Python Syntax Medical Insurance Project.ipynb

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   "source": [
    "# Python Syntax: Medical Insurance Project"
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   "source": [
    "Suppose you are a medical professional curious about how certain factors contribute to medical insurance costs. Using a formula that estimates a person's yearly insurance costs, you will investigate how different factors such as age, sex, BMI, etc. affect the prediction."
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   "source": [
    "## Setting up Factors"
   ]
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    "1. Our first step is to create the variables for each factor we will consider when estimating medical insurance costs.\n",
    "\n",
    "   These are the variables we will need to create:\n",
    "   - `age`: age of the individual in years\n",
    "   - `sex`: 0 for female, 1 for male*\n",
    "   - `bmi`: individual's body mass index\n",
    "   - `num_of_children`: number of children the individual has\n",
    "   - `smoker`: 0 for a non-smoker, 1 for a smoker\n",
    "   \n",
    "   In the code block below, create the following variables for a **28**-year-old, **nonsmoking woman** who has **three children** and a **BMI** of **26.2**.\n",
    "   \n",
    "   **Note**: We are using this [medical insurance dataset](https://www.kaggle.com/mirichoi0218/insurance) as a guide, which unfortunately does not include data for non-binary individuals."
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    "# create the initial variables below\n",
    "age = 28\n",
    "sex = 0\n",
    "bmi = 26.2\n",
    "num_of_children = 3\n",
    "smoker = 0"
   ]
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   "source": [
    "## Working with the Formula"
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    "2. After the declaration of the variables, create a variable called `insurance_cost` that utilizes the following formula:\n",
    "\n",
    "   $$\n",
    "   \\begin{aligned}\n",
    "   insurance\\_cost = 250*age - 128*sex \\\\\n",
    "   + 370*bmi + 425*num\\_of\\_children \\\\\n",
    "   + 24000*smoker - 12500 \\\\\n",
    "   \\end{aligned}\n",
    "   $$"
   ]
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   "id": "91f86188",
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   "source": [
    "# Add insurance estimate formula below\n",
    "insurance_cost = 205 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n"
   ]
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    "3. Let's display this value in an informative way. Print out the following string in the kernel:\n",
    "\n",
    "   ```\n",
    "   This person's insurance cost is {insurance_cost} dollars.\n",
    "   ```\n",
    "   \n",
    "   You will need to use string concatenation, including the `str()` function to print out the `insurance_cost`."
   ]
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   "cell_type": "code",
   "execution_count": 14,
   "id": "cf6d3790",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This person's insurance cost is 4209.0 dollars.\n"
     ]
    }
   ],
   "source": [
    "print('This person\\'s insurance cost is ' + str(insurance_cost) + ' dollars.')"
   ]
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   "source": [
    "## Looking at Age Factor"
   ]
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   "source": [
    "4. We have seen how our formula can estimate costs for one individual. Now let's play with some individual factors to see what role each one plays in our estimation!\n",
    "\n",
    "   Let's start with the `age` factor. Using a plus-equal operator, add 4 years to our `age` variable."
   ]
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   "cell_type": "code",
   "execution_count": 15,
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   "source": [
    "age += 4"
   ]
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   "source": [
    "5. Now that we have changed our `age` value, we want to recalculate our insurance cost. Declare a new variable called `new_insurance_cost` in the code block below.\n",
    "\n",
    "   Make sure you leave the `insurance_cost` variable the same as in Task 2. We will use it later in our program!"
   ]
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   "source": [
    "new_insurance_cost = 205 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500"
   ]
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   "source": [
    "6. Next, we want to find the difference between our `new_insurance_cost` and `insurance_cost`. To do this, let's create a new variable called `change_in_insurance_cost` and set it equal to the difference between `new_insurance_cost` and `insurance_cost`.\n",
    "\n",
    "   Note: depending on the order that we subtract (eg., `new_insurance_cost - insurance_cost` vs. `insurance_cost - new_insurance_cost`), we'll get a positive or negative version of the same number. To make this difference interpretable, let's calculate `new_insurance cost - insurance_cost`. Then we can say, \"people who are four years older have estimated insurance costs that are `change_in_insurance_cost` dollars different, where the sign of `change_in_insurance_cost` tells us whether the cost is higher or lower\"."
