAAFYCAYAAAAWbORAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdOklEQVR4nO3de3TT9f3H8VeaUkyLKS0ttVxqhdN2R/FyYKLCdHghrp7fDirmoB4HE6dyFRTUOnGkup32iMjNA06riAMVlWkHgsvRA8pQcQ7OnHPEimsRKCGQ0lKagk3z+8PRyWihgX7yTcvz8RfNN83n3ct5ni+fJt/YDhw4EBEAoMMlWD0AAHRVBBYADCGwAGAIgQUAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYEiilYsfPnxY8+bN01//+lclJSXpwgsv1K9//WtVVVWpuLhYtbW1Sk1NlcfjUU5OjpWjAkDULA3sokWLlJSUpDfffFM2m0379++XJJWWlsrtdquwsFDr1q1TSUmJlixZYuWoABA1y7YIGhoatHbtWk2YMEE2m02S1KtXLwWDQfl8PrlcLkmSy+WSz+dTTU2NVaMCwCmx7Ax2586dSk1NVVlZmT777DMlJydrwoQJ6t69uzIzM2W32yVJdrtdmZmZ8vv9SktLs2pcAIiaZYENh8PatWuX8vPzdd999+mLL77QjBkzVFJSEvVjVVRUGJgQAE4uLy+vzWOWBTY7O1t2u13XX3+9JGnQoEHq2bOnunfvrkAgoHA4LLvdrnA4rEAgoKysrDYf60RfIABYxbI92J49e+rHP/6xNm/eLEmqqqpSMBhUTk6O8vPz5fV6JUler1cFBQVsDwDodGxWvmXMrl279MQTT6i2tlaJiYmaOHGihg0bpsrKShUXF6uurk5Op1Mej0fnnnuuVWMCwCmxNLAA0JVZ+jxYxNaO2kOqPhiK6ZrZZzuUk5oS0zWBeEFgzyDVB0Mau2pTTNd8efRwAoszFtciAABDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGEFgAMITAAoAhBBYADCGwAGAIgQUAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGEFgAMCTRysVHjRqlpKQkJSUlSZKmTJmiK664QlVVVSouLlZtba1SU1Pl8XiUk5Nj5agAEDVLAytJpaWlGjhw4HG3ud1uFRYWat26dSopKdGSJUssmhAATk3cbREEg0H5fD65XC5Jksvlks/nU01NjcWTAUB0LD+DfeyxxyRJF198sSZNmiS/36/MzEzZ7XZJkt1uV2Zmpvx+v9LS0qwcFQCiYmlgn3vuOWVlZenIkSN6+umnNWfOHN12221RP05FRYWB6bqeUKR77NdsaODngy4tLy+vzWOWBjYrK0uSlJSUpFtuuUUzZszQ9OnTFQgEFA6HZbfbFQ6HFQgEWu7bmhN9gfiv4M59MV/TkZysvH78gRJnJsv2YEOhkOrr6yVJkUhEXq9X+fn5Sk9PV35+vrxeryTJ6/WqoKCA7QEAnY5lZ7DBYFAPP/ywmpubFQ6Hdd555+nhhx+WJBUVFam4uFhlZWVyOp3yeDxWjQkAp8x24MCBiNVDIDY279ynsas2xXTNl0cP12X9MmK6JhAv4u5pWgDQVRBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGWH65wq5sR02DqmsbY7pmdupZyklLjumaAFpHYA2qrm3UuOWfxXTNZXf8mMACcYItAgAwhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGEFgAMITAAoAhBBYADCGwAGAIgQUAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMiYvAPv/88xo6dKi2b98uSaqqqtL48eM1evRojR8/Xjt27LB4QgCInuWB3bZtm7744gudc845LbeVlpbK7XZr1apVcrvdKikpsXBCADg1lgb2yJEjevLJJ/XQQw/JZrNJkoLBoHw+n1wulyTJ5XLJ5/OppqbGylEBIGqWBvb3v/+9CgsL1bdv35bb/H6/MjMzZbfbJUl2u12ZmZny+/1WjQkApyTRqoU///xzffnll5oyZcppP1ZFRUUHTNTxQk3JsV8zFGrz+xGKdI/xNFKooSFufz5AR8jLy2vzmGWB3bp1q6qqqnTjjTdKkvbu3av77rtP06dPVyAQUDgclt1uVzgcViAQUFZWVpuPdaIv0ErBymDM13Q4HMrL7dvqseDOfTGeRnIkJyuvX07M1wXigWVbBOPGjdPatWtVXl6u8vJy9e7dWwsXLtTIkSOVn58vr9crSfJ6vSooKFBaWppVowLAKbHsDPZEioqKVFxcrLKyMjmdTnk8HqtHAoCoxU1gy8vLW/6dm5urpUuXWjgNAJw+y58HCwBdFYEFAEMILAAYQmABwBACCwCGEFgAMITAAoAhBBYADCGwAGAIgQUAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYEhUgb3xxhv14Ycftnl848aNLW9iCABnuqgCW11drYaGhjaPh0Ih7dmz57SHAoCuIOotApvN1uaxHTt2KCUl5bQGAoCu4qRverhmzRq98847LR+/+OKLevvtt4+738GDB7V9+3YNHz68QwcEgM7qpIENhULav39/y8f19fWKRCLH3Mdms+mss87SqFGjdPfdd3f8lADQCZ00sG63W263W5I0atQozZgxQ1dddZXxwQCgsztpYH+ovLzc1BwA0OVEFdijDh06pD179qiuru647QJJGjx48GkPBgCdXVSBra2t1dy5c/Xee++pubn5uOORSEQ2m02ffPJJhw0IAJ1VVIEtLS3Vhg0b5Ha7NXjwYDmdTlNzAUCnF1VgP/74Y40ZM0bTp083NA4AdB1RvdCgW7du6t+/v6lZAKBLieoM9pprrtHHH3+s0aNHm5oHZ5AddfWqPtT2S69NyE5JVo6zR0zXxJkrqsDecccdmjVrljwej0aPHq3s7GwlJBx/Epyent5hA6Lrqj7UoF+sWx/TNf9QeDWBRcxEFdhbbrlFNptN27Zt07vvvtvm/XgWAQBEGdi77rrrhBd7AQD8V1SBveeee0zNAVju27o6VdfXx3TN7B491J+nO3ZZp/RKLqArqq6v17g1a2K65rL/+z8C24VFFdiysrKT3sdms+muu+465YEAoKuIKrDPP/98m8dsNlvLS2UJLABEGdjNmzcfd1tzc7Oqq6u1cuVKff7555o/f35HzQYAndppv6tsQkKC+vbtqwceeEB9+vTRvHnzOmIuAOj0OvSPXEOGDNHixYvbff+ZM2dq9+7dSkhIkMPh0IMPPqj8/HxVVVWpuLhYtbW1Sk1NlcfjUU5OTkeOCgDGdWhgq6qqWr2MYVs8Ho969Pj+VTUffPCBnnjiCf3hD39QaWmp3G63CgsLtW7dOpWUlGjJkiUdOSoAGBdVYLds2dLq7fX19frss8/0xhtv6Nprr2334x2N69HHsNlsCgaD8vl8crlckiSXy6U5c+aopqZGaWlp0YwLAJaKKrATJ05s9ZVckUhECQkJcrlcmjFjRlQD/Pa3v9XmzZsViUS0YMEC+f1+ZWZmym63S5LsdrsyMzPl9/sJLIBOJarAtvXfdKfTqezsbKWkpEQ9wKxZsyRJa9eu1aJFi3TvvfdG/RgVFRVRf04shJqSY79mKNTm9yMU6R7jaaRQQ0Pb89i7xXgaKRRqe56GVi5cZFrDCX5e6Bzy8vLaPBZVYE2+19YNN9ygkpIS9e7dW4FAQOFwWHa7XeFwWIFAQFlZWW1+7om+QCsFK4MxX9PhcCgvt2+rx4I798V4GsmRnKy8fq3/gTJYvTfG00gOR7Lysnu3eqxm9+4YTyMlOxzK69Mn5usiNk75TQ+3bNmi3f/5hezTp48GDx4c1RlsQ0ODDh482BLOjRs3yul0Kj09Xfn5+fJ6vSosLJTX61VBQQHbAwA6nagDu3LlSj377LMKhULHvKOsw+HQxIkTNWbMmHY9TigU0iOPPKJQKKSEhAQ5nU7NnTtXNptNRUVFKi4uVllZmZxOpzweT7RjAoDlogrs2rVr9fTTT+uCCy7QrbfeqvPOO0+RSESVlZV67bXXNG/ePKWmpupnP/vZSR+rV69eevHFF1s9lpubq6VLl0YzGgDEnagC+8orr+iiiy7SkiVLlJj430/Nz8/XNddco4kTJ2r58uXtCiwAdHVR/dm0qqpKI0eOPCauRyUmJmrkyJGqqqrqsOEAoDOLKrAOh0P79rX9l+h9+/bJ4XCc9lAA0BVEFdjLLrtMr7/+uv72t78dd2zLli164403dPnll3fYcADQmUW1BztlyhRt3bpVkydPVn5+vnJzcyVJlZWV+uqrr5SRkaHJkyebmBMAOp2ozmCzsrK0fPly3XbbbWpsbNT69eu1fv16NTY26vbbb9fy5ctP+IIAADiTRHUGGwqF1NjYqGnTpmnatGnHHd+zZ48aGxt11llnddiAANBZRXUGO2/ePM2cObPN4w8++KAWLFhw2kMBQFcQVWA3b96sESNGtHl8xIgR+uSTT053JgDoEqIK7P79+5WRkdHm8V69ep3waVwAcCaJKrA9e/bUN9980+bxb7755piLaAPAmSyqwA4fPlxvvfWWPv/88+OO/eMf/9Bbb72lYcOGddhwANCZRfUsgrvvvlubNm3SvffeqyuuuEIDBw6UzWbT119/rY8//li9evXShAkTTM0KAJ1KVIHNyMjQsmXL9Mwzz+iDDz7Qpk2bJEkpKSkqLCzUpEmTTrhHCwBnkqivB9urVy/Nnj1bkUhENTU1ikQiSk9Pb/W9ugDgTHbKb9tts9mUnp7ekbMAQJcS+3d5A4AzBIEFAEMILAAYQmABwBACCwCGEFgAMITAAoAhBBYADCGwAGAIgQUAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADDklN+2+3QdOHBAHo9HO3fuVFJSkvr166dHHnlEaWlpqqqqUnFxsWpra5WamiqPx6OcnByrRgWAU2LZGazNZtMvfvELvfnmm3rllVfUr18/PfPMM5Kk0tJSud1urVq1Sm63WyUlJVaNCQCnzLLApqamasiQIS0fDxo0SHv27FEwGJTP55PL5ZIkuVwu+Xw+1dTUWDUqAJySuNiDbW5u1qpVq3TVVVfJ7/crMzNTdrtdkmS325WZmSm/32/xlAAQHcv2YH/oqaeeksPhkNvtls/ni/rzKyoqDEx1+kJNybFfMxRq8/sRinSP8TRSqKGh7Xns3WI8jRQKtT1PQ0LszzcaTvDzQueQl5fX5jHLA7tgwQJ9++23mjt3rhISEpSVlaVAIKBwOCy73a5wOKxAIKCsrKw2H+NEX6CVgpXBmK/pcDiUl9u31WPBnftiPI3kSE5WXr/W/0AZrN4b42kkhyNZedm9Wz1Ws3t3jKeRkh0O5fXpE/N1ERuWbhEsXrxY27Zt05w5c5SUlCRJSk9PV35+vrxeryTJ6/WqoKBAaWlpVo4KAFGz7Ax2+/bteumll5STk6O77rpLktSnTx/NmTNHRUVFKi4uVllZmZxOpzwej1VjAsApsyywAwcO1KefftrqsdzcXC1dujTGEwFAx4qLZxEAQFdEYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGWP623R3l2/0hVR84HNM1s3t2V/9ejpiuCaDz6DKBrT5wWOOe+zymay675yICC6BNbBEAgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCky7zQAOiKvq2p0Z7a2piueU5qqvqnpcV0za6KwAJxbE9trX61fHlM1yy74w4C20HYIgAAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYIhlgV2wYIFGjRqloUOHavv27S23V1VVafz48Ro9erTGjx+vHTt2WDUiAJwWywL705/+VM8995yys7OPub20tFRut1urVq2S2+1WSUmJRRMCwOmxLLCXXHKJsrKyjrktGAzK5/PJ5XJJklwul3w+n2pqaqwYEQBOS1ztwfr9fmVmZsput0uS7Ha7MjMz5ff7LZ4MAKLXJS72UlFRoYbDPWK+bkMopIqKQJvHQ03JMZzmP2uGQqqoqGj9WKR7jKeRQg0Nbc9j7xbjaaRQqO15GhJif77RcIKflySFmppiOM1/1jzJTDhWXl5em8fiKrBZWVkKBAIKh8Oy2+0Kh8MKBALHbSX8r7y8PNVsPxCbIX8g2eFQ3sDsNo8HK4MxnOZ7DodDebl9Wz0W3LkvxtNIjuRk5fXLafVYsHpvjKeRHI5k5WX3bvVYze7dMZ7mP79Dffq0efxAZWXshvmP73+HcmO+blcUV1sE6enpys/Pl9frlSR5vV4VFBQojUunAeiELDuDfeqpp7Rhwwbt379fkydPVmpqqlauXKmioiIVFxerrKxMTqdTHo/HqhEB4LRYFtiZM2dq5syZx92em5urpUuXWjARAHSsuNoiAICuhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAwhsABgCIEFAEMILAAYQmABwBACCwCGEFgAMITAAoAhBBYADCGwAGAIgQUAQwgsABhCYAHAkESrBwDQeezct0/+mpqYrpmVlqZ+GRkxXbOjEFgA7eavqdHERYtiuuaSqVM7bWDZIgAAQwgsABhCYAHAEAILAIYQWAAwhMACgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADAkbq+mVVVVpeLiYtXW1io1NVUej0c5OTlWjwUgjuzy++Xfty+ma2ZlZKhvVla77hu3gS0tLZXb7VZhYaHWrVunkpISLVmyxOqxAMQR/759uu+JJ2K65sLHHmt3YONyiyAYDMrn88nlckmSXC6XfD6famJ8oV8AOB22AwcORKwe4n/961//ksfj0cqVK1tuGzNmjIqLi/WjH/3IwskAoP3i8gwWALqCuAxsVlaWAoGAwuGwJCkcDisQCCirnfseABAP4jKw6enpys/Pl9frlSR5vV4VFBQoLS3N4skAoP3icg9WkiorK1VcXKy6ujo5nU55PB6de+65Vo8FAO0Wt4GNhbq6Ot1www26+eab9cADD1g6y6hRo5SUlKSkpCQdOXJEl1xyiR5++GElJlr3TLqmpia98MIL8nq9SkxMVCQS0bBhwzRlyhRL5jr6PerWrZsaGxs1YMAAjR07VhdddFHMZ/nfmZKSklpumzNnjvr06RMX8wwZMsTS3+2mpia9+OKL8nq9stvtSkxMVP/+/XXPPfdowIABMZ3lzjvv1JEjR9TU1KQdO3a0rF9QUKDf/OY3RtaM2+fBxsK7776rCy+8UF6vV1OnTlW3bt0snae0tFQDBw5UOBzWPffco/Xr12vkyJGWzfP444/r8OHDevnll5WSkqKmpiatXr1aR44csSz8R79HkrR+/XpNnz5dCxcu1KBBgyyZ539nigfxNM/jjz+uxsZGLV26VGeffbYikYjef/99VVZWxjywS5culSTt3r1b48aN04oVK4yvGZd7sLGyevVq3XnnnRo4cKA+/PBDq8dpceTIER05ckRnn322ZTPs2LFDGzZs0KOPPqqUlBRJUmJiom666SYlJydbNtcPXX311br55pu1fPlyq0dBK47+Ds2aNavld9lms+m6667TNddcY/F0sXHGnsF+9dVXqqur06WXXqpgMKjVq1fr2muvtXSmoqIiJSUladeuXbrssst0+eWXWzaLz+dT//795XQ6LZuhPS644AJt3LjR0hmO/twkyW636+WXX46beaZMmaIrrrjCkjk6y++QSWdsYP/0pz/phhtukM1m04gRI/TUU09p79696t27t2UzHf2v3eHDh1VUVKRXX31Vt912m2XzoH3i6b/kUvzNc9Q333yjxx57TI2NjRo2bJhmzJhh9UjGnZFbBN99953+/Oc/a/Xq1Ro1apTGjBmjpqYmvfPOO1aPJknq3r27hg8frk8//dSyGQoKCvTtt9+qrq7Oshna48svv4z5Xh7a5+jv0MGDByVJAwYM0IoVKzRmzBjV19dbPF1snJGB3bBhg3Jzc7VmzRqVl5ervLxcCxcu1Jo1a6weTZLU3NysrVu3qn///pbNkJOTo6uuukolJSU6dOiQpO9f8PHaa6+poaHBsrl+6IMPPtCqVat0++23Wz0KWnH0d+h3v/vdMUENhUIWThVbZ+QWwZo1a3T99dcfc9tFF12k5uZmbdmyRYMHD7ZkrqN7Z01NTRowYIB+9atfWTLHUbNnz9bzzz+vsWPHqlu3bi1P0/rhU5JiraioqOVpWuedd57mz5+vCy+80LJ5js70w+/Jo48+qvPPP9/CieLH7Nmz9cILL2jcuHFKTEyU0+lURkaGxo0bZ/VoMXFGPw8WAEw6I7cIACAWCCwAGEJgAcAQAgsAhhBYADCEwOKM9dxzz2no0KHa1453JZ0wYYImTJgQg6nQlZyRz4NF5xQMBvXKK69o48aNqq6uViQSUf/+/TVs2DDdeuutysjIsHpE4BgEFp3Cl19+qfvvv1+HDh2Sy+WS2+1WQkKCvv76a7399ttav369Vq1aZWz9RYsWGXtsdF0EFnHv4MGDeuihh2Sz2bRs2bLjLmQyadIkLVu2zOgMVl8rGJ0TgUXc++Mf/6i9e/equLi41atE9ejRQ5MnT275eOvWrXr99df1z3/+U/v371dqaqquvPJKTZkypdVr7NbV1WnBggXatGmTbDabrr76ak2fPl09evRouc/R/ddnn31W0vcXbb7xxhs1efJkZWRk6KWXXtLu3bt17rnnavr06Ro6dGhHfxvQCRFYxL2NGzeqe/fuuu6669p1//fee091dXUaNWqUevXqpYqKCpWXl2v79u0qKys77v6zZs1SZmamJk6cqK+++krl5eXy+/3t2hZ4//33VVtbq5tuukndu3fXa6+9poceekjl5eVKTU2N+mtF10JgEfcqKyuVk5PT7v+mT506VWedddYxtw0aNEizZ8/W3//+d1188cXHHMvMzNT8+fNls9kkSRkZGXrhhRf0ySefnPSi57t27dKbb77Z8o7HQ4YM0R133CGv1yu3293eLxFdFE/TQtw7dOhQVG9TczSukUhE9fX1OnDgQMsbI27btu24+7vd7pa4StKYMWMkSR999NFJ17r22muPeTv5/Px8paSkaNeuXe2eF10XZ7CIeykpKVFdg9bv92vhwoX66KOPWq5le9TRiz//0P9ed7dnz55yOp2qrq4+6VrnnHPOcbc5nc64v1A5YoPAIu7l5ubK5/Ppu+++O+k2QXNzs6ZOnaqamhqNGzdOubm5cjgcam5u1rRp09Tc3Hzc5/zw7PWoSKR9V/G02+2t3t7ez0fXxhYB4t6VV16pw4cP6/333z/pfb/++mtVVlZq2rRp+uUvf6kRI0bosssuU9++fdv8nB07dhzz8YEDB3Tw4EFlZ2ef9uw4sxFYxL2bb75ZvXv31vz58/Xvf//7uOP19fVavHixJCkhofVf6RUrVrT5+G+88cYxZ5wrV66UJMvejRVdB1sEiHtnn322nnzySd1///0aO3asXC6Xzj///JZXcnm9XqWmpmrSpEnKzc1V//79NX/+fPn9fqWmpuqjjz7S3r1723z8QCCg6dOn6yc/+YkqKir09ttv69JLLyWwOG0EFp3C+eefr1dffVUrVqzQX/7yF3m9Xknf/4HqpptuavnLf2Jiop5++mnNnTtXy5cvl91u1+WXX64FCxaosLCw1cd+4okntHTpUi1evFg2m00///nPdf/998fsa0PXxXtyAYAh7MECgCEEFgAMIbAAYAiBBQBDCCwAGEJgAcAQAgsAhhBYADCEwAKAIQQWAAz5fwaLI1CadJEuAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# let's grab that letter for the deck level with a simple for loop\n","levels = []\n","for level in deck:\n","    levels.append(level[0])\n","\n","cabin_df = pd.DataFrame(levels)\n","cabin_df.columns = ['Cabin']\n","cabin_df.sort_values(by='Cabin', inplace=True)\n","sns.catplot(x='Cabin', data=cabin_df, kind='count', palette='winter_d')"]},{"cell_type":"markdown","id":"6553c58d","metadata":{"papermill":{"duration":0.016765,"end_time":"2023-01-31T18:26:53.725552","exception":false,"start_time":"2023-01-31T18:26:53.708787","status":"completed"},"tags":[]},"source":["Interesting to note we have a 'T' deck value there which doesn't make sense, we  can drop it out with the following code:"]},{"cell_type":"code","execution_count":16,"id":"1b77358e","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:53.760859Z","iopub.status.busy":"2023-01-31T18:26:53.760103Z","iopub.status.idle":"2023-01-31T18:26:54.067084Z","shell.execute_reply":"2023-01-31T18:26:54.065832Z"},"papermill":{"duration":0.328228,"end_time":"2023-01-31T18:26:54.069958","exception":false,"start_time":"2023-01-31T18:26:53.74173","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0b53978d0>"]},"execution_count":16,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["cabin_df = cabin_df[cabin_df.Cabin != 'T']\n","sns.catplot(x='Cabin', data=cabin_df, kind='count', palette='summer')"]},{"cell_type":"markdown","id":"2df66dd3","metadata":{"papermill":{"duration":0.015931,"end_time":"2023-01-31T18:26:54.103458","exception":false,"start_time":"2023-01-31T18:26:54.087527","status":"completed"},"tags":[]},"source":["Great now that we've analyzed the distribution by decks, let's go ahead and answer our third question."]