如何从数据集中调用并让它比较 python 中的两个不同数据点？

Question

I'm not very good with python.

Answer 1

You can use pandas library to access the values in the dataset which you wanted to use as a criterion to predict the win. You should make a function and in it apply your way.

#Index-based selection¶
#Pandas indexing works in one of two paradigms. The first is index-based selection: selecting data based on its numerical position in the data. iloc follows this paradigm.
#To select the first row of data in a DataFrame, we may use the following:

df.iloc[0]
#to get a column
df.iloc[:, 0]
df.iloc[[0, 1, 2], 0]
#Label-based selection
#The second paradigm for attribute selection is the one followed by the loc operator: label-based selection. In this paradigm, it's the data index value, not its position, which matters.
#For example, to get the first entry in reviews, we would now do the following:
df.loc[0, 'country']
df.loc[:, ['taster_name', 'taster_twitter_handle', 'points']]
cols=['dc','adfa','fas']
indiecs-[0,1,10,14]
df.loc[indiecs,cols]

Answer 2

I added a few extras in there, but basically,

1. You need to somehow get the inputs of the 2 players you want.
2. Filter out your dataframe to get those particular player stats
3. Compare those stats and score them in some way
4. Sum up the scores for each category/colum
5. Print out the results

Code:

#pip install fuzzywuzzy
#pip install choice

import pandas as pd
import numpy as np
from fuzzywuzzy import process
import choice


df = pd.read_csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vSTbHMm7RQOxOj6yl17g7MLfCBFghAACUie0k3HLB_ja9E0t0HpENl4ydN4b58UdCCiBTB9rvj0zy-O/pub?output=csv")
choices = list(df['PLAYER'])

def select_player(choices, player_no):
    player = input('Type player %s: ' %player_no)
    if 100 not in [x[1] for x in process.extract(player, choices, limit=5)]:
        print('Which player did you mean?')
        player = choice.Menu([x[0] for x in process.extract(player, choices, limit=5)]).ask()
    else:
        player = process.extract(player, choices, limit=5)[0][0]
    print('You selected: %s' %player)
    return player


def play_game(player_1, player_2):    
    player_1_stats = df[df['PLAYER'] == player_1]
    player_2_stats = df[df['PLAYER'] == player_2]
    
    score = player_1_stats.append(player_2_stats).reset_index(drop=True)
    
    num_cols = list(score.select_dtypes('number').columns)
    for col in num_cols:
        winning_score = score[col].max()
        score[col] = np.where(score[col] == winning_score, 1,0)
    score['Total'] = score[num_cols].sum(axis=1)
    
    print(score[['PLAYER','Total']])
    
player_1 = select_player(choices, 1)
player_2 = select_player(choices, 2)

play_game(player_1, player_2)

Output:

Type player 1: james harden
You selected: James Harden

Type player 2: Jim Butler
Which player did you mean?
Make a choice:
 0: Jimmy Butler
 1: Ben Simmons
 2: Devin Booker

Enter number or name; return for next page

? 0

You selected: Jimmy Butler

          PLAYER  Total
0  James Harden      4
1  Jimmy Butler      3