   ]
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   "cell_type": "code",
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   "source": [
    "change_in_insurance_cost = new_insurance_cost - insurance_cost"
   ]
  },
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   "source": [
    "7. We want to display this information in an informative way similar to the output from instruction 3. In the code block below, print the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
    "\n",
    "   ```\n",
    "   The change in cost of insurance after increasing the age by 4 years is XXX dollars.\n",
    "   ```\n",
    "   \n",
    "   Doing this will tell us how 4 years in age affects medical insurance cost estimates assuming that all other variables remain the same.\n",
    "   \n",
    "   You will need to concatenate strings and use the `str()` method."
   ]
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   "cell_type": "code",
   "execution_count": 21,
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     "text": [
      "The change in cost of insurance after increasing the age by 4 years is 820.0 dollars.\n"
     ]
    }
   ],
   "source": [
    "print('The change in cost of insurance after increasing the age by 4 years is ' + str(change_in_insurance_cost) + ' dollars.')"
   ]
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   "source": [
    "## Looking at BMI Factor"
   ]
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   "source": [
    "8. Now that you have looked at the age factor, let's move onto another one: BMI. First, we have to redefine our `age` variable to be its original value.\n",
    "\n",
    "   Set `age` to `28`. This will reset its value and allow us to focus on just the change in the BMI factor moving forward.\n",
    "   \n",
    "   On the next line, using the plus-equal operator, add `3.1` to our `bmi` variable."
   ]
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    "age = 28\n",
    "bmi += 3.1"
   ]
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   "source": [
    "9. Now let's find out how a change in BMI affects insurance costs. Our next steps are pretty much the same as we have done before when looking at `age`.\n",
    "   1. Below the line where `bmi` was increased by `3.1`, rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
    "   2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
    "   3. Display the following string in the output terminal, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
    "   \n",
    "   ```py\n",
    "   The change in estimated insurance cost after increasing BMI by 3.1 is XXX dollars.\n",
    "   ```"
   ]
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  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "19d121c8",
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "The change in estimated insurance cost after increasing BMI by 3.1 is 1147.0 dollars.\n"
     ]
    }
   ],
   "source": [
    "new_insurance_cost = 205 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
    "change = new_insurance_cost - insurance_cost\n",
    "print('The change in estimated insurance cost after increasing BMI by 3.1 is ' + str(change) + ' dollars.')"
   ]
  },
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   "source": [
    "## Looking at Male vs. Female Factor"
   ]
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   "source": [
    "10. Let's look at the effect sex has on medical insurance costs. Before we make any additional changes, first reassign your `bmi` variable back to its original value of `26.2`.\n",
    "\n",
    "    On a new line of code in the code block below, reassign the value of `sex` to `1`. A reminder that `1` identifies male individuals and `0` identifies female individuals."
   ]
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   "cell_type": "code",
   "execution_count": 32,
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   "source": [
    "bmi -= 3.1\n",
    "sex = 1"
   ]
  },
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   "source": [
    "11. Perform the steps below!\n",
    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
    "    2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
    "    3. Display the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
    "    ```\n",
    "    The change in estimated cost for being male instead of female is XXX dollars.\n",
    "    ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ce2da0e8",
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     "name": "stdout",
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     "text": [
      "The change in estimated cost for being maile instead of female is -1275.0 dollars.\n"
     ]
    }
   ],
   "source": [
    "new_insurance_cost = 205 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
    "change = new_insurance_cost - insurance_cost\n",
    "print('The change in estimated cost for being maile instead of female is ' + str(change) + ' dollars.')"
   ]
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   "source": [
    "12. Notice that this time you got a negative value for `change_in_insurance_cost`. Let's think about what that means. We changed the sex variable from `0` (female) to `1` (male) and it decreased the estimated insurance costs.\n",
    "\n",
    "    This means that men tend to have lower medical costs on average than women. Reflect on the other findings you have dug up from this investigation so far."
   ]
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   "source": [
    "## Extra Practice"
   ]
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   "source": [
    "13. Great job on the project!!!\n",
    "\n",
    "    So far we have looked at 3 of the 5 factors in the insurance costs formula. The two remaining are `smoker` and `num_of_children`. If you want to keep challenging yourself, spend some time investigating these factors!\n",
    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
    "    2. Save the difference between `new_insurance_cost` in a variable called `change_in_insurance_cost`.\n",
    "    3. Display the information below!"
   ]
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