},{"cell_type":"markdown","id":"0e92ee86","metadata":{"papermill":{"duration":0.016353,"end_time":"2023-01-31T18:26:54.136317","exception":false,"start_time":"2023-01-31T18:26:54.119964","status":"completed"},"tags":[]},"source":["# 3. Where did the passengers come from?"]},{"cell_type":"code","execution_count":17,"id":"62266c6c","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:54.174154Z","iopub.status.busy":"2023-01-31T18:26:54.171468Z","iopub.status.idle":"2023-01-31T18:26:54.192514Z","shell.execute_reply":"2023-01-31T18:26:54.191235Z"},"papermill":{"duration":0.042236,"end_time":"2023-01-31T18:26:54.195074","exception":false,"start_time":"2023-01-31T18:26:54.152838","status":"completed"},"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","      <th>Person</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","      <td>male</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","      <td>female</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","      <td>female</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","      <td>female</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","      <td>male</td>\n","    </tr>\n","  </tbody>\n","</table>\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","                                                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","   Parch            Ticket     Fare Cabin Embarked  Person  \n","0      0         A/5 21171   7.2500   NaN        S    male  \n","1      0          PC 17599  71.2833   C85        C  female  \n","2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n","3      0            113803  53.1000  C123        S  female  \n","4      0            373450   8.0500   NaN        S    male  "]},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":["titanic_df.head()"]},{"cell_type":"markdown","id":"ccc0bf59","metadata":{"papermill":{"duration":0.016959,"end_time":"2023-01-31T18:26:54.229155","exception":false,"start_time":"2023-01-31T18:26:54.212196","status":"completed"},"tags":[]},"source":["Note here that the Embarked column has C, Q, and S values. Reading about the project on Kaggle you'll note that these stand for Cherbourg, Queenstown, Southhampton."]},{"cell_type":"code","execution_count":18,"id":"f6a02575","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:54.265559Z","iopub.status.busy":"2023-01-31T18:26:54.265119Z","iopub.status.idle":"2023-01-31T18:26:54.708369Z","shell.execute_reply":"2023-01-31T18:26:54.706852Z"},"papermill":{"duration":0.464331,"end_time":"2023-01-31T18:26:54.711164","exception":false,"start_time":"2023-01-31T18:26:54.246833","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad165690>"]},"execution_count":18,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 406.6x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Now we can make a quick factorplot to check out the results, note the \n","# order argument, used to deal with NaN values\n","\n","sns.catplot(x='Embarked', data=titanic_df, hue='Pclass', kind='count', order=['C', 'Q', 'S'])"]},{"cell_type":"markdown","id":"83f94104","metadata":{"papermill":{"duration":0.016661,"end_time":"2023-01-31T18:26:54.745259","exception":false,"start_time":"2023-01-31T18:26:54.728598","status":"completed"},"tags":[]},"source":["An interesting find here is that in Queenstown, almost all the passengers that boarded there were 3rd class. It would be intersting to look at the economics of that town in that time period for further investigation."]},{"cell_type":"markdown","id":"e26a436b","metadata":{"papermill":{"duration":0.01682,"end_time":"2023-01-31T18:26:54.779564","exception":false,"start_time":"2023-01-31T18:26:54.762744","status":"completed"},"tags":[]},"source":["# 4. Who was alone and who was with family?"]