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commit
7aeb189308
167
.ipynb_checkpoints/Wizualizacja-checkpoint.ipynb
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167
.ipynb_checkpoints/Wizualizacja-checkpoint.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 67,
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"id": "9d832900",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import re\n",
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"\n",
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"pd.set_option('display.max_rows', 10000)\n",
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"pd.set_option('display.max_columns', 10000)\n",
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"\n",
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"file_path = 'games.csv'\n",
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"\n",
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"data = pd.read_csv(file_path) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 84,
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"id": "84d9af06",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['Qd1', 'Qc2', 'Qc3', 'Qb3', 'Qb7+', 'Qxd7#']\n",
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"['Qd1', 'Qxd4', 'Qd1', 'Qa4', 'Qh4', 'Qxg5', 'Qg3', 'Qxg6']\n",
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"Square names from list1: ['d1', 'c2', 'c3', 'b3', 'b7', 'd7']\n",
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"Square names from list2: ['d1', 'd4', 'd1', 'a4', 'h4', 'g5', 'g3', 'g6']\n"
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]
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}
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],
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"source": [
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"import re\n",
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"\n",
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"def extract_square_names(moves_list):\n",
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" square_names = []\n",
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"\n",
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" for move in moves_list:\n",
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" # Use a regular expression to match the chess square name\n",
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" match = re.search(r'[a-h][1-8]', move)\n",
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" if match:\n",
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" square_names.append(match.group())\n",
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"\n",
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" return square_names"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 85,
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"id": "1f11b18c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['Qd1', 'Qxd4', 'Qd1', 'Qa4', 'Qh4', 'Qxg5', 'Qg3', 'Qxg6']\n",
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"White queen moves: ['d1', 'd4', 'd1', 'a4', 'h4', 'g5', 'g3', 'g6']\n",
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"['Qd8', 'Qe7', 'Qc7', 'Qg7', 'Qxg6']\n",
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"Black queen moves: ['d8', 'e7', 'c7', 'g7', 'g6']\n"
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]
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}
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],
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"source": [
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"opening_number_of_games = data['opening_name'].value_counts()\n",
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"opening_number_of_games.head(10)\n",
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"# openings = ['Sicilian Defense', 'Old Benoni Defense', \"Queen's Pawn Game: Mason Attack\"]\n",
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"\n",
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"old_benoni_games = data[data['opening_name'].str.contains('Old Benoni Defense', case = False)]\n",
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"old_benoni_count = len(old_benoni_games)\n",
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"\n",
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"for text in old_benoni_games.head(1)['moves']:\n",
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" moves = text.split()\n",
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" white_queen_moves = ['Qd1']\n",
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" black_queen_moves = ['Qd8']\n",
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" for idx, move in enumerate(moves):\n",
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" if move.startswith(\"Q\"):\n",
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" if idx % 2 == 0:\n",
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" white_queen_moves.append(move)\n",
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" if idx % 2 == 1:\n",
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" black_queen_moves.append(move)\n",
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"# print(f'White queen moves: {white_queen_moves}')\n",
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"# print(f'Black queen moves: {black_queen_moves}')\n",
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" print(f'White queen moves: {extract_square_names(white_queen_moves)}')\n",
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" print(f'Black queen moves: {extract_square_names(black_queen_moves)}')\n",
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"# list1 = ['Qd1', 'Qc2', 'Qc3', 'Qb3', 'Qb7+', 'Qxd7#']\n",
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"# list2 = ['Qd1', 'Qxd4', 'Qd1', 'Qa4', 'Qh4', 'Qxg5', 'Qg3', 'Qxg6']\n",
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"# print(white_queen_moves)\n",
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"# print(list1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "e0e4858a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"opening_name\n",
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"Alekhine Defense: Exchange Variation 9.0\n",
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"Anderssen Opening 1.0\n",
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"Benko Gambit Accepted | Fully Accepted Variation 9.0\n",
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"Benko Gambit Declined | Quiet Line 7.0\n",
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"Benoni Defense: Benoni-Indian Defense 4.0\n",
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" ... \n",
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"Trompowsky Attack 3.0\n",
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"Van Geet Opening: Dunst-Perrenet Gambit 5.0\n",
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"Vienna Game #2 6.0\n",
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"Vienna Game: Vienna Gambit | Main Line 6.0\n",
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"Yusupov-Rubinstein System 5.0\n",
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"Name: opening_ply, Length: 112, dtype: float64\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/var/folders/lm/cbc3n48n4x94zd3vf6zbbly40000gn/T/ipykernel_2729/977498901.py:12: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
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" filtered_data = data[data['white_rating'] > 2200][data['black_rating'] > 2200]\n"
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]
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}
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],
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"source": [
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"\n",
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"\n",
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"# Filtrowanie danych dla elo > 2200\n",
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"filtered_data = data[data['white_rating'] > 2200][data['black_rating'] > 2200]\n",
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"\n",
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"# Oblicz średnią opening_ply dla każdej unikalnej wartości w kolumnie 'opening'\n",
