Pandas HR database: Count the NaN values of all the columns of locations file
Pandas HR database Queries: Exercise-14 with Solution
Write a Pandas program to count the NaN values of all the columns of locations file.
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())
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:
Python Code Editor:
Structure of HR database :
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Previous: Write a Pandas program to create a boolean series selecting rows with one or more nulls from locations file.
Next: Write a Pandas program to display the first name, last name, salary and department number for those employees whose first name ends with the letter 'm'.
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