},{"cell_type":"code","execution_count":19,"id":"81c4318b","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:54.815291Z","iopub.status.busy":"2023-01-31T18:26:54.814862Z","iopub.status.idle":"2023-01-31T18:26:54.833382Z","shell.execute_reply":"2023-01-31T18:26:54.832216Z"},"papermill":{"duration":0.039704,"end_time":"2023-01-31T18:26:54.835844","exception":false,"start_time":"2023-01-31T18:26:54.79614","status":"completed"},"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","      <th>Person</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","      <td>male</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","      <td>female</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","      <td>female</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","      <td>female</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","      <td>male</td>\n","    </tr>\n","  </tbody>\n","</table>\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","                                                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","   Parch            Ticket     Fare Cabin Embarked  Person  \n","0      0         A/5 21171   7.2500   NaN        S    male  \n","1      0          PC 17599  71.2833   C85        C  female  \n","2      0  STON/O2. 3101282   7.9250   NaN        S  female  \n","3      0            113803  53.1000  C123        S  female  \n","4      0            373450   8.0500   NaN        S    male  "]},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":["titanic_df.head()"]},{"cell_type":"code","execution_count":20,"id":"d600daba","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:54.872959Z","iopub.status.busy":"2023-01-31T18:26:54.872473Z","iopub.status.idle":"2023-01-31T18:26:54.883589Z","shell.execute_reply":"2023-01-31T18:26:54.882353Z"},"papermill":{"duration":0.033094,"end_time":"2023-01-31T18:26:54.886124","exception":false,"start_time":"2023-01-31T18:26:54.85303","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["0      1\n","1      1\n","2      0\n","3      1\n","4      0\n","      ..\n","886    0\n","887    0\n","888    3\n","889    0\n","890    0\n","Name: Alone, Length: 891, dtype: int64"]},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":["# Let's start by adding a new column to define alone\n","# We'll add the parent/child column with the sibsp column\n","\n","titanic_df['Alone'] = titanic_df.SibSp + titanic_df.Parch\n","titanic_df.Alone"]},{"cell_type":"markdown","id":"02b4b846","metadata":{"papermill":{"duration":0.016775,"end_time":"2023-01-31T18:26:54.920097","exception":false,"start_time":"2023-01-31T18:26:54.903322","status":"completed"},"tags":[]},"source":["Now we know that if the Alone column is anything but 0, then the passenger had family aboard and wasn't alone. So let's change the column now so that if the value is greater than 0, we know the passenger was with his/her family, otherwise they were alone."]},{"cell_type":"code","execution_count":21,"id":"764a0be3","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:54.958498Z","iopub.status.busy":"2023-01-31T18:26:54.958031Z","iopub.status.idle":"2023-01-31T18:26:54.9667Z","shell.execute_reply":"2023-01-31T18:26:54.96539Z"},"papermill":{"duration":0.030984,"end_time":"2023-01-31T18:26:54.969307","exception":false,"start_time":"2023-01-31T18:26:54.938323","status":"completed"},"tags":[]},"outputs":[],"source":["# Look for > 0 or == 0 to set alone status\n","titanic_df.loc[titanic_df['Alone'] > 0, 'Alone'] = 'with Family'\n","titanic_df.loc[titanic_df['Alone'] == 0, 'Alone'] = 'Alone'"]},{"cell_type":"code","execution_count":22,"id":"a3b3fec0","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:55.007256Z","iopub.status.busy":"2023-01-31T18:26:55.006751Z","iopub.status.idle":"2023-01-31T18:26:55.028251Z","shell.execute_reply":"2023-01-31T18:26:55.026893Z"},"papermill":{"duration":0.043025,"end_time":"2023-01-31T18:26:55.030908","exception":false,"start_time":"2023-01-31T18:26:54.987883","status":"completed"},"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","      <th>Person</th>\n","      <th>Alone</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","      <td>male</td>\n","      <td>with