How to get all the linked elements (rows) which are repeated in pandas (Python)?-CodePudding

I'm trying to get all the food-id which has been consumed by a customer. If i give an input of lets say a customerId = C15, then it should return all the food_id's which customer has a link. I tried something.

import datetime
import random
import pandas as pd

pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)

df = pd.DataFrame({
'food_id':['B1', 'CF', 'C1', 'CF', 'B1', 'IO', 'B1', 'FT', 'BR','CF', 'C1', 'SM', 'IC','B1', 'SM'],
'purch_amt':[150.5, 270.65, 65.26, 110.5, 948.5, 2400.6, 5760, 1983.43, 2480.4, 250.45, 75.29, 3045.6, 500, 500, 250],
'ord_date': ['05-10-2022','09-10-2022','05-10-2022','08-17-2022','10-09-2022','07-27-2022','10-09-2022','10-10-2022','10-10-2022','06-17-2022','07-08-2022','04-25-2022','02-08-2022','08-08-2022','07-09-2022'],
'customer_id':['C31','C31','D35','D31','C35','D31','C35','D31','D35','C31','D35','D35','D35','C35','C38']})


def get_mostly_ordered_food_id():
    print('Max food_id ordered')
    result = df['food_id'].value_counts().rename_axis('food_id').reset_index(name='counts')
    df2 = pd.DataFrame(result)
    print(df2.head(3))

def show_data():
    result = df.groupby(['customer_id'])
    print(result.first())

def test_add_data():
    foodID = ['B1', 'CF', 'C1', 'IO', 'FT', 'BR', 'IC', 'SM']
    customerID = ['C31','D35','D31','C35','C38']
    date = 'Test-Data'
    for i in range(0,10):
        df.loc[len(df.index)] = [random.choice(customerID), random.choice(foodID), date, 500]
    print(df)
    get_mostly_ordered_food_id()

If i give an input,say a customer ID then it should return all the food-id which has been consumed. also I should not repeat.

trying to get. e.g. --> input - C15 (which is customer id)

it should return --> B1, C2 (which is food ids) with no duplication. (if any duplication is there, it should throw a warning.)

Thanks

CodePudding user response：

Maybe something like this would work.

# The input customer id
customer_id = "C31"

# Select rows with the given customer id
df_customer = df[df['customer_id'] == customer_id]

# Get the list of unique food ids consumed by the customer
food_ids = df_customer['food_id'].unique()

# Print the list of food ids
print(food_ids)