基于dataframe中的多個條件設置python變量

另一種可能的解決方案：

mydate = datetime.now().date()
df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%Y').dt.date
last_apple_sales = df.loc[(df['Date'] == mydate) & (
    df['Product'] == 'apple'), 'Sales'].squeeze()

但是，如果您的目標是重復執行，那么最好是創建一個函數：

def last_sales(df, mydate, product):
    df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%Y').dt.date
    return df.loc[(df['Date'] == mydate) & (df['Product'] == product), 'Sales'].squeeze()

mydate = datetime.now().date()
last_sales(df, mydate, 'apple')

Complete code:

import pandas as pd
import numpy as np
from io import StringIO
from datetime import datetime

text = """
Date         Product  Sales
28/09/2022   apple    10.2
28/09/2022   orange   5.1
28/09/2022   pear     12.3 
27/09/2022   apple    4.1
27/09/2022   orange   3.9
27/09/2022   pear     15.0
"""

df = pd.read_csv(StringIO(text), sep='\s+')

def last_sales(df, mydate, product):
    df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%Y').dt.date
    return df.loc[(df['Date'] == mydate) & (df['Product'] == product), 'Sales'].squeeze()

mydate = datetime.now().date()
last_sales(df, mydate, 'apple')