Family</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","      <td>female</td>\n","      <td>with Family</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","      <td>female</td>\n","      <td>Alone</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","      <td>female</td>\n","      <td>with Family</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","      <td>male</td>\n","      <td>Alone</td>\n","    </tr>\n","  </tbody>\n","</table>\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","                                                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","   Parch            Ticket     Fare Cabin Embarked  Person        Alone  \n","0      0         A/5 21171   7.2500   NaN        S    male  with Family  \n","1      0          PC 17599  71.2833   C85        C  female  with Family  \n","2      0  STON/O2. 3101282   7.9250   NaN        S  female        Alone  \n","3      0            113803  53.1000  C123        S  female  with Family  \n","4      0            373450   8.0500   NaN        S    male        Alone  "]},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":["# Let's check to make sure it worked\n","titanic_df.head()"]},{"cell_type":"code","execution_count":23,"id":"658f6093","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:55.071187Z","iopub.status.busy":"2023-01-31T18:26:55.070744Z","iopub.status.idle":"2023-01-31T18:26:55.334878Z","shell.execute_reply":"2023-01-31T18:26:55.333521Z"},"papermill":{"duration":0.288096,"end_time":"2023-01-31T18:26:55.337656","exception":false,"start_time":"2023-01-31T18:26:55.04956","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad072d50>"]},"execution_count":23,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Now let's get a simple visualization!\n","sns.catplot(x='Alone', data=titanic_df, kind='count', palette='Blues', \n","            order=['Alone', 'with Family'])"]},{"cell_type":"markdown","id":"ebb6ea38","metadata":{"papermill":{"duration":0.019984,"end_time":"2023-01-31T18:26:55.376273","exception":false,"start_time":"2023-01-31T18:26:55.356289","status":"completed"},"tags":[]},"source":["Great work! Now that we've throughly analyzed the data let's go ahead and take a look at the most interesting (and open-ended) question: *What factors helped someone survive the sinking?*"]},{"cell_type":"markdown","id":"7b1309d4","metadata":{"papermill":{"duration":0.019229,"end_time":"2023-01-31T18:26:55.414179","exception":false,"start_time":"2023-01-31T18:26:55.39495","status":"completed"},"tags":[]},"source":["# 5. What factors helped someone survive the sinking?"]},{"cell_type":"code","execution_count":24,"id":"5f10e448","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:55.454595Z","iopub.status.busy":"2023-01-31T18:26:55.453729Z","iopub.status.idle":"2023-01-31T18:26:55.726175Z","shell.execute_reply":"2023-01-31T18:26:55.725256Z"},"papermill":{"duration":0.296113,"end_time":"2023-01-31T18:26:55.728711","exception":false,"start_time":"2023-01-31T18:26:55.432598","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad0d0390>"]},"execution_count":24,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's start by creating a new column for legibility purposes through mapping\n","titanic_df['Survivor'] = titanic_df.Survived.map({0:'No', 1:'Yes'})\n","\n","# Let's just get a quick overall view of survied vs died. \n","sns.catplot(x='Survivor', data=titanic_df, kind='count')"]},{"cell_type":"markdown","id":"9ee2cad7","metadata":{"papermill":{"duration":0.020503,"end_time":"2023-01-31T18:26:55.76811","exception":false,"start_time":"2023-01-31T18:26:55.747607","status":"completed"},"tags":[]},"source":["So quite a few more people died than those who survived. Let's see if the class of the passengers had an effect on their survival rate, since the movie Titanic popularized the notion that the 3rd class passengers did not do as well as their 1st and 2nd class counterparts."]