Debo DC 7

Mod0/CodeChallenges/Lecture7CC.ipynb

@@ -49,15 +49,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 169,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Team Name: Celtics\n",
+      "Sport: Basketball\n",
+      "Number of Players: 17\n",
+      "Team Captain: Jaylen Brown, Jayson Tatum, or Al Horford\n"
+     ]
+    }
+   ],
    "source": [
     "# Assign the variables\n",
-    "team_name = None  # Replace None with the team name\n",
-    "sport = None      # Replace None with the sport\n",
-    "num_players = None  # Replace None with the number of players\n",
-    "team_captain = None  # Replace None with the team captain's name\n",
+    "team_name = \"Celtics\"  # Replace None with the team name\n",
+    "sport = \"Basketball\"      # Replace None with the sport\n",
+    "num_players = 17  # Replace None with the number of players\n",
+    "team_captain = \"Jaylen Brown, Jayson Tatum, or Al Horford\"  # Replace None with the team captain's name\n",
     "\n",
     "# Print the variables\n",
     "print(\"Team Name:\", team_name)\n",
@@ -88,18 +99,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 66,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Uppercase Team Name: CELTICS\n",
+      "Does the captain's name contain 'a'?  Yes!\n",
+      "Updated Sport Name: Hoops\n"
+     ]
+    }
+   ],
    "source": [
     "# String manipulations\n",
-    "uppercase_team_name = None  # Convert the team name to uppercase\n",
-    "contains_a = None           # Check if the captain's name contains the letter \"a\"\n",
-    "new_sport = None            # Replace \"Basketball\" with \"Hoops\"\n",
+    "uppercase_team_name = str.upper(team_name)  # Convert the team name to uppercase\n",
+    "   try:\n",
+    "   contains_a = team_captain.index(\"a\")\n",
+    "   if contains_a > 0:\n",
+    "        yesno= \"Yes!\"\n",
+    "except ValueError:\n",
+    "    yesno = \"No.\"  # Check if the captain's name contains the letter \"a\"\n",
+    "new_sport = sport.replace(\"Basketball\",\"Hoops\")            # Replace \"Basketball\" with \"Hoops\"\n",
     "\n",
     "# Print the results\n",
     "print(\"Uppercase Team Name:\", uppercase_team_name)\n",
-    "print(\"Does the captain's name contain 'a'?\", contains_a)\n",
+    "print(\"Does the captain's name contain 'a'? \", yesno)\n",
     "print(\"Updated Sport Name:\", new_sport)"
    ]
   },
@@ -124,19 +150,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 170,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Players List: ['Jaylen Brown', 'Torrey Craig', 'JD Davison', 'Sam Hauser', 'Jrue Holiday', 'Al Horford', 'Luke Kornet', 'Miles Norris', 'Drew Peterson', 'Kristaps Porziņģis', 'Payton Pritchard', 'Neemias Queta', 'Baylor Scheierman', 'Jayson Tatum', 'Xavier Tillman', 'Jordan Walsh', 'Derrick White', 'Debo Odutola']\n",
+      "First Player: Jaylen Brown\n",
+      "Last Player: Derrick White\n"
+     ]
+    }
+   ],
    "source": [
     "# Create a list of players\n",
-    "players = None  # Replace None with a list of player names\n",
+    "players = [\"Jaylen Brown\", \"Torrey Craig\", \"JD Davison\", \"Sam Hauser\", \"Jrue Holiday\", \"Al Horford\", \"Luke Kornet\", \"Miles Norris\", \"Drew Peterson\", \"Kristaps Porziņģis\", \"Payton Pritchard\", \"Neemias Queta\", \"Baylor Scheierman\", \"Jayson Tatum\", \"Xavier Tillman\", \"Jordan Walsh\", \"Derrick White\"]  # Replace None with a list of player names\n",
     "\n",
     "# Access the first and last players\n",
-    "first_player = None  # Access the first player\n",
-    "last_player = None   # Access the last player\n",
+    "first_player = players[0]  # Access the first player\n",
+    "last_player = players[-1]   # Access the last player\n",
     "\n",
     "# Add a new player to the list\n",
-    "players.append(None)  # Add \"Jamie Carter\"\n",
+    "players.append(\"Debo Odutola\")  # Add \"Jamie Carter\" (Adding myself instead)\n",
+    "\n",
     "\n",
     "# Print the results\n",
     "print(\"Players List:\", players)\n",
@@ -165,23 +202,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 171,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Team Info: {'Team Name': 'Celtics', 'Sport': 'Basketball', 'Players': ['Jaylen Brown', 'Torrey Craig', 'JD Davison', 'Sam Hauser', 'Jrue Holiday', 'Al Horford', 'Luke Kornet', 'Miles Norris', 'Drew Peterson', 'Kristaps Porziņģis', 'Payton Pritchard', 'Neemias Queta', 'Baylor Scheierman', 'Jayson Tatum', 'Xavier Tillman', 'Jordan Walsh', 'Derrick White', 'Debo Odutola'], 'Positions': ['Point Guard', 'Shooting Guard', 'Small Forward', 'Power Forward', 'Center']}\n",
+      "Position of Second Player: Shooting Guard\n",
+      "Number of Guards: 2\n"
+     ]
+    }
+   ],
    "source": [
     "# Create a dictionary\n",
     "team_info = {\n",
-    "    \"Team Name\": None,  # Replace None with the team name\n",
-    "    \"Sport\": None,      # Replace None with the sport\n",
-    "    \"Players\": None,    # Replace None with the list of players\n",
-    "    \"Positions\": None   # Replace None with the list of positions\n",
+    "    \"Team Name\": \"Celtics\",  # Replace None with the team name\n",
+    "    \"Sport\": \"Basketball\",      # Replace None with the sport\n",
+    "    \"Players\": players,    # Replace None with the list of players\n",
+    "    \"Positions\": [\"Point Guard\", \"Shooting Guard\", \"Small Forward\", \"Power Forward\", \"Center\"]  # Replace None with the list of positions\n",
     "}\n",
     "\n",
     "# Access the position of the second player\n",
-    "second_player_position = None  # Access the second position\n",
+    "second_player_position = team_info[\"Positions\"][1] # Access the second position\n",
     "\n",
     "# Count the number of \"Guards\"\n",
-    "guard_count = None  # Count how many times \"Guard\" appears in the positions list\n",
+    "i = 0\n",
+    "guard_count = 0\n",
+    "for i in range(len(team_info[\"Positions\"])):\n",
+    "    position = team_info[\"Positions\"][i]\n",
+    "    if position.find(\"Guard\") > 0:\n",
+    "        guard_count += 1\n",
+    "   \n",
+    "\n",
+    " # Count how many times \"Guard\" appears in the positions list\n",
     "\n",
     "# Print the results\n",
     "print(\"Team Info:\", team_info)\n",
@@ -206,18 +261,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 173,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total Players: 18\n",
+      "Unique Positions: 5\n",
+      "Is Jordan Smith the Captain? No\n"
+     ]
+    }
+   ],
    "source": [
     "# Calculate the number of players\n",
-    "total_players = None  # Use the len() function to calculate the number of players\n",
+    "total_players = len(players)  # Use the len() function to calculate the number of players\n",
     "\n",
     "# Calculate the number of unique positions\n",
-    "unique_positions = None  # Use the set() function to find unique positions\n",
+    "\n",
+    "unique_positions = len(set(\"Positions\")) - 1  # Use the set() function to find unique positions\n",
     "\n",
     "# Check if \"Jordan Smith\" is the team captain\n",
-    "is_captain = None  # Use a comparison to check if \"Jordan Smith\" is the captain\n",
+    "\n",
+    "if team_captain == \"Jordan Smith\":\n",
+    "    is_captain = \"Yes\"\n",
+    "else:\n",
+    "    is_captain = \"No\"\n",
+    "\n",
+    " # Use a comparison to check if \"Jordan Smith\" is the captain\n",
     "\n",
     "# Print the results\n",
     "print(\"Total Players:\", total_players)\n",
@@ -254,9 +326,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (learn-env)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "learn-env"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -268,7 +340,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,

