fix issues

Author: tomvannuenen

data/.DS_Store

@@ -745,7 +745,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

lessons/.ipynb_checkpoints/1_Functions_and_Conditionals-checkpoint.ipynb

@@ -158,7 +158,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "numbers = [12, 20, 43, 88, 97, 100, 105, 110]\n",
+    "numbers = [12, 20.2, 43, 88.88, 97, 100, 105, 110.9167]\n",
     "\n",
     "for number in numbers:\n",
     "    if number > 100:\n",
@@ -185,7 +185,7 @@
     "    \n",
     "The result of this is a single list, number, or string with a summary value for the entire collection being looped over.\n",
     "\n",
-    "Returning to the tire pressure example, we can make a new list with all of the tire pressures rounded:"
+    "We can make a new list with all of the rounded numbers:"
    ]
   },
   {
@@ -298,95 +298,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><div id=882af88a-033f-431f-a12e-16e795baa656 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('882af88a-033f-431f-a12e-16e795baa656').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>country</th>\n",
-       "      <th>year</th>\n",
-       "      <th>pop</th>\n",
-       "      <th>continent</th>\n",
-       "      <th>lifeExp</th>\n",
-       "      <th>gdpPercap</th>\n",
-       "      <th>gniPercap</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>1962</td>\n",
-       "      <td>10267083.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>31.997</td>\n",
-       "      <td>853.100710</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>1967</td>\n",
-       "      <td>11537966.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>34.020</td>\n",
-       "      <td>836.197138</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>1972</td>\n",
-       "      <td>13079460.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>36.088</td>\n",
-       "      <td>739.981106</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>1977</td>\n",
-       "      <td>14880372.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>38.438</td>\n",
-       "      <td>786.113360</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>1982</td>\n",
-       "      <td>12881816.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>39.854</td>\n",
-       "      <td>978.011439</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table></div>"
-      ],
-      "text/plain": [
-       "       country  year         pop continent  lifeExp   gdpPercap  gniPercap\n",
-       "0  Afghanistan  1962  10267083.0      Asia   31.997  853.100710        NaN\n",
-       "1  Afghanistan  1967  11537966.0      Asia   34.020  836.197138        NaN\n",
-       "2  Afghanistan  1972  13079460.0      Asia   36.088  739.981106        NaN\n",
-       "3  Afghanistan  1977  14880372.0      Asia   38.438  786.113360        NaN\n",
-       "4  Afghanistan  1982  12881816.0      Asia   39.854  978.011439        NaN"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = pd.read_csv('~/Documents/GitHub/DEV/Python-Intermediate-Pilot/data/gapminder_gni.csv')\n",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv('../data/gapminder_gni.csv')\n",
     "df.head()"
    ]
   },
@@ -735,6 +653,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
     "# YOUR CODE HERE\n",
     "\n",
     "country_list = [..., ..., ...]\n",
@@ -793,7 +713,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

lessons/.ipynb_checkpoints/2_Iteration_and_Visualization-checkpoint.ipynb

@@ -131,7 +131,7 @@
    "source": [
     "## Locating the Data\n",
     "\n",
-    "Try to locate the files in the \"chis_data\" folder, which is in the \"data\" folder, which is in the main \"Python-Fundamentals\" folder. Using `pd.read_csv()`, read in all three data frames and assign them to the three variables defined below.\n",
+    "Try to locate the files in the \"chis_data\" folder, which is in the \"data\" folder, which is in the main \"Python-Intermediate\" folder. Using `pd.read_csv()`, read in all three data frames and assign them to the three variables defined below.\n",
     "\n",
     "💡 **Tip**: You can use Jupyter Lab's File Browser to the left of your screen to get a sense of where the \"chis_data\" folder is.\n",
     "\n",
@@ -194,6 +194,17 @@
     "# YOUR CODE HERE\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Let's reset the index\n",
+    "df.reset_index(drop=True)\n",
+    "df"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -270,12 +281,14 @@
    "source": [
     "## Creating a Function\n",
     "\n",
-    "It turns out that poverty is expressed \"as Times of 100% Federal Poverty Line (FPL)\". One approach to this could be to see if we can find differences in general health for people **below and above the poverty line**. \n",
+    "It turns out that poverty is expressed \"as Times of 100% Federal Poverty Line (FPL)\".\n",
+    "For instance, `\"100-199%\" FPL\"` means that the row's income was 1-1.99 times the FPL.\n",
+    "One approach to this statistic could be to see if we can find differences in general health for people **below and above the poverty line**. \n",
     "\n",
     "To do this, we can create a function that takes in values of the `poverty_level` column and outputs whether that value is above or below the poverty line.\n",
     "\n",
     "1. Create a new function called `assign_level`. It takes one parameter, which we'll call `i`.\n",
-    "2. If `i` is `0-99% FPL`, return 0. In all other cases, return 1."
+    "2. If `i` is `\"0-99% FPL\"`, return 0. In all other cases, return 1."
    ]
   },
   {
@@ -429,7 +442,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,