Pandas SQL Query: Count the NaN values of all the columns of locations file

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

Write a Pandas program to count the NaN values of all the columns of 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("\nNaN values of all the columns of locations file:" )
print(locations.isna().sum())

Sample Output:

NaN values of all the columns of locations file:
location_id       0
street_address    0
postal_code       1
city              0
state_province    6
country_id        0
dtype: int64

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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