},{"cell_type":"code","execution_count":25,"id":"4555c465","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:55.809341Z","iopub.status.busy":"2023-01-31T18:26:55.80834Z","iopub.status.idle":"2023-01-31T18:26:56.179649Z","shell.execute_reply":"2023-01-31T18:26:56.178704Z"},"papermill":{"duration":0.394311,"end_time":"2023-01-31T18:26:56.182135","exception":false,"start_time":"2023-01-31T18:26:55.787824","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad0729d0>"]},"execution_count":25,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's use a factor plot again, but now considering class\n","sns.catplot(x='Pclass', y='Survived', data=titanic_df, kind='point')"]},{"cell_type":"markdown","id":"30d5701f","metadata":{"papermill":{"duration":0.020294,"end_time":"2023-01-31T18:26:56.222182","exception":false,"start_time":"2023-01-31T18:26:56.201888","status":"completed"},"tags":[]},"source":["Look like survival rates for the 3rd class are substantially lower! But maybe this effect is being caused by the large amount of men in the 3rd class in combination with the women and children first policy. Let's use 'hue' to get a clearer picture on this."]},{"cell_type":"code","execution_count":26,"id":"7570ee1f","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:56.263308Z","iopub.status.busy":"2023-01-31T18:26:56.262887Z","iopub.status.idle":"2023-01-31T18:26:57.021669Z","shell.execute_reply":"2023-01-31T18:26:57.020352Z"},"papermill":{"duration":0.782645,"end_time":"2023-01-31T18:26:57.024392","exception":false,"start_time":"2023-01-31T18:26:56.241747","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad019690>"]},"execution_count":26,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 437.975x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's use a factor plot again, but now considering class and gender\n","sns.catplot(x='Pclass', y='Survived', data=titanic_df, hue='Person', kind='point')"]},{"cell_type":"markdown","id":"d0cc3cdc","metadata":{"papermill":{"duration":0.019195,"end_time":"2023-01-31T18:26:57.063397","exception":false,"start_time":"2023-01-31T18:26:57.044202","status":"completed"},"tags":[]},"source":["From this data it looks like being a male or being in 3rd class were both not favourable for survival. Even regardless of class the result of being a male in any class dramatically decreases your chances of survival.\n","\n","But what about age? Did being younger or older have an effect on survival rate?"]},{"cell_type":"code","execution_count":27,"id":"2dc8d8f6","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:57.104928Z","iopub.status.busy":"2023-01-31T18:26:57.104428Z","iopub.status.idle":"2023-01-31T18:26:57.573111Z","shell.execute_reply":"2023-01-31T18:26:57.571629Z"},"papermill":{"duration":0.492744,"end_time":"2023-01-31T18:26:57.575593","exception":false,"start_time":"2023-01-31T18:26:57.082849","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ad00d250>"]},"execution_count":27,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's use a linear plot on age versus survival\n","sns.lmplot(x='Age', y='Survived', data=titanic_df)"]},{"cell_type":"markdown","id":"8131cd44","metadata":{"papermill":{"duration":0.020758,"end_time":"2023-01-31T18:26:57.616965","exception":false,"start_time":"2023-01-31T18:26:57.596207","status":"completed"},"tags":[]},"source":["Looks like there is a general trend that the older the passenger was, the less likely they survived. Let's go ahead and use hue to take a look at the effect of class and age."]