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"average_opening_ply = filtered_data.groupby('opening_name')['opening_ply'].mean()\n",
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"\n",
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"# Wyświetl średnie opening_ply dla każdej opening, dla elo > 2200\n",
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"print(average_opening_ply)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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150
wizualizacja/Wizualizacja.ipynb
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150
wizualizacja/Wizualizacja.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 86,
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"id": "e4b28b2f",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import re\n",
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"\n",
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"pd.set_option('display.max_rows', 10000)\n",
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"pd.set_option('display.max_columns', 10000)\n",
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"\n",
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"file_path = 'games.csv'\n",
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"\n",
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"data = pd.read_csv(file_path) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 87,
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"id": "e7264e32",
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"metadata": {},
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"outputs": [],
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"source": [
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"import re\n",
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"\n",
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"def extract_square_names(moves_list):\n",
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" square_names = []\n",
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"\n",
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" for move in moves_list:\n",
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" # Use a regular expression to match the chess square name\n",
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" match = re.search(r'[a-h][1-8]', move)\n",
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" if match:\n",
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" square_names.append(match.group())\n",
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"\n",
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" return square_names"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 88,
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"id": "d3157e88",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"White queen squares: ['d1', 'd4', 'd1', 'a4', 'h4', 'g5', 'g3', 'g6']\n",
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"Black queen squares: ['d8', 'e7', 'c7', 'g7', 'g6']\n"
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]
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}
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],
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"source": [
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"opening_number_of_games = data['opening_name'].value_counts()\n",
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"opening_number_of_games.head(10)\n",
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"# openings = ['Sicilian Defense', 'Old Benoni Defense', \"Queen's Pawn Game: Mason Attack\"]\n",
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"\n",
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"old_benoni_games = data[data['opening_name'].str.contains('Old Benoni Defense', case = False)]\n",
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"old_benoni_count = len(old_benoni_games)\n",
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"\n",
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"for text in old_benoni_games.head(1)['moves']:\n",
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" moves = text.split()\n",
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" white_queen_moves = ['Qd1']\n",
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" black_queen_moves = ['Qd8']\n",
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" for idx, move in enumerate(moves):\n",
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" if move.startswith(\"Q\"):\n",
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" if idx % 2 == 0:\n",
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" white_queen_moves.append(move)\n",
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" if idx % 2 == 1:\n",
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" black_queen_moves.append(move)\n",
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" white_queen_squares = extract_square_names(white_queen_moves)\n",
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" black_queen_squares = extract_square_names(black_queen_moves)\n",
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" print(f'White queen squares: {white_queen_squares}')\n",
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" print(f'Black queen squares: {black_queen_squares}')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "fdd92a15",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"opening_name\n",
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"Alekhine Defense: Exchange Variation 9.0\n",
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"Anderssen Opening 1.0\n",
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"Benko Gambit Accepted | Fully Accepted Variation 9.0\n",
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"Benko Gambit Declined | Quiet Line 7.0\n",
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"Benoni Defense: Benoni-Indian Defense 4.0\n",
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" ... \n",
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"Trompowsky Attack 3.0\n",
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"Van Geet Opening: Dunst-Perrenet Gambit 5.0\n",
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"Vienna Game #2 6.0\n",
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"Vienna Game: Vienna Gambit | Main Line 6.0\n",
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"Yusupov-Rubinstein System 5.0\n",
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"Name: opening_ply, Length: 112, dtype: float64\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/var/folders/lm/cbc3n48n4x94zd3vf6zbbly40000gn/T/ipykernel_2729/977498901.py:12: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
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" filtered_data = data[data['white_rating'] > 2200][data['black_rating'] > 2200]\n"
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]
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}
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],
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"source": [
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"\n",
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"\n",
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"# Filtrowanie danych dla elo > 2200\n",
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"filtered_data = data[data['white_rating'] > 2200][data['black_rating'] > 2200]\n",
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"\n",
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"# Oblicz średnią opening_ply dla każdej unikalnej wartości w kolumnie 'opening'\n",
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"average_opening_ply = filtered_data.groupby('opening_name')['opening_ply'].mean()\n",
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"\n",
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"# Wyświetl średnie opening_ply dla każdej opening, dla elo > 2200\n",
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"print(average_opening_ply)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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20059
wizualizacja/games.csv
Normal file
20059
wizualizacja/games.csv
Normal file
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