Filter

Learn how can we use filtering in pandas

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retail_sales_dataset.csv

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retail sales dataset

Date	Customer ID	Gender	Age	Product Category	Quantity	Price per Unit
11/24/2023	CUST001	Male	34	Beauty	3	50
2/27/2023	CUST002	Female	26	Clothing	2	500
1/13/2023	CUST003	Male	50	Electronics	1	30
5/21/2023	CUST004	Male	37	Clothing	1	500
5/6/2023	CUST005	Male	30	Beauty	2	50
4/25/2023	CUST006	Female	45	Beauty	1	30
3/13/2023	CUST007	Male	46	Clothing	2	25
2/22/2023	CUST008	Male	30	Electronics	4	25
12/13/2023	CUST009	Male	63	Electronics	2	300
10/7/2023	CUST010	Female	52	Clothing	4	50
2/14/2023	CUST011	Male	23	Clothing	2	50
10/30/2023	CUST012	Male	35	Beauty	3	25

Filter to get the first row

To get the first row , all you need to do is to pass index number of the row in loc.

# Assuming the DataFrame is named df
first_row = df.loc[0]
print(first_row)

Date	Customer ID	Gender	Age	Product Category	Quantity	Price per Unit
11/24/2023	CUST001	Male	34	Beauty	3	50

Filter to get specific rows

To get rows from index 3 to 7 using .loc, you can specify the index range. Here's how you can do it:

# Assuming the DataFrame is named df
rows_3_to_7 = df.loc[3:7]
print(rows_3_to_7)

This will output the following subset of the DataFrame:

Date	Customer ID	Gender	Age	Product Category	Quantity	Price per Unit
5/21/2023	CUST004	Male	37	Clothing	1	500
5/6/2023	CUST005	Male	30	Beauty	2	50
4/25/2023	CUST006	Female	45	Beauty	1	30
3/13/2023	CUST007	Male	46	Clothing	2	25
2/22/2023	CUST008	Male	30	Electronics	4	25

Filter to get specific row and specific columns

To get rows from index 3 to 7 and only the first 3 columns using .loc, you can specify both the index range and the columns you want. Here's how you can do it:

# Assuming the DataFrame is named df
rows_3_to_7_columns_1_to_3 = df.loc[3:7, df.columns[:3]]
print(rows_3_to_7_columns_1_to_3)

This will output the following subset of the DataFrame:

Date	Customer ID	Gender
5/21/2023	CUST004	Male
5/6/2023	CUST005	Male
4/25/2023	CUST006	Female
3/13/2023	CUST007	Male
2/22/2023	CUST008	Male