},{"cell_type":"code","execution_count":28,"id":"299f6a16","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:57.659712Z","iopub.status.busy":"2023-01-31T18:26:57.659263Z","iopub.status.idle":"2023-01-31T18:26:58.686627Z","shell.execute_reply":"2023-01-31T18:26:58.685385Z"},"papermill":{"duration":1.051553,"end_time":"2023-01-31T18:26:58.689078","exception":false,"start_time":"2023-01-31T18:26:57.637525","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0acee6050>"]},"execution_count":28,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 406.6x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's use a linear plot on age versus survival using hue for class seperation\n","sns.lmplot(x='Age', y='Survived',hue='Pclass', data=titanic_df)"]},{"cell_type":"markdown","id":"7a9819cc","metadata":{"papermill":{"duration":0.02322,"end_time":"2023-01-31T18:26:58.73367","exception":false,"start_time":"2023-01-31T18:26:58.71045","status":"completed"},"tags":[]},"source":["We can also use the x_bin argument to clean up this figure and grab the data and bin it by age with a std attached!"]},{"cell_type":"code","execution_count":29,"id":"285aa5ab","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:26:58.779296Z","iopub.status.busy":"2023-01-31T18:26:58.778117Z","iopub.status.idle":"2023-01-31T18:27:00.070293Z","shell.execute_reply":"2023-01-31T18:27:00.069113Z"},"papermill":{"duration":1.317736,"end_time":"2023-01-31T18:27:00.07308","exception":false,"start_time":"2023-01-31T18:26:58.755344","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0ace4f2d0>"]},"execution_count":29,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 406.6x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Let's use a linear plot on age versus survival using hue for class seperation\n","generations = [10, 20, 40, 60, 80]\n","sns.lmplot(x='Age', y='Survived', hue='Pclass', data=titanic_df, palette='winter', x_bins=generations)"]},{"cell_type":"markdown","id":"50b8fabe","metadata":{"papermill":{"duration":0.021766,"end_time":"2023-01-31T18:27:00.119165","exception":false,"start_time":"2023-01-31T18:27:00.097399","status":"completed"},"tags":[]},"source":["Interesting find on the older 1st class passengers! What about if we relate gender and age with the survival set?"]},{"cell_type":"code","execution_count":30,"id":"5e18e342","metadata":{"execution":{"iopub.execute_input":"2023-01-31T18:27:00.165672Z","iopub.status.busy":"2023-01-31T18:27:00.164997Z","iopub.status.idle":"2023-01-31T18:27:01.106514Z","shell.execute_reply":"2023-01-31T18:27:01.105551Z"},"papermill":{"duration":0.968216,"end_time":"2023-01-31T18:27:01.109002","exception":false,"start_time":"2023-01-31T18:27:00.140786","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7ff0acc96a90>"]},"execution_count":30,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 437.975x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["sns.lmplot(x='Age', y='Survived', hue='Sex', data=titanic_df, palette='winter', x_bins=generations)"]},{"cell_type":"markdown","id":"c9340c11","metadata":{"papermill":{"duration":0.022239,"end_time":"2023-01-31T18:27:01.153717","exception":false,"start_time":"2023-01-31T18:27:01.131478","status":"completed"},"tags":[]},"source":["Awesome! we've gotten some really great insights on how gender,age, and class all related to a passengers chance of survival. Now you take control: Answer the following questions using pandas and seaborn:\n","\n","    1.) Did the deck have an effect on the passengers survival rate? Did this answer match up with your intuition?\n","    2.) Did having a family member increase the odds of surviving the crash?"]},{"cell_type":"markdown","id":"74f9ec85","metadata":{"papermill":{"duration":0.021812,"end_time":"2023-01-31T18:27:01.197606","exception":false,"start_time":"2023-01-31T18:27:01.175794","status":"completed"},"tags":[]},"source":["## References:\n","- [Jose Portilla Udemy Course: Learning Python for Data Analysis and Visualization](https://www.udemy.com/course/learning-python-for-data-analysis-and-visualization/)"]}],"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":"3.7.12"},"papermill":{"default_parameters":{},"duration":24.441847,"end_time":"2023-01-31T18:27:02.143147","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2023-01-31T18:26:37.7013","version":"2.3.4"}},"nbformat":4,"nbformat_minor":5}