here is the example of the question
import pandas as pd
# read excel file
df = pd.read_excel("C:/Users/samer/Desktop/project/online_retail2.xlsx")
df.head()
# is gonna remove nan from the equation
df = df.dropna()
columns = list(df.columns)
columns = [x.lower() for x in columns]
df.columns = columns
#task 2.1
df['stockcode'] = df['stockcode'].apply(str)
df["products ordered by individuals"] = df["description"] + [' '] + df["stockcode"]
top_products = df['products ordered by individuals'].value_counts()[:10]
print('Top 10 products ordered by individuals:\n' , top_products)
#task 2.2
df['sales'] = df['price'] * df['quantity']
The_most_money_spent= df.groupby("customer id").sum().sort_values("sales", ascending=False).head(10)
print("Top ten customers who spent most money are: \n" ,The_most_money_spent)
#task 2.3
top_orders_were_placed = df[['invoicedate','sales']].value_counts('sales','invoicedate',
ascending=False)
top_orders_were_placed.head(5)
df['orders']= df[['sales', 'invoicedate']]
top_orders_were_placed= df['orders'].value_counts(ascending=False)
top_orders_were_placed.head()
I'm trying to find a way to get the greatest number of products, but I just don't know how to use or find the date from the file. despite numerous attempts, I just can't figure it out, and it's been 2 days, so what exactly should I use?