4. Filtering in Pandas

  1. Display only customer ID, name, email, phone, and address columns of the top 3 rows.

Solution
import pandas as pd
df=pd.read_csv('retail_data.csv')
df.iloc[0:3,1:6]
# this can also be done by df.head(3)[['Customer_ID', 'Name', 'Email', 'Phone', 'Address']]

# Output
    Customer_ID	Name	Email	Phone	Address
0	37249	Michelle Harrington	Ebony39@gmail.com	1414786801	3959 Amanda Burgs
1	69749	Kelsey Hill	Mark36@gmail.com	6852899987	82072 Dawn Centers
2	30192	Scott Jensen	Shane85@gmail.com	8362160449	4133 Young Canyon

  1. Display the last 5 rows and first 5 columns of the dataset.

Solution
df.iloc[-5:,0:5]

# Output

        Transaction_ID	Customer_ID	Name	Email	Phone
293906	4246475	12104	Meagan Ellis	Courtney60@gmail.com	7466353743
293907	1197603	69772	Mathew Beck	Jennifer71@gmail.com	5754304957
293908	7743242	28449	Daniel Lee	Christopher100@gmail.com	9382530370
293909	9301950	45477	Patrick Wilson	Rebecca65@gmail.com	9373222023
293910	2882826	53626	Dustin Merritt	William14@gmail.com	9518926645

  1. Display the last 7 rows and last 7 columns.

Solution
df.iloc[-7:,-7:]

# Output

Product_Type	Feedback	Shipping_Method	Payment_Method	Order_Status	Ratings	products
293904	Tablet	Average	Same-Day	Cash	Pending	2	Amazon Fire Tablet
293905	Shorts	Excellent	Standard	Cash	Delivered	4	Chino shorts
293906	Fiction	Bad	Same-Day	Cash	Processing	1	Historical fiction
293907	Laptop	Excellent	Same-Day	Cash	Processing	5	LG Gram
293908	Jacket	Average	Express	Cash	Shipped	2	Parka
293909	Furniture	Good	Standard	Cash	Shipped	4	TV stand
293910	Decorations	Average	Same-Day	Cash	Shipped	2	Clocks

  1. Retrieve the first 3 rows

Solution
df.iloc[:3]

# Output

Transaction_ID	Customer_ID	Name	Email	Phone	Address	City	State	Zipcode	Country	...	Total_Amount	Product_Category	Product_Brand	Product_Type	Feedback	Shipping_Method	Payment_Method	Order_Status	Ratings	products
0	8691788	37249	Michelle Harrington	Ebony39@gmail.com	1414786801	3959 Amanda Burgs	Dortmund	Berlin	77985	Germany	...	324.086270	Clothing	Nike	Shorts	Excellent	Same-Day	Debit Card	Shipped	5	Cycling shorts
1	2174773	69749	Kelsey Hill	Mark36@gmail.com	6852899987	82072 Dawn Centers	Nottingham	England	99071	UK	...	806.707815	Electronics	Samsung	Tablet	Excellent	Standard	Credit Card	Processing	4	Lenovo Tab
2	6679610	30192	Scott Jensen	Shane85@gmail.com	8362160449	4133 Young Canyon	Geelong	New South Wales	75929	Australia	...	1063.432799	Books	Penguin Books	Children's	Average	Same-Day	Credit Card	Processing	2	Sports equipment

  1. Display the rows where the order status is shipped.

Solution

  1. Display the data of Berlin state.

Solution

  1. Display the data for the electronics and clothing category only.

Solution

  1. Display the data of Germany where ratings are between 3-5(inclusive).

Solution

  1. Display the data of Adidas and Nike with excellent feedback.

Solution

  1. Display orders shipped to Canada with a rating of 3 or higher.

Solution

  1. Find orders where the total amount is greater than $1,000, the payment method is "Credit Card," and the product category is "Electronics."

Solution

  1. Find the companies that have excellent feedback for electronics in the American market.

Solution
242KB
sample_iowa_liquor_sales.csv
Open

  1. Create a sample of 50 rows from the above dataset.

Solution

  1. Display the first 10 rows of the last 10 columns.

Solution

  1. Display the sale records of Polk County but the sale value must be above 500.

Solution

  1. Find out the sales in Linn county but the bottle volume must be more than 1000ml.

Solution

  1. Display sales records where "Bottle Volume (ml)" is either 500 or 1000, and the "Sale (Dollars)" is over $700.

Solution

  1. Show the sales of happened on 10-10-2012 and 11/26/2013 only.

Solution
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