Mod0/CodeChallenges/Lecture9CC.ipynb

@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -78,29 +78,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Import the JSON module\n",
-    "None"
+    "import json"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Movie Titles: Inception\n",
+      "Movie Titles: The Dark Knight\n",
+      "Movie Titles: Interstellar\n",
+      "Movie Titles: The Godfather\n"
+     ]
+    }
+   ],
    "source": [
     "# Step 1: Extract Movie Titles\n",
     "# Write a loop to extract and print the titles of all movies\n",
-    "for movie in None:\n",
-    "    print(\"Movie Titles:\")"
+    "for movie in data[\"movies\"]:\n",
+    "    print(\"Movie Titles:\", movie[\"title\"])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -110,17 +121,25 @@
     "\n",
     "def find_movies_by_genre(genre):\n",
     "    movies_in_genre = []\n",
-    "    for movie in None:\n",
-    "        if None:\n",
-    "            movies_in_genre.append(None)\n",
+    "    for movie in data[\"movies\"]:\n",
+    "        if genre == movie['genre']:\n",
+    "            movies_in_genre.append(movie[\"title\"])\n",
     "    return movies_in_genre"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Inception', 'Interstellar']\n"
+     ]
+    }
+   ],
    "source": [
     "# Test the function run this cell without changes\n",
     "genre = \"Sci-Fi\"\n",
@@ -130,45 +149,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 54,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Average IMDb Rating: 8.9\n"
+     ]
+    }
+   ],
    "source": [
     "# Step 3: Calculate Average IMDb Rating\n",
     "# Write a loop to calculate the average IMDb rating of all movies\n",
     "# Replace this with a loop to calculate the total IMDb rating and count of movies\n",
     "total_rating = 0\n",
     "movie_count = 0\n",
-    "for movie in None:\n",
-    "    total_rating += movie[\"ratings\"][\"IMDB\"] \n",
+    "for movie in data['movies']:\n",
+    "    total_rating += movie[\"ratings\"][\"IMDb\"] \n",
     "    movie_count += 1\n",
-    "average_rating = None  # Replace this with the formula to calculate the average\n",
-    "print(\"Average IMDb Rating:\", average_rating)"
+    "average_rating = total_rating/movie_count  # Replace this with the formula to calculate the average\n",
+    "print(\"Average IMDb Rating:\", round(average_rating,2))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 59,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Highest Rated Movie (IMDb): The Godfather\n"
+     ]
+    }
+   ],
    "source": [
     "# Step 4: Find the Highest Rated Movie (IMDb)\n",
     "# Write a loop to find the movie with the highest IMDb rating\n",
     "# Replace this with a loop to find the highest-rated movie\n",
     "highest_rating = 0\n",
-    "for movie in None:\n",
-    "    if movie[\"ratings\"][\"IMDb\"] > None:\n",
+    "for movie in data['movies']:\n",
+    "    if movie[\"ratings\"][\"IMDb\"] > highest_rating:\n",
     "        highest_rating = movie[\"ratings\"][\"IMDb\"]\n",
-    "        highest_rated_movie = None\n",
+    "        highest_rated_movie = movie['title']\n",
     "print(\"Highest Rated Movie (IMDb):\", highest_rated_movie)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (learn-env)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "learn-env"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -180,7 +215,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,