Pandas SQL Query: Create a boolean series selecting rows with one or more nulls from locations file

Last update on December 21 2024 07:55:09 (UTC/GMT +8 hours)

Write a Pandas program to create a boolean series selecting rows with one or more nulls from locations file.

LOCATIONS.csv

Sample Solution :

Python Code :

import pandas as pd
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
employees = pd.read_csv(r"EMPLOYEES.csv")
departments = pd.read_csv(r"DEPARTMENTS.csv")
job_history = pd.read_csv(r"JOB_HISTORY.csv")
jobs = pd.read_csv(r"JOBS.csv")
countries = pd.read_csv(r"COUNTRIES.csv")
regions = pd.read_csv(r"REGIONS.csv")
locations = pd.read_csv(r"LOCATIONS.csv")
print(locations.isnull())

Sample Output:

    location_id  street_address  postal_code   city  state_province  	  country_id
0         False           False        False  False            True 		False  
1         False           False        False  False            True 		False  
2         False           False        False  False           False 		False  
3         False           False        False  False            True 		False  
4         False           False        False  False           False		False		   
5         False           False        False  False           False 		False  
6         False           False        False  False           False 		False		 
7         False           False        False  False           False		False   
8         False           False        False  False           False 		False  
9         False           False        False  False           False 		False  
10        False           False        False  False            True 		False  
11        False           False        False  False           False  		False 
12        False           False        False  False           False 		False  
13        False           False        False  False            True  		False 
14        False           False         True  False            True  		False 
15        False           False        False  False           False 		False  
16        False           False        False  False           False  		False 
17        False           False        False  False           False 		False  
18        False           False        False  False           False 		False  
19        False           False        False  False           False  		False 
20        False           False        False  False           False  		False 
21        False           False        False  False           False 		False  
22        False           False        False  False           False  		False   

Click to view the table contain:

Employees Table

Departments Table

Countries Table

Job_History Table

Jobs Table

Locations Table

Regions Table

Python Code Editor:

Structure of HR database :

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