GW_fixtures.ipynb

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   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "\n",
    "# Fetch general information once and use it across functions to reduce API calls\n",
    "general_info = requests.get(\"https://fantasy.premierleague.com/api/bootstrap-static/\").json()\n",
    "teams = {team[\"id\"]: team[\"name\"] for team in general_info[\"teams\"]}\n",
    "positions = {position[\"id\"]: position[\"singular_name_short\"] for position in general_info[\"element_types\"]}\n",
    "\n",
    "def get_player_fixture_info(player_id, gameweek):\n",
    "    \"\"\"\n",
    "    Fetch fixture information for a given player and gameweek.\n",
    "    \"\"\"\n",
    "    player_info = requests.get(f\"https://fantasy.premierleague.com/api/element-summary/{player_id}/\").json()\n",
    "    fixtures = player_info[\"fixtures\"]\n",
    "    fixture = next((f for f in fixtures if f[\"event\"] == gameweek), None)\n",
    "    if fixture:\n",
    "        home_team = teams[fixture[\"team_h\"]]\n",
    "        away_team = teams[fixture[\"team_a\"]]\n",
    "        kickoff_time = fixture[\"kickoff_time\"]\n",
    "        is_home = fixture[\"is_home\"]\n",
    "        return home_team, away_team, kickoff_time, is_home\n",
    "    return None, None, None, None\n",
    "\n",
    "def get_player_position(element_type):\n",
    "    \"\"\"\n",
    "    Retrieve the player position using cached positions data.\n",
    "    \"\"\"\n",
    "    return positions.get(element_type)\n",
    "\n",
    "def get_team_name(team_id):\n",
    "    \"\"\"\n",
    "    Retrieve the team name using cached teams data.\n",
    "    \"\"\"\n",
    "    return teams.get(team_id)\n",
    "\n",
    "# Initialize lists to hold player data\n",
    "my_teams = []\n",
    "home_teams = []\n",
    "away_teams = []\n",
    "kickoff_times = []\n",
    "is_homes = []\n",
    "positions_list = []\n",
    "costs = []\n",
    "names = []\n",
    "ids = []\n",
    "\n",
    "gameweek = 26  # Define the gameweek\n",
    "\n",
    "# Iterate over player information to populate lists\n",
    "for player_info in general_info[\"elements\"]:\n",
    "    id = player_info[\"id\"]\n",
    "    name = f\"{player_info['first_name']} {player_info['second_name']}\"\n",
    "    team_id = player_info[\"team\"]\n",
    "    cost = player_info[\"now_cost\"]\n",
    "    element_type = player_info[\"element_type\"]\n",
    "    position = get_player_position(element_type)\n",
    "\n",
    "    home_team, away_team, kickoff_time, is_home = get_player_fixture_info(id, gameweek)\n",
    "\n",
    "    # Append player data to lists\n",
    "    ids.append(id)\n",
    "    names.append(name)\n",
    "    costs.append(cost)\n",
    "    positions_list.append(position)\n",
    "    my_teams.append(get_team_name(team_id))\n",
    "    home_teams.append(home_team)\n",
    "    away_teams.append(away_team)\n",
    "    kickoff_times.append(kickoff_time)\n",
    "    is_homes.append(is_home)\n",
    "\n",
    "# Create a DataFrame to hold all player data\n",
    "df = pd.DataFrame({\n",
    "    \"id\": ids,\n",
    "    \"name\": names,\n",
    "    \"position\": positions_list,\n",
    "    \"cost\": costs,\n",
    "    \"home_team\": home_teams,\n",
    "    \"away_team\": away_teams,\n",
    "    \"kickoff_time\": kickoff_times,\n",
    "    \"is_home\": is_homes,\n",
    "    \"team_x\": my_teams\n",
    "})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[df[\"team_x\"]==\"Liverpool\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(f\"C:\\\\Users\\\\prane\\\\Downloads\\\\FPL\\\\GW_PointsPredictor\\\\Default_data\\\\2023-24\\\\fixtures\\\\GW{gameweek}.csv\")"
